Golf game result simulation modeling system

Abstract

An updated hybrid golf tournament simulation method may include generating a predicted hole score for each hole per turn of a golf tournament. A predicted hole score may be generated using collective historical and historical player data corresponding to historical occurrences of one or more hole events related to a golf game to calculate a probability of the hole event as a weight to generate a predicted result of the hole event. A score probability distribution may be assigned to the prediction result to generate a predicted hole score. The simulation may be analyzed to obtain a prediction result probability, such as a winning probability, a promotion probability, or a probability of entering the first 10 names. The simulation may be updated during the actual competition of the tournament by replacing the predicted score with the actual score, thereby further updating the predicted result probability.

Description

Technical Field

[0001] The present disclosure relates to the management of golf tournaments, including result simulation, and may also include real-time simulation updates. Background Art

[0002] There are many golf tournaments available for golfers to participate in. In a professional setting, tournaments are typically associated with one of the many organized golf tours. For example, the PGA TOUR is the world's leading membership organization for professional golfers to conduct tours, and it jointly sanctions the PGA Tour, the PGA Tour Champions, the Korn Ferry Tour, the PGA Tour Latinoamérica, and the PGA Tour Canada. Each tour usually includes multiple tournament events within a season, during which players participate in each tournament throughout the season. For example, some tours use a points system to rank players within a season, awarding points based on the position obtained in each tournament. The points accumulated by a player can be used to determine their eligibility to participate in the playoffs or the championship tournament during the season. In some cases, the accumulated points can be used to determine eligibility to participate in the same or other tours and events in future seasons.

[0003] The points system should be able to reflect a player's playing level during the season, while also providing excitement by offering a format in which multiple players can compete for the top ranking throughout the season. It is important to strike a balance between these broad goals from the perspective of both players and fans.

[0004] Systems and methods are needed for evaluating the potential impact of different schedules and points systems. Summary of the Invention

[0005] In one aspect, a method of updating a golf tournament simulation is configured to mix simulation updates that update the simulation based on the actual play of a simulated golf tournament. In one configuration, the method includes: retrieving relevant aggregate history and historical player data from a statistical database to generate a hole event probability for each hole event in one or more hole events for each hole in a round; processing the aggregate history and historical player data through a hole event probability algorithm to generate a hole event probability for each hole event; using the generated hole event probabilities as weights in a weighted random generator algorithm to calculate a predicted hole event outcome for each hole event; assigning a score probability distribution to each hole, the score probability distribution corresponding to one or more predicted hole event outcomes for the hole; and inputting the assigned score probability distribution into a random score selector algorithm to generate a predicted hole score for each hole. The method may further include: generating a predicted round score based on the predicted hole scores; repeating the generation of the predicted round scores for all tournament rounds for each competing player and further repeating to generate multiple tournament simulations; calculating one or more outcome probabilities from the multiple tournament simulations; storing the tournament simulations for update processing; and updating all simulations as needed during the actual conduct of the tournament and updating the predicted outcome probabilities.

[0006] In one example, the predicted round score is the sum of the predicted hole scores for each hole in the round.

[0007] In the above or other examples, the predicted round score includes an adjusted sum of the predicted hole scores for the round, or a sum of the adjusted predicted hole scores for the round.

[0008] In one example, the method includes: applying a score adjustment based at least in part on the historical player data of the simulated player. The adjustment may be applied to each hole score or the predicted round score. The historical player data may include the variance of the player in actual historical play. In one configuration, the variance of the player in actual historical play may be the variance of the corresponding tournament round of the simulated round relative to the average score of all tournament rounds. In some settings, the adjustment to the predicted hole score may be based on the difference between the average round score of the simulated player in all tournament rounds and the average round score of the player in the tournament in the particular simulated round. In one example of applying the score adjustment, if there is a historical play variance of the average round score of the simulated player in the simulated round relative to the average round score of the player in all tournament rounds, a round adjustment may be applied to each predicted hole score output by the random score selector algorithm or to the round score calculated from the predicted hole scores.

[0009] In any of the above or other examples, the historical competition includes a rolling average over one or more seasons. In this or other configurations, more recent historical data points in the historical competition are weighted more heavily.

[0010] In any of the above or other examples, the method may include: applying a cut line protocol to each tournament simulation according to tournament rules, and not including the predicted round scores of the match play rounds in the predicted tournament scores of players predicted to not advance. In one configuration, the cut line protocol includes: simulating rounds for the qualifying rounds to generate predicted round scores for all players in each qualifying round; establishing a tournament cut line based on the predicted round scores from the qualifying rounds; and simulating rounds for the match play rounds of the players predicted to advance to generate predicted round scores for the players predicted to advance in the match play rounds. In another configuration, the cut line protocol includes: simulating rounds for the qualifying rounds and the match play rounds to generate predicted round scores for all players in the qualifying rounds and the match play rounds, and establishing a golf tournament cut line based on the predicted round scores from the qualifying rounds.

[0011] In any of the above or other examples, the hole event probability corresponds to the probability of a hole event occurring on the hole.

[0012] In any of the above or other examples, the relevant collective history and historical player data represent the historical occurrences of hole events in actual competitions in tournaments at the same or similar levels.

[0013] In any of the above or other examples, the relevant collective history data represents the historical occurrences of hole events for the collective players on multiple holes and the specific hole being simulated in an actual tournament, and the historical player data represents the historical occurrences of retained events for the player being simulated on multiple holes.

[0014] In any of the above or other examples, the relevant collective history and historical player data correspond to the occurrences of hole events on holes where the hole attributes correspond to the hole being simulated. For example, the attribute may be the par value.

[0015] In any of the above or other examples, the hole event result of the first hole event of the first hole specifies the elements required to identify the relevant collective history and historical player data for generating the hole event probability of the second hole event of the first hole.

[0016] In any of the above or other examples, the method further includes: calculating that the hole event probability for par 4 and / or par 5 holes is greater than the hole event probability for par 3 holes.

[0017] In any of the above or other examples, one or more hole events include a first hole event, where the first hole event includes a hitting location of a tee shot, and the first hole event probability includes the probability that a player's tee shot hits the hitting location. In one example, the result of the hitting location of the tee shot is based on the attributes of the hole. For example, the attribute of the hole can be the par rating of the hole. The first hole event probability for a par-4 hole can include the probability that a player's tee shot hits the fairway, and the first hole event probability for a par-3 hole can include the probability that a player's tee shot hits the green. In some configurations, at least one hole includes a second hole event, which includes a hitting location of a subsequent shot. The result of the subsequent hitting location can correspond to the attributes of the hole. In one example, the attribute is the par rating of the hole. For example, the second hole event probability for a par-4 hole can include the probability that a player hits the green from the location determined by the predicted result of the first hole event.

[0018] In any of the above or other examples, each hole includes a first hole event corresponding to a hitting position. The first hole event may correspond to a tee - off position hole event, including the green for a par - 3 hole and the fairway for par - 4 and par - 5 holes. The collective history and historical player data related to the tee - off position hole event may include: for a par - 3 hole: the player's green - in - regulation rate for the par - 3 hole, the collective green - in - regulation rate for the hole, and the collective green - in - regulation rate for par - 3 holes; and for par - 4 and par - 5 holes: the probability that a player hits the fairway for par - 4 and par - 5 holes, the collective probability of hitting the fairway for the hole, and the collective probability of hitting the fairway for par - 4 and par - 5 holes. In a further configuration, a second hole event including at least some holes is included. The second hole event may correspond to the hitting position after the tee - off shot. In one example, generating a predicted hole score for a par - 4 hole includes: retrieving relevant collective history and historical player data from a statistical database, using the predicted hole event position result of the tee - off position hole event calculated for the hole as a statistical position to calculate the probability of the subsequent hitting position hole event. Using the corresponding position hole event probability as a weight in a weighted random - generator algorithm, the predicted hole event position result of the subsequent hitting position hole event can be calculated. According to one method, in a manner similar to that of a par - 4 hole, the predicted hole result of the subsequent hitting position hole event for a par - 5 hole can be calculated. In one example, if the predicted hole event position result of the tee - off position hole event calculated for the hole is the fairway, the collective history and historical player data related to the subsequent hitting position hole event include historical statistical data corresponding to the historical occurrence of hitting the green from the fairway, including the player's green - in - regulation rate from the fairway for par - 4 and par - 5 holes, the collective green - in - regulation rate from the fairway for the hole, and the collective green - in - regulation rate from the fairway for par - 4 and par - 5 holes. If the predicted hole event position result of the tee - off position hole event calculated for the hole is not the fairway, the collective history and historical player data related to the subsequent hitting position hole event include historical statistical data corresponding to the historical occurrence of hitting the green from off - fairway, including the player's green - in - regulation rate from off - fairway for par - 4 and par - 5 holes, the collective green - in - regulation rate from off - fairway for the hole, and the collective green - in - regulation rate from off - fairway for par - 4 and par - 5 holes.

[0019] In any of the above or other examples, the hole event probability algorithm includes:

[0020]

[0021] where x is the historical incidence rate of a player performing a hole event, y is the collective historical incidence rate of the hole event on a specific hole, and z is the collective historical incidence rate of the hole event during play on multiple courses.

[0022] In one example, the first hole event probabilities for par 4 and par 5 holes include the probability that a player's tee shot hits the fairway. Let x be the probability that a player on par 4 and par 5 holes hits the fairway, y be the probability that the hole collective hits the fairway, and z be the probability that the par 4 and par 5 hole collective hits the fairway. The second hole event probabilities for par 4 and par 5 holes can include the probability that a player hits the green from a position specified by the prediction outcome of the first hole event on a subsequent shot. In one application, if the prediction outcome of the first hole event is hitting the fairway, the collective history and player collective history data correspond to the historical occurrences of hitting the green from the fairway. Here, x is the probability that a player on par 4 and par 5 holes gets on the green from the fairway, y is the probability that the hole collective gets on the green from the fairway, and z is the probability that the par 4 and par 5 hole collective gets on the green from the fairway. If the prediction outcome of the first hole event is missing the fairway, the historical statistics correspond to the historical occurrences of hitting the green from off the fairway. Here, x is the probability that a player on par 4 and par 5 holes gets on the green from off the fairway, y is the probability that the hole collective gets on the green from off the fairway, and z is the probability that the par 4 and par 5 hole collective gets on the green from off the fairway. In any of the above or other examples, the first hole event probability for a par 3 hole can include the probability that a player's tee shot hits the green. Let x be the probability that a player on a par 3 hole gets on the green, y be the probability that the hole collective gets on the green, and z be the probability that the par 3 hole collective gets on the green.

[0023] In any of the above or other examples, one or more predicted hole event outcomes for each hole are binary.

[0024] In any of the above or other examples, each hole is associated with multiple score probability distributions, where each score probability distribution corresponds to a specific predicted hole event outcome or a combination of predicted hole event outcomes for the hole. The score probability distribution can represent the historical score distribution of the hole in the presence of each potential hole event outcome or combination thereof. Assigning the score probability distributions can include pairing one or more predicted hole event outcomes of the hole with the score probability distributions corresponding to the predicted hole event outcomes.

[0025] In any example in the above or other examples, calculating one or more outcome probabilities includes calculating the probability of the predicted outcome, including: analyzing whether the predicted outcome appears in multiple simulations, and dividing the number of simulations in which the predicted outcome appears by the total number of simulations. In one example, one or more predicted outcomes include: scores or score ranges on one or more holes in one round of a tournament, scores or score ranges on one or more holes in two or more rounds of a tournament, hole events on one or more holes in one round of a tournament, hole events on one or more holes in two or more rounds of a tournament, or a combination thereof. In the above or other examples, one or more predicted outcomes include: scores within a specified score or a specified range in one or more rounds of a tournament, scores within a specified hole in one or more rounds of a tournament, or a combination thereof. In any example in the above or other examples, one or more predicted outcomes include: ranking of players by round finishing position, finishing position of players, finishing position range of players, or a combination thereof. In any example in the above or other examples, one or more predicted outcomes include: the probability of a player finishing the game with the lowest round score, the probability of a player finishing the game with a round score within a specified finishing position ranking, or a combination thereof. In any of the above or other examples, one or more prediction results include: ranking of a player's finishing position in one or more rounds of a tournament, ranking of a player's finishing position in a tournament, a player's finishing position in one or more rounds of a tournament, a range of finishing positions in one or more rounds of a tournament, a tournament win, promotion, a promotion line, or a combination thereof. In any of the above or other examples, one or more prediction results include: probability ranking of a player's finishing position in one or more rounds of a tournament, probability ranking of a player's finishing position in a tournament, probability of a player's finishing position in one or more rounds of a tournament, probability of a player finishing within a range of finishing positions in one or more rounds of a tournament, probability of a player winning a tournament, probability of a player advancing, promotion line probability, or a combination thereof. In one example, the prediction result probabilities include: probability of winning, probability of entering the top 10, probability of reaching the promotion line, and probability of promotion.

[0026] In any of the above or other examples, updating the simulation may include replacing the predicted hole score with the actual hole score when the player completes a hole-in, updating the predicted round score to take into account the replaced actual hole score, adding the updated predicted round scores in all tournament rounds to generate an updated predicted tournament score for the participating players, adding the updated predicted round scores in the preliminary round to establish an updated promotion line, counting the predicted round scores of the rematch rounds in the scores of the players who did not qualify, and not counting the predicted round scores of the rematch rounds in the scores of the players who did not qualify.

[0027] In any of the above or other examples, when actual in-play scoring data is received, the simulation can be updated at intervals of less than 30 seconds during the game. In one example, the update can be performed at intervals of less than 20 seconds, 15 seconds, 10 seconds, or 5 seconds. Updates can also be made based on scoring or shot events that occur during the actual tournament play.

[0028] In any of the above or other examples, the simulation is updated during the actual golf event until the event ends.

[0029] In any of the above or other examples, the method further includes: moving information for each player to a database using the player identification (ID) and timestamp to display the latest probabilities, thereby allowing for digital trend display on television broadcasts and digital platforms.

[0030] In another aspect, there is provided a machine-readable medium carrying machine-readable instructions that, when executed by a processor of a machine, cause the machine to perform the above method, including any combination of the related examples.

[0031] In another aspect, a system is provided that includes a processor and a storage medium storing instructions that, when executed by the processor, cause the system to perform the above-described method, including any combination of the related examples. In yet another aspect, a golf tournament simulation modeling system may include a statistical database that includes historical statistical data of golf tournaments. A hole event probability generator may be configured to use the historical statistical data to generate one or more hole event probabilities for each hole of each round of a golf tournament based on at least a portion of the historical statistical data. A hole event result generator may be configured to use the hole event probabilities as weights to generate hole event results. A hole event generator may include a weighted result generator or be configured to access the operations of a weighted result generator, the weighted result generator being configured to use the hole event probabilities as weights to generate the results of hole events. A hole score generator may be configured to assign a score probability distribution to each hole based on one or more hole event results generated for each hole. The hole score generator may include a score distribution engine or be configured to access the operations of a score distribution engine, the score distribution engine being configured to generate or provide a hole score probability distribution of potential combinations of hole event results. The hole score generator may include a random score generator or be configured to access the operations of a random score generator, the random score generator being configured to generate a random score based on the hole score probability distribution identified by the hole score generator. A prediction engine may be configured to output a prediction regarding a golf tournament. The prediction engine may include a prediction result generator that is configured to generate a prediction result. Additionally or alternatively, the prediction engine may include a prediction result probability generator that is configured to generate probabilities of one or more prediction results based on predictions of the prediction results in multiple simulations of the golf tournament. An update processor may be configured to update one or more prediction results and / or prediction result probabilities based on actual score data after the actual start of the tournament. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The novel features of the above-described embodiments are particularly set forth in the appended claims. However, the manner of organization and operation of the above-described embodiments may be best understood by reference to the following description taken in conjunction with the accompanying drawings, in which:

[0033] Figure 1 illustrates a simulation method for generating predicted round or tournament scores according to various embodiments described herein;

[0034] Figure 2 illustrates another aspect in which the simulation method according to various embodiments described herein Figure 1 is applied to a cut line.

[0035] Figure 3 illustrates the simulation method according to various embodiments described herein Figure 1The simulation method is applied to another aspect of the promotion line, as Figure 3 a supplement or alternative to the aspect shown;

[0036] Figure 4 shows another aspect of the simulation method for generating a predicted completion position according to various embodiments described herein;

[0037] Figure 5 shows another aspect of the simulation method for generating the probability of a predicted completion position according to various embodiments described herein;

[0038] Figure 6 shows another aspect of the simulation method for generating the probability of a prediction result according to various embodiments described herein;

[0039] Figure 7 schematically shows the implementation logic of an update processor for updating a prediction result and / or a prediction result probability based on replacing a predicted score with an actual score according to various embodiments described herein;

[0040] Figure 8 shows an actual score replacement method for updating a prediction result and / or a probability based on a simulation model according to various embodiments described herein;

[0041] Figure 9 shows a simulation modeling method according to various embodiments described herein;

[0042] Figure 10 shows a simulation modeling system according to various embodiments described herein; and

[0043] Figure 11 is a schematic diagram of a machine in the form of a computer system according to various embodiments described herein, and a set of instructions in the machine, when executed, can cause the machine to perform simulation modeling to generate a prediction result and its probability. Detailed Description

[0044] The points system plays an important role in the tournament season. The accumulated points can be used to rank the eligibility of players to participate in current and future season events, tournaments, classifications, and tours. There are countless potential variations that could be adopted in the points system. For example, players typically accumulate points in the tour schedule based on tournament results, with the first place receiving the highest points and subsequent places receiving gradually decreasing points. However, different tournaments can adopt different point allocation methods relative to the predicted finishing position and / or the total available point quota. Not all players are eligible to participate in every tournament, and even eligible players may choose not to participate in a particular tournament or may be eliminated and thus not receive points. To provide the best product to players and fans, it is crucial for tour organizers to find a fair points system and generate excitement throughout the season.

[0045] During the tournament season, predictions of a player's and / or course's tournament performance, either before or during a tournament, can be a valuable tool for tournament organizers and players in aspects such as event scheduling, broadcast programming, and match decisions. Performance predictions can also increase fan excitement by providing ongoing predictions that show how a player's actual performance dynamically changes the predicted performance outcome during the tournament, as some players exceed the predicted performance while others fall short.

[0046] This disclosure describes various systems and methods for simulating golf games. Figures 1 to 11 Aspects of the simulation modeling systems and methods described herein are shown. Refer to Figure 10 , the simulation modeling system 10 can be configured to simulate aspects of a golf game and the levels of those aspects and generate a predictive model output derived from the simulation. For example, the system 10 can be configured to simulate playing a golf hole, a portion of a golf hole, a golf round, a golf tournament, or a combination thereof. The simulation can correspond to a single round, multiple rounds of a tournament, an entire tournament, multiple tournaments in a season, an entire season, or other desired games. In one embodiment, the system 10 can be configured to simulate a golf game and generate predictions for such simulation to evaluate the effectiveness, eligibility, and points system across multiple tournament events or the tournament season, thereby assessing player risk, optimizing the season pace and the number of designated events, and creating new competitive systems.

[0047] The simulation modeling system 10 may include a hole event probability generator 20 configured to generate one or more hole event probabilities for holes being simulated. The system 10 may include or access a statistical database 12 that includes historical player data 14, collective historical data 16, or both, which the hole event probability generator 20 may use to generate hole event probabilities. The system 10 may include or access a hole event result generator 30 configured to generate hole event results using the hole event probabilities as weights. In the illustrated embodiment, the hole event result generator 30 includes or accesses a weighted result generator 32 configured to generate the results of hole events using the hole event probabilities as weights. The system 10 may include or access a hole score generator 40 configured to generate hole scores for each hole using the event results. The hole score generator 40 may include or access a score distribution engine 42 configured to generate or provide a hole score probability distribution of combinations of hole event results. The hole score generator 40 may include or access a random score generator 44 configured to generate random scores based on the hole score probability distribution identified by the hole score generator 40. The system 10 may include a prediction engine 60 configured to output predictions. The prediction engine 60 may include a prediction result generator 62 configured to generate prediction results and / or a prediction result probability generator 64 configured to generate the probabilities of the prediction results. In one example, the probability of a prediction result is at least partially based on predictions of prediction results in multiple simulations of a golf tournament. In some embodiments, the system 10 includes or accesses a modification engine 50. The modification engine may include a score adjuster 52 and / or a cut line executor 54. The score adjuster 52 may be configured to adjust a player's score, such as a hole score. As described in more detail below, in some embodiments, the score adjuster is configured to adjust the score relative to the simulated round based on the player's relevant historical round play. The cut line executor 54 may be configured to execute a cut line protocol and apply the cut line to the second-round score when the first-round score is insufficient to predict or actually advance in the simulation. In one embodiment, the system 10 includes an update processor 70 configured to update the prediction results and / or the prediction result probabilities based on actual score data after the actual start of the tournament. The prediction results may include predicted round or tournament scores, finishing positions, advancement, cut lines, etc. The prediction result probabilities may include the probabilities of prediction results based on analysis of multiple simulations.

[0048] In some implementations, the evaluations, predictions, and probabilities (which may be collectively referred to herein as predictions or prediction model outputs or simply prediction outputs) may be based on historical player data 14, collective historical data 16 (such as course statistics, player statistics), and PGA TOUR Data (if applicable). The prediction model output can include one or more hole event results, hole scores, hole rankings, round scores, tournament scores, round completion position probabilities, tournament completion position probabilities, etc. for a single player or multiple players. In some embodiments, system 10 can be configured to generate a prediction output selected from one or more of a player's predicted round score, tournament score, round ranking, or tournament completion position. In one configuration, the prediction model output corresponds to a player completing at a specified completion position or within a range of completion positions. For example, the prediction result probability generator 64 can be configured to generate a prediction model output based on historical player data 14, collective historical data 16 (e.g., course statistics, player statistics), and PGA TOUR data (if applicable), including one or more of the probability of a player winning or the probability of a top-10 finish in a golf tournament. Additionally or alternatively, the cut line executor 54 can be configured to enforce a cut line, and the prediction result generator 62 can be configured to generate a prediction output that predicts the cut line value / score required to make the cut and / or the players who will make the cut. The prediction output can be available before and / or during the corresponding tournament. For example, the simulation modeling system 10 can be configured to estimate the probability of each player winning before a golf event is conducted. Thus, predictions can be generated for use before a round, tournament, or season begins. In some configurations, system 10 can additionally or alternatively be configured to, for example by updating the processor 70, use a hybrid simulation model to continuously, periodically, or on request generate in-round or updated predictions during a live tournament, the hybrid simulation model replacing the holes that have already occurred with actual hole event results or scores and the holes that have not yet occurred with simulation model results.

[0049] The generated simulation can use historical tournament statistics to simulate each player on the course playing each hole in each round (usually four rounds) of a tournament, the historical tournament statistics which can be stored in the statistical database 12 and can include historical player data specific to the actual players generating the simulation, collective historical data 16 of a group of players similar (e.g., competing at the same or similar levels) to the player situation generating the simulation, or a combination thereof. For example, the historical statistics can be taken from the statistical data archives of the player-specific PGA TOUR and the collective statistics of the participants in previous tournaments. The historical statistics applied to the simulated holes (e.g., regarding the hole events of that hole) can be specific to that hole, corresponding to holes with similar attributes (par value, dogleg, elevation, etc.), or can be applied generally without regard to the hole or hole attributes.

[0050] In various embodiments, system 10 may perform a single simulation of one hole, one round, multiple rounds, or a tournament for a single player, multiple players, or all players. In one example, the prediction result generator 62 generates prediction results regarding one or more holes, one round, multiple rounds, or a tournament, such as predicted scores for one or more holes, a score for a particular round or multiple rounds, or a tournament. Additional examples of prediction results include, but are not limited to: predicted cut line values, cut line predictions for players, predicted finish positions or finish position ranges for one or more players, or combinations thereof.

[0051] In some embodiments, system 10 may be configured to run multiple simulations, such as hundreds or thousands of times. In one example, the prediction result probability generator 64 is configured to generate probabilities of prediction results regarding one or more holes (e.g., the probability of making a birdie on a particular hole or set of holes, the probability of shooting under par on a particular number of holes, etc.), one round (e.g., the probability of shooting over par, the probability of shooting 3 under par in the second round, etc.), multiple rounds (e.g., the probability of being in the top 5 in the first two rounds), or a tournament (e.g., the probability of ultimately finishing in the top 5, the probability of shooting 10 or fewer under par). Additional examples of prediction result probabilities include, but are not limited to: probabilities of cut line values or value ranges, probabilities of players making the cut, finish position probabilities, or probabilities of players finishing within a finish position range, or combinations thereof. According to one method, system 10 may be configured to establish a winning probability prediction (which may also be referred to herein as a prediction result probability including a predicted finish position probability) for one or more players (e.g., each player on a tournament course) based on the number of times a player wins first place in individual simulations of the event divided by the total number of simulations run. In one embodiment, system 10 may also be configured to update the winning probability or other prediction result probabilities during an actual event by updating the processor 70 as true scores are posted by running simulations of the remaining holes and combining the simulated scores with the actual scores of the holes played.

[0052] As described above and described in more detail below, system 10 can be configured to generate a simulation of output cut line predictions via prediction engine 60. Additionally or alternatively, system 10 can implement a cut via cut line actuator 54 in the simulation. For example, in a tournament simulation, a cut line can be adopted based on a first round simulation, and if the first round simulation results in a player not advancing according to tournament rules, such as the player ranking in the top x after y holes, the player being within z strokes of the leader after y holes, or both, then the player is removed from the second round simulation of the first tournament simulation. In one example, the cut line can be implemented by cut line actuator 54 after the first 36 holes (e.g., two rounds). However, since multiple tournament simulations can be performed for a particular tournament, a second tournament simulation may result in the player advancing, and thus, the player's play will be simulated in such tournament simulations where the player is simulated as advancing. In some embodiments, all rounds can be simulated for all players. If a player does not advance in the simulation based on the first round results, cut line actuator 54 performs the cut and update processor 70 excludes the second round simulation results. However, if the actual play changes the actual or predicted cut line such that a player advances or is predicted to advance, update processor 70 can be configured to introduce the player's second round simulation results and the impact on the predictions of other players. Thus, system 10 can dynamically update the predictions of the field based on the actual play. In the various embodiments described herein, if a player is predicted not to enter the applicable tournament elimination round, the predicted tournament score can include only the predicted round scores of the first round. It can be understood that such predicted tournament scores can be marked or otherwise labeled or organized to correspond only to the first round. For example, the predicted tournament scores of players predicted not to advance can be marked as not advancing, or classified or listed together with the predicted scores of players predicted not to advance.

[0053] Figure 1 FIG. 100 shows a simulation method 100 according to various embodiments, which system 10 can be configured to execute to generate one or more of the following: predicted hole scores, including unadjusted predicted hole scores 112 (via the operations of hole event probability generator 20, hole event result generator 30, and hole score generator); predicted hole scores, including adjusted predicted hole scores 116 (via the operation of score adjuster 52); or predicted (adjusted or unadjusted) predicted round scores 120 (via the operation of prediction result generator 62). In various embodiments, method 100 can further include: simulating multiple rounds in a simulated golf tournament to generate predicted (adjusted or unadjusted) tournament scores 128. In some embodiments, multiple predicted round scores can be used to implement a cut line relative to a player or identify a cut line relative to a course (e.g., see Figure 2 and Figure 3)。As described in more detail below, for example with reference to Figure 4 , in another embodiment, method 100 or the output generated thereby may further be used in a method of generating a predicted round or tournament finish position (by operation of prediction result generator 62). Also as described in more detail below, for example with reference to Figure 5 , in another embodiment, these methods or the output generated thereby may further be used in a method of generating a performance completion probability (by operation of prediction result probability generator 64).

[0054] Continuing to refer to Figure 1 and Figure 10 , the hole event probability generator 20 may be configured to calculate an event probability (102) of one or more hole events for a hole. A hole event may include an event related to the hole that may be performed by a player during play on the hole. Exemplary hole events may include, but are not limited to: a tee shot hole event, one or more consecutive stroke hole events, or a combination thereof.

[0055] System 10 can provide a flexible platform on which simulations can be generated using a player's actual historical performance data. For example, the system can be configured to generate hole event probabilities based on actual historical data, which may be referred to herein as historical occurrence data and may include player historical data 14, collective historical data 16, or both. Historical player data 14 includes statistics specific to the player being simulated. In one example, historical player data 14 includes statistics corresponding to the historical occurrences of hole events. Collective historical data 16 includes collective statistics of multiple players, e.g., one or more season averages of all competitors in similar situations (such as competitors competing in the same or similar level of tournaments). For example, the collective historical data 16 used in PGA TOUR simulations can be data obtained from PGA TOUR statistics of the entire field of competitors, such as PGA TOUR averages. In one example, collective historical data 16 includes statistics corresponding to the collective historical occurrences of hole events, typically involving multiple holes or a particular hole for which the hole event is being simulated. For example, for a green-in-regulation hole event on the fourth hole at a PGA TOUR tournament held at the Copperhead Course, the collective historical occurrence statistics can be the PGA TOUR green-in-regulation (GIR) rate for all par-3 holes during one or more PGA TOUR seasons or portions thereof during tournaments, and the average PGA TOUR GIR rate for the fourth hole at the Copperhead Course during one or more PGA TOUR seasons or portions thereof during tournaments. As another example, players from multiple tours can participate in some tournaments, such as the U.S. Open. Collective historical data (e.g., occurrences, statistics) can be taken from one, all, or any combination of tours. In another example, the statistics used can be taken from tournaments in one or more tours in which the particular player being simulated has participated.

[0056] Historical player data 14 may include the statistical percentage or relative incidence of a player performing hole events during a game. In one configuration, such historical game statistics may be specific to hole attributes corresponding to the hole of the hole event being simulated. For example, statistics for holes with similar hole attributes (e.g., par values) may be used to generate one or more hole event probabilities relative to the hole being simulated. In one example, statistics corresponding to the historical occurrence of hole events for par-3 holes may be used to calculate the probability of a corresponding hole event occurring in a simulation for a par-3 hole. In another example, historical player data 14 includes statistics corresponding to the historical occurrence of hole events for par-4 holes, which may be used relative to one or more hole events for par-4 holes, and statistics corresponding to the hole events for par-5 holes may be used relative to one or more hole events for par-5 holes. In one configuration, historical player data 14 includes statistics corresponding to the historical occurrence of hole events for par-3 holes, which may be used relative to one or more hole simulations for par-3 holes, and statistics corresponding to the historical occurrence of hole events for par-4 and par-5 holes may be used for simulations of one or more hole events for par-4 and par-5 holes. As described in more detail below, in some embodiments, multiple hole event outcomes may be generated for all or some of the holes in a round. In some such configurations, statistics corresponding to the historical occurrence of some hole events for one or more simulated holes may correspond to the attributes of the simulated holes, such as par values, while the statistics for one or more other hole events for one or more simulated holes may correspond to different hole attributes or may be hole-attribute neutral. Thus, a hole may have multiple hole events, where the statistics used to calculate the probability of a first hole event may be statistics collected from games of actual holes with a first hole attribute similar to the hole being simulated, the statistics used to calculate the probability of a second hole event for the hole may be statistics collected from games of actual holes with a second hole attribute (different from the first hole attribute) similar to the hole being simulated, or may be collected from games of all holes regardless of the attribute. Although historical player data 14, which includes statistics corresponding to the occurrence of hole events simulated relative to a player, is generally described herein as corresponding to a player's play on multiple holes rather than on a specific hole being simulated, in some embodiments, historical player data 14 that includes statistics for a player's play on the hole being simulated may additionally or alternatively be used to generate the hole event probability for that hole. In one embodiment, historical player data 14 that includes statistics may be obtained over all available sessions, rounds, or seasons. Additionally or alternatively, the statistics may be obtained over a pre-determined session, round, season, or part of a season, where the part of the season may include the current season or only previous seasons.

[0057] The collective historical data 16 can be obtained from the play of a specific hole, a general hole, or a hole having similar attributes to the simulated hole. The collective historical data 16 can include collective statistics corresponding to the historical performance of hole events of multiple players, such as the percentage or relative incidence of hole events from players competing at a similar level to the simulated player, and in the case of simulating a professional tournament, can include the competition situation of professional championships. The completion of professional championships can also be classified by level, such as class tournaments, tours, leagues, etc. In some embodiments, collective statistics related to the occurrence of hole events can be selected as the statistics representing the simulated competition level.

[0058] In one configuration, the collective historical data 16 used to calculate the hole event probability can be taken from the historical statistics of actual play on holes having hole attributes similar to the simulated hole. For example, the historical occurrence of hole events on a par-3 hole can be used for the simulation of a par-3 hole, the historical occurrence of hole events on a par-4 hole can be used for the simulation of a par-4 hole, or the historical occurrence of hole events on a par-5 hole can be used for the simulation of a par-5 hole. In one configuration, the historical occurrence of hole events on a par-3 hole can be used for the simulation of a par-3 hole, and the combined historical occurrence of hole events on par-4 and par-5 holes can be used for the simulation of par-4 and par-5 holes. As described in more detail below, in some embodiments, multiple hole event results can be generated for all or part of the holes in a round. In some such configurations, the historical occurrence of some hole events for one or more holes can correspond to the hole attributes, such as the par value, while one or more hole events for one or more holes can correspond to different hole attributes, or can represent the normal collective historical occurrence of events relative to the player's play on all holes.

[0059] In addition to or as an alternative to using the collective historical data 16 including statistics corresponding to the occurrence of hole events in the play on multiple courses to determine the hole event probability, the hole event probability generator 20 can use the statistics corresponding to the collective historical occurrence of hole events in the collective play on the actual hole being simulated. For example, the hole event probability can be generated at least in part based on the actual collective historical occurrence of hole events on the hole. In various embodiments, the hole event probability can be based on historical player statistics regarding the occurrence of hole events and collective historical statistics regarding the occurrence of hole events (common to and specific to the simulated hole).

[0060] In some embodiments, collective historical data 16 about multiple courses, collective historical data 16 about holes, historical player data 14 about the simulated players, or combinations thereof can be obtained within available time periods, rounds, or seasons. Additionally or alternatively, statistical data can be obtained within predetermined time periods, rounds, seasons, or partial seasons, where the partial seasons can include the current season or only previous seasons. In various embodiments, collective historical data and player historical data can be obtained relative to different time periods or seasons, etc. For example, collective historical data (such as collective statistics of a course) can be based on an average over three to five years, which can depend on availability and relevance due to changes such as course changes. Historical player data (such as player statistics) can be based on a shorter time period, such as a rolling average over one to three years. In another example, for more frequent tournaments related to the current tournament, the rolling average is weighted. In some examples, the hole event probability generator 20 is configured to employ recency weighting, i.e., giving greater weight to more recent data points compared to older data points. The weighting can be progressive. For example, available statistical data over a period of time (such as multiple seasons, say five seasons) can be used, where the data points corresponding to the most recent season in which a hole event occurred are weighted so that more recent seasons have a greater impact on the statistics. In some embodiments, the same weight can be applied to multiple seasons or groups of seasons, while other seasons are given different weights or no weight. In another example, the data points from each season are progressively weighted to apply the greatest weight to the data points from the most recent season. Although seasons are used above and elsewhere in this document to describe example weighting schemes, it should be understood that multiple weighting schemes can be applied additionally or alternatively. For example, since the level of play can vary depending on the competitors in a particular tournament, the tournament can be divided into groups that are closer to the expected level of play. For example, the hole event probability generator 20 can give greater weight to data points collected from major tournaments (e.g., the Masters, the U.S. Open, the Open Championship, the PGA Championship) when simulating major tournaments, or give greater weight to data points collected from one or more tiers of non-major tournaments when simulating non-major tournaments of a similar level. As described above, statistical data related to the historical occurrence of hole events can be selected as the statistical data corresponding to the simulated level of play. For example, statistics corresponding to a particular tour can be used to simulate the tournaments of that tour. However, in some embodiments, statistics corresponding to multiple tours can be used, for example, when the level of play corresponds.

[0061] As described above, a variety of hole events can be used. For example, hole events can include tee-off hole events, subsequent shot hole events (e.g., second shot hole events or third shot hole events, or both). In various embodiments, the tee-off hole event, the subsequent shot hole event, or both can include a shot location attribute. For example, the tee-off or subsequent shot location can include results such as fairway, off the fairway, green, rough, hazard / bunker, reserved area, out of bounds, or other areas of the hole. Historical occurrence data for generating the probability of a particular hole event result can include the historical occurrence of the hole event corresponding to the tee-off, or the historical occurrence of the subsequent shot hole event related to a player or group of players.

[0062] In some embodiments where a hole includes multiple hole events, the historical occurrence data used by the generation result specifying system for a hole event in step 104 to calculate the probability of a second hole event. For example, the first hole event for a par 4 hole can be hitting the fairway (example results are hitting the fairway, missing the fairway), and the second hole event can be hitting the green (example results are hitting the green, missing the green). The hole event probability generator 20 can utilize the historical occurrence data regarding hitting the fairway on the tee-off to calculate the probability of hitting the fairway to generate a result of hitting the fairway or missing the fairway for the first hole event. If the result of the first hole event is hitting the fairway, the hole event probability generator 20 can use the historical occurrence data to calculate the probability of getting on the green from the fairway relative to the second hole event. If the result of the first hole event is missing the fairway, the hole event probability generator 20 can use the historical occurrence data regarding the green-in-regulation rate from off the fairway to calculate the probability of getting on the green from an off-the-fairway location.

[0063] According to various embodiments, a hole event can include the number of putts or score when another hole event occurs (e.g., reaching the green, chipping onto the green from the fairway, rough, bunker, natural area, or other location). In one example, a hole event after a missed green result from a previous hole event includes a scramble or a sidehill scramble and utilizes historical scramble occurrence data. In a further or another example, the previous hole event result includes a location, and the historical scramble occurrence data is based on scrambles from the result location. In some embodiments, the generated location result can include a bunker, and a subsequent hole event can include a bunker shot or not include a bunker shot, and the historical occurrence data used to generate the result utilizes historical bunker shot occurrence data. Additionally or alternatively, a tee shot or subsequent shot location hole event can include a distance result, such as within a predefined distance from the hole on the green, e.g., within 5', 10', between 10'-15', greater than 20' relative to a putt hole event, scramble hole event, or bunker shot hole event. In one example, a tee shot hole event can include a tee shot distance, e.g., a percentage of the hole yardage covered by the tee shot. In a further example, the historical occurrence data used is specific to the par attribute of the hole, e.g., the percentage of the hole yardage covered by a tee shot on a par 4 hole or the percentage of the hole yardage covered on a par 5 hole. As another example, a first hole event can include a bunker location, and a second hole event can correspond to getting onto the green from the bunker or a bunker shot. As described above, potential results can include a distance or distance component related to a location, e.g., greater than 30 yards, 20-30 yards, 10-20 yards, less than 10 yards. In such cases, the historical occurrence data used can correspond to statistical data related to generating the result. In one embodiment, the hole event probability generator 20 is configured to apply the player's historical occurrence statistics for hole events, the collective historical occurrence statistics for the hole, and the historical occurrence statistics for regular holes (which can include holes with similar attributes) to the hole events described herein.

[0064] Various probability models can be utilized to calculate one or more hole event probabilities (102) for a hole (e.g., by the hole event probability generator 20). In one configuration, the hole event probability generator 20 can calculate the hole event probability according to an example of step 102 that employs an adaptation of the log5 formula from the 1983 Bill James Baseball Abstract, which has received the endorsement of Dallas Adams and can be referred to as the log5(M) event probability model:

[0065]

[0066] After modification, the formula is reused to estimate the probability of a specific event occurring at each hole on each course at a specific time. This algorithm is used to create a weighted probability for each hole event.

[0067] According to one embodiment, historical player data and collective historical data of multiple players are used, where x = historical incidence rate of a player's hole events, y = collective historical incidence rate of hole events on a specific hole, and z = collective historical performance of hole events during play on multiple golf courses, which may include holes having attributes similar to the hole being played, as described above and elsewhere herein. Also as described above and elsewhere herein, the collective historical data, player historical data, or both may accumulate data points over an available period, a predetermined period, or both. When data is unavailable, missing, or incomplete, some embodiments may employ alternative methods. For example, if data for a particular player is insufficient, a generalized probability may be applied, such as obtaining a generalized probability from players whose scores most closely resemble that player based on available statistics. Some embodiments may place more weight on recent statistics.

[0068] As described above, the hole event result generator 30 may utilize the output probabilities as weights to generate a predicted hole result (104) for each hole event. The result generation function may be performed by a variety of methods. In one example, the hole event result generator 30 utilizes a weighted random result generator 32 to perform the result generation function, and the weighted random result generator 32 uses the generated hole event probabilities as weights. In some embodiments, method 100 may further include: assigning one or more hole events to each hole, calculating corresponding hole event probabilities for each hole, and generating corresponding hole event results.

[0069] Some holes or all holes may include multiple hole events, and the probabilities of these hole events are calculated and corresponding results are generated. Thus, some simulated holes on a golf course may be associated with fewer or more hole events compared to one or more other holes on the golf course. In various embodiments, the potential outcomes of a hole event may be binary, ternary, quaternary, quinary, or consistent with the number of events simulated for the hole. For example, for binary potential outcomes of a hole event, the hole event probability applies to two potential outcomes, such as hitting the fairway and missing the fairway. The potential outcomes may be abbreviated, for example, "1" for a positive outcome (hitting the fairway, hitting the green), or "0" for a negative outcome (missing the fairway, missing the green). Thus, using the binary example, the hole result including one hole event may be represented as (1) or (0). The hole result including two hole events may be represented as (1, 1), (0, 1), (1, 0), or (0, 0). As described above, in some embodiments, a second hole event on a hole requires determination of the result of a first hole event, for example, specifying historical occurrence data or hole event results applicable to the second hole event.

[0070] The hole score generator 40 can be configured to assign a score probability distribution (106) corresponding to the predicted hole result for the hole using the generated hole results (e.g., (1, 0, 2), (0), (1, 1), etc.). In various embodiments, the hole event result generator 30 identifies a score probability distribution from a plurality of predefined score probability distributions, each score probability distribution assigned to a predicted hole result regarding one or more hole events. A score probability distribution for each combination of hole results can be obtained or generated, e.g., by the score distribution engine 42 for each hole. The score probability distributions are typically generated prior to the tournament and apply equally to each player. In one example, the score probability distribution can be represented as a historical score distribution for the hole corresponding to a combination of hole event results generated by the hole. In one embodiment, when there is a combination of hole event results, the score probability distribution corresponds to the historical score distribution. For example, the score probability distribution can be specific to a hole using historical collective scores regarding a combination of hole events, specific to historical collective data regarding a combination of hole events for a regular hole or a par-like hole (e.g., a par-3 hole, a par-4 / par-5 hole), specific to a player's historical scores regarding a combination of hole events for a regular hole or a par-like hole (e.g., a par-3 hole, a par-4 / par-5 hole), or a combination thereof. As described above regarding historical occurrence data, in some embodiments, the score distribution engine 42 can select the historical distribution to cover a predefined time period or a predefined number of seasons. In a further or another example, the score distribution engine 42 can apply recency weighting to give greater weight to more recent data points compared to older data points. However, in other examples, the score probability distribution can be based on the score distribution of holes with similar attributes, such as par type, specific to one or a group of players, or a combination thereof.

[0071] Using the score probability distribution assigned to the hole based on a combination of simulated hole results, the hole score generator 40 can be configured to generate a predicted hole score (108) for the hole. Various methods can be used to utilize the assigned score probability distribution to generate the predicted hole score. For example, the hole score generator 40 can be configured to select a random score based on the assigned historical probability distribution, which is related to the score of the same historical result recorded on that specific hole based on the generated predicted hole event results or a combination of predicted hole event results. In one example, the hole score generator 40 is configured to use a random score generator 44 combined with the assigned score probability distribution to generate the predicted hole score for hole 108. The random score generator 44 can apply the specific score probabilities in the assigned distribution when randomly generating the hole score. For example, the assigned hole distribution can specify:

[0072] Triple bogey = 0.02

[0073] Double bogey = 0.03

[0074] Bogey = 0.15

[0075] Par = 0.60

[0076] Birdie = 0.20

[0077] Eagle = 0.02

[0078] The random score generator 44 can randomly select a score from the above distribution, for example, where the availability of the random selection of each score option is defined by the relative distribution.

[0079] The hole score generator 40 can output the predicted hole score (unadjusted) 112. Additionally or alternatively, the system 10 can repeatedly generate the predicted hole score for each hole to generate the predicted hole score (unadjusted) 112 (110) for each hole. The prediction engine 60 can also be configured to sum the predicted hole scores within a round (118) to calculate the predicted round score 120. In some embodiments, the method can output the predicted round score 120 of the player. However, in another embodiment, the system 10 can be configured to also perform simulations (122, 124) for additional rounds of the tournament and generate a predicted tournament score 128. For example, for a multi-round golf tournament, the system 10 can be configured to repeatedly generate the predicted hole scores for all rounds in the simulated golf tournament, the prediction engine 60 can sum (122, 124), and output the predicted tournament score 128 of the player.

[0080] In a further or alternative embodiment, the modification engine 50 may be configured to apply a score adjuster 52 to the predicted score to generate an adjusted score. One or more score adjustments (such as score differential adjustments) may be applied to the predicted hole score (114) to generate an adjusted predicted score 116. A variety of adjustments may be employed. For example, player-specific adjustments may include using a player's historical score data to adjust the predicted score for a particular hole or round. In various embodiments, the score adjuster 52 may be configured to adjust a player's score based on contextual differences in the player's average score. Context may include one or more of the following: time (e.g., better or worse recent performance), season (fall, winter, spring, summer), geography (course terrain or style type, course elevation, course geographic location or region), environment (e.g., specific weather conditions such as hot, cold, humid or rainy), tournament schedule (e.g., a particular tournament, major tournament, early-season tournament, end-of-season tournament, tournament after not advancing, or tournament after a week off), or round schedule (e.g., a particular tournament round). For example, there may be a difference between a player's average score and the average score of other players relative to a particular course, round, weather condition, elevation, time of year, or combination thereof. As another example, there may be a difference between a player's average score and the score the player achieves when competing in a particular context (e.g., any of the contexts above). In some embodiments, different contextual difference adjustments may be applied to different players depending on whether there is a statistically significant difference in the players' average scores in the context relevant to the simulated game. For example, if simulating a round at a desert course early in the tournament season, a differential adjustment may be applied to players who have a score differential in one or two such contexts. In one example, the system may track contextual differences in player scores and mitigate one or more differences associated with the simulation through score differential adjustments. In some embodiments, one or more contexts used for score differential adjustments are the same for all competing players. In one configuration, the context may relate to a particular tournament round being simulated, and the differential adjustment may include a round-specific component that captures the difference in a player's performance in the particular round being simulated (e.g., the second round) relative to the player's broader average score performance. For example, for the currently simulated round, the hole score or round score may be adjusted by a player-specific differential adjustment factor based on the player's historical score average difference (e.g., the player's relevant season average score). For example, the difference between the broader score average of the player's current season or other period (e.g., a rolling average over a period of time or several seasons) and the rolling average of a particular round therein may be applied. For example, the differential adjustment may be applied to the round score or may be divided by 18 and applied as an adjustment factor to each hole score in the round. In one example, a rolling average from the previous few weeks or months may be used.In any of the above examples, the average score can be weighted such that more recent performance is given a greater weight than older scores. For example, a rolling average taken over the past 52 weeks (if available) can be used to generate a differential adjustment factor and can be weighted for more recent performance. In some embodiments, if a player does not have available scores over the entire rolling period, scores available over a shorter period can be used. In one embodiment, a rolling average of a previous number of available tournament scores can be used, which can include weights.

[0081] In one method, differential adjustment is performed by adding or subtracting (as appropriate) the player's relative score average difference for the simulated round. For example, a player's average score across all rounds of a tournament is 72 (total tournament score divided by number of tournament rounds), and the average score in the third round of the tournament might be 71. Thus, for the simulation of the third round, the predicted round score can be subtracted by -1 (i.e., the player's average score difference for that round) to generate an adjusted predicted round score. Similarly, to adjust the predicted hole score instead of the predicted round score, system 10 can divide the average score difference for the round by the number of holes in the round (e.g., 18) to obtain a differential adjustment factor for the player's average hole score difference in that round, which is approximately -0.06 in this example. Thus, -0.06 can be subtracted from each unadjusted predicted hole score to generate an adjusted predicted hole score. This per-hole score adjustment can be used such that when the actual scores for the holes are substituted for their respective simulated hole scores, the differential adjustment factor for the remaining holes to be played in the round remains unchanged.

[0082] In some embodiments, additional or alternative adjustments for the player can be utilized. For example, the differential adjustment for a player can include an adjustment for the player relative to the course in the simulated round or tournament or in other rounds or tournaments. For example, after establishing the predicted score for each hole of the round for a single player, the score can be adjusted by the player's average relative score vs. course in the current season or other predefined period or season. In a further example, the hole score or round score can be adjusted based on the historical score vs. course in the corresponding round. In the above or another example, the player's hole score or round score can be adjusted based on the player's average round score adjustment vs. course relative to the season and the historical score adjustment by course and round. In some embodiments, the score adjuster 52 can apply differential adjustment based on the player's average score for hole attributes. For example, the predicted hole score for a par-3 hole can be adjusted by the player's relative score average difference for par-3 holes in the simulated round, and the predicted hole scores for par-4 and par-5 holes can be adjusted by the player's relative score average differences for par-4 and par-5 holes respectively in the simulated round.

[0083] After applying the adjustment (which is optional in some embodiments), the score adjuster 52 can be configured to output the adjusted predicted score 116. Additionally or alternatively, the system 10 can repeatedly generate the adjusted predicted hole score for each hole. The prediction result generator 62 can also be configured to add the adjusted predicted hole scores of the round (118) to calculate the predicted round score 120 (or the adjusted predicted round score), including the adjusted sum of the hole scores. In some embodiments, the method 100 can end with outputting the player's predicted round score 120, which includes the adjusted or unadjusted predicted round score. However, in another embodiment, the system 10 can be configured to also perform simulations (122, 124) for all rounds of the tournament to calculate a predicted tournament score 128, which includes the adjusted and / or unadjusted predicted round score. For example, for a multi-round golf tournament, the system 10 may be configured to repeatedly generate predicted hole scores (122, 124) for all rounds in the simulated golf tournament, sum the round scores, and output an adjusted predicted tournament score 128. Although the illustrated method 100 describes applying a variance adjustment to unadjusted predicted hole scores, in some embodiments, a variance adjustment may be applied to unadjusted predicted round scores, unadjusted predicted tournament scores, or both in addition to or instead of being applied to unadjusted predicted hole scores.

[0084] In some embodiments, the system 10 may include a cutting line executor 54 configured to apply a cutting line (124) by applying a cutting line protocol. Cutting lines are typically applied after one or more rounds of a tournament. If a player fails to advance based on a preliminary round score, the player will not be able to participate in the rematch round and will not receive a score for the rematch round. Various cutting line protocols may be used. For example, the system may be pre-programmed with cutting lines, or may be configured to identify predicted cutting lines, such as previous cutting lines based on previous tournaments on a course or similar courses. In one configuration, the cutting line may be based on previous cutting lines for courses of similar difficulty, which are determined based on previous collective scores. In any of the above examples, the cutting line protocol may further take into account the player's performance on the same or similar courses. As described below with reference to Figure 2 and Figure 3 Describing in more detail, the system 10 may be configured to generate a predicted advancement line by simulating a tournament in which each player or each player realistically competes for advancement.

[0085] It should be understood that the simulation method can be executed multiple times, for example, thousands of times, and the output scores can be added and divided by the number of simulation trials to obtain an extended average prediction (adjusted or unadjusted) score. In some embodiments, the system can be configured to average for each simulated hole, each simulated round, each simulated tournament, or any combination thereof.

[0086] Figure 2 An example of a cut line protocol 200 according to various embodiments is shown. According to this protocol, the system 10 is configured to perform Figure 1 the simulation method to generate predicted (adjusted or unadjusted) round scores (202) for each round of the preliminary round of the simulated tournament for each player participating in the tournament. The system 10 can add up the predicted (adjusted or unadjusted) round scores of the preliminary round (204). The cut line executor 54 can set a cut line according to the tournament rules (206) and apply this cut line to identify the predicted advancing players. After identifying the predicted advancing players, the cut line executor 54 can perform Figure 1 a quarterfinal round simulation on the advancing players (208) to obtain predicted (adjusted or unadjusted) scores for one or more players.

[0087] Figure 3 An example of a cut line protocol 300 is shown. The cut line protocol 300 is similar to the cut line protocol 200, except that the cut line executor 54 performs simulations for both the preliminary round and the quarterfinal round to generate predicted (adjusted or unadjusted) round scores (302) for each round of the simulated tournament for each participating player. The system 10 can add up the predicted (adjusted or unadjusted) round scores of the preliminary round (304). The cut line executor 54 can set a cut line according to the tournament rules (306) and apply this cut line to identify the predicted advancing players so as to include the predicted (adjusted or unadjusted) round scores of the quarterfinal round in the predicted (adjusted or unadjusted) tournament scores of the advancing players (308). According to this protocol 300, the system 10 retains the predicted (adjusted or unadjusted) round scores of the quarterfinal round of the non-advancing players for use in the prediction update protocol (310) if necessary. Since the cut line can move dynamically according to the updated predicted scores of the participating players during the actual competition, the cut line protocol 300 can be used to reduce the update calculations based on, for example, the actual data during the on-site tournament. If the cut line protocol 200 is implemented, the system 10 can perform additional round simulations for the players predicted to advance subsequently based on the actual scores.

[0088] Figure 4 An example method 400 for generating a predicted round completion, a predicted tournament completion, or both according to one embodiment is shown. Method 400 includes performing Figure 1A related part of the simulation method to generate predicted (adjusted or unadjusted) scores for contestants. The prediction result generator 62 can rank the contestants by the predicted (adjusted or unadjusted) scores (404) to output the predicted round completion, predicted tournament completion, or both for one or more contestants.

[0089] As described above and elsewhere in this document, the method 100 and other similar methods described herein (which may include method 200, method 300, or method 400 in some examples) or the prediction result generator 62 can be used to generate prediction results regarding round or tournament simulations, such as predicted cut lines, advancement or non-advancement, predicted scores for one or more holes, rounds, or tournaments, or predicted round or tournament completion positions. In additional or alternative embodiments, the prediction result probability generator 64 can be configured to generate prediction result probabilities relative to the prediction results, which can include cut lines or completion positions, such as win probabilities, top 10, etc.

[0090] Figure 5 An example method 500 for generating completion position probabilities by performing multiple simulation trials is shown. Method 500 includes: performing Figure 4 the simulation method n times to obtain n predicted round / tournament completions for the contestants participating in the tournament (502). The prediction result probability generator 64 can identify the simulations where there is a specified completion position (504). For example, the performance completion can be winning or being in the top x, such as top 5, top 10, top 15, top 20, etc. The prediction result probability generator 64 can divide the number of simulations with the specified completion position by n (506) to output the performance probability completion relative to the specified completion position. For example, if the specified completion position is winning and it is predicted that contestant 1 wins the tournament 370 times out of 3000 simulation trials, a win probability of approximately 12.3% can be output. As another example, if the specified completion position is top 10 and it is predicted that contestant 1 makes it into the top 10 2200 times out of 3000 simulation trials, the probability of contestant 1 making it into the top 10 can be output as approximately 73.3%.

[0091] Figure 6 An example method 600 for generating result probabilities by performing multiple simulation trials is shown. Method 600 includes: performing Figure 1The simulation method is run n times to obtain n prediction results (602) for one or more contestants. For example, if the result is the score of a contestant on a particular hole, round, or tournament, system 10 may only need to run the simulation multiple times for one contestant rather than all contestants. However, system 10 can also run the simulation multiple times for multiple or all contestants, for example, to generate predicted finishing positions, cut lines, or other prediction results from the simulation. The prediction result probability generator 64 can identify the simulations in which there are prediction results (604). The prediction result probability generator 64 can divide the number of simulations in which there are prediction results by the total number of simulations n in step 606 and output the result probability for the prediction result. For example, if the prediction result is advancement, the system can run 5000 simulations according to method 100 to generate the predicted (adjusted or unadjusted) round scores, and can also include running method 200 or method 300 for the first round of the contestant. If contestant 1 advances in 3779 simulation trials, an advancement probability of approximately 75.56% can be output. As another example, if the prediction result is that the cut line is +3, system 10 can run the simulation as in the above example, and the prediction result probability generator 64 can identify the simulations in which the cut line is +3. If the cut line is +3 in 1500 simulations, a probability of 30% for the cut line of +3 can be output. If the prediction result is that the cut line is below +3 and the cut line is below +3 in 3000 simulations, a probability of 60% for the cut line below +3 can be output. As another example, if the prediction result is that the score of a particular round is under par, the system can run the simulation for that particular round to generate the predicted (adjusted or unadjusted) round score of the contestant and identify the rounds in which the contestant's score is under par. If the contestant scores under par in 2500 out of 5000 simulations, the prediction result probability generator 64 can output a probability of 50% for under par. The prediction results can include the finishing position. For example, as Figure 5 shown, the scores of the contestants in each simulation are sorted to determine the finishing position.

[0092] As described above, the systems and methods described herein can include updating predictions based on actual scores. The predictions can be updated in real-time when the scores are received, or intermittently when real-time scores are received, to provide a hybrid simulation that includes both actual and simulated data. In some embodiments, the real-time updates can occur continuously at predetermined intervals during a live event, continuously after the actual scores are received, or both. In various embodiments, such a hybrid simulation model can be implemented by alternatives, such as replacing simulated scores with actual scores in all simulations among multiple simulation embodiments. For example, as each score occurs, the system can replace the corresponding predicted score with the actual score. Thus, when an actual score is obtained, the system can replace the predicted score with the actual score and update the associated result predictions (e.g., hole score, round or tournament score, cut line value, advancement or non-advancement, finishing position).

[0093] When the method includes generating prediction results or finishing position probabilities based on multiple simulation trials, the system can replace the corresponding predicted scores as described above with actual tournament scores in all simulations and update the prediction probabilities, which can correspond to the finishing position predictions or scores of the contestants, the cut line, or other changes that may occur with each update in the simulation. For example, in cases where the system applies a cut line, the cut line can be moved dynamically based on the updated predicted scores of the contestants. Thus, in the simulation trials, the contestants predicted to advance can change dynamically during the course of the event, and the system can include predicting the scores of the contestants predicted not to advance in the playoff rounds and excluding the scores of the contestants predicted not to advance during the entire tournament. Since the changes in each simulation may change the probabilities generated by multiple simulations, the system can also update the probabilities. For example, the system can update the scores in all simulations, including considering the changes in the cut line for each simulation when in use, and update the associated predicted finishing positions and result probabilities based on the updates to the simulation.

[0094] In one embodiment, the system is configured to generate a probability of winning, a probability of finishing in the top 10, a cut line value, a probability of advancement, or a combination thereof. Once the event starts, the system is configured to update the predictions and probabilities based on actual score data. For example, the pre-event probability estimate of winning can become a combination of actual score data and simulated score data. The model can then be configured to use the same approach as in the pre-event phase but with an alternative method to generate an output to estimate the probability of finishing in the top 10, the cut line value, the probability of advancement, or a combination thereof.

[0095] Figure 7 An example update method 700 using an alternative method is shown. In such an example, system 10( Figure 10) The update processor 70 can be configured to replace the predicted (adjusted or unadjusted) hole score with the actual hole score when the player completes the hole (702), for example, continuously in real time, continuously in real time at a predetermined interval, when an event occurs, or otherwise. The update processor 70 can update the predicted (adjusted or unadjusted) round score considering the replaced actual hole score (704). The update processor 70, the prediction engine 60, or both can be configured to sum the updated predicted (adjusted or unadjusted) round scores in all tournament rounds to generate an updated predicted tournament score for the participating player (706).

[0096] When the system 10 is configured to adopt a cut line, the method 700 can include: summing the updated predicted (adjusted or unadjusted) round scores in the first round to establish an updated cut line during the update operation of the first round (708). The system 10 or its update processor 70 can be configured to count the predicted (adjusted or unadjusted) predicted round scores of the advancing players in the second round (which may or may not be updated) into the first round, and exclude the predicted (adjusted or unadjusted) predicted round scores of the non-advancing players in the second round (710).

[0097] When the method 700 includes generating predictions related to the finishing position or result, the system 10 or its update processor 70 can further update the relevant predicted round / tournament finishing position or predicted result (712). When the method 700 includes generating prediction results or performance probabilities from multiple simulations, the system 10 can be configured to repeat the above steps of the method 700 for each simulation trial and update the relevant prediction result probabilities and performance completion probabilities (714). For example, the update processor 70, the prediction result probability generator 64, or both can be configured to identify simulations with relevant results regarding the prediction result probabilities and update the probabilities as needed. Similarly, the update processor 70 and the prediction result probability generator 64 can identify the finishing positions related to the finishing position probabilities and update the probabilities as needed.

[0098] It should be understood that although the systems described herein can be configured to output predefined predictions, probabilities, or both, these predictions, probabilities, or both can be automatically continuously updated in real time periodically or when one or more events occur (such as receiving actual scores), but in some embodiments, the system 10 can also be configured to make queries to output specific predictions, probabilities, or both derived from simulations, which can include hybrid simulations updated to include actual score data.

[0099] Figure 8It is a schematic diagram of an exemplary alternative update processor 800. In various embodiments, the update processor 70 includes the update processor 800 or its functionality. In one method, the update processor 800 generates a container 804 for each player on the field, which contains only the data of a specific player for each simulated tournament, and these simulated tournaments can be single simulated tournaments or multiple simulated tournaments, such as hundreds or thousands of them. The scores of each simulated hole can be retained in a data file in the container 804 and then used to calculate the scores of each player per round. The processor 802 can obtain the score supply relative to all player containers 804 (some of which contain actual score data 806) and continuously recalculate all probabilities for each player. In some embodiments, all probabilities can include updated advancement probabilities. As described above, this update process can be executed continuously in real time, for example, at certain time intervals, when receiving score data 806, or a combination thereof. The time interval can be set, for example, to approximately every second, 2 seconds, 5 seconds, 10 seconds, 15 seconds, 20 seconds, 25 seconds, 30 seconds, 45 seconds, or per minute. In one embodiment, the update process is executed at a time interval of approximately every 5 - 60 seconds, 5 - 45 seconds, 5 - 30 seconds, 5 - 15 seconds, 5 - 10 seconds, less than every 5 seconds, 10 seconds, 15 seconds, 30 seconds, 45 seconds, or per minute. In one configuration, the update process is completed approximately every 15 seconds. In another configuration, the update process is repeated every 5 - 15 seconds during the game until the tournament ends. In addition, the update process can also be initiated by completing a certain event (such as a hit or a hole-in-one score). The output of the update process 800 can create a data file, which can be loaded into a database (such as a Dynamo database) for use by one or more end-use applications. When a player completes a hole during the actual tournament process, all simulated scores for that hole in a specific round can be replaced by the actual score from the actual score data 806. In some embodiments, the system 10 is configured to move the information of each player to the database using the player ID and timestamp to display the latest probabilities and allow for digital trend display on television broadcasts and digital platforms (such as fan websites or betting platforms).

[0100] As an example illustration of the operation of the update processor 800 according to one embodiment, if player A makes a birdie on the first hole of the first round of a tournament, then in all simulation trials, the score of player A on the first hole of the first round is set to a birdie. In some cases, some of the simulation results may already be a birdie, and these simulation results will not be changed based on the score of player A on the first hole of the first round. However, for simulations where the score of player A on the first hole of the first round is not a birdie, the score of player A on the first hole of the first round is updated to a birdie in all such simulations to match the actual score data 806. Then the score of player A in the container 804 is recalculated to obtain an updated total score and provided to the processor 802. The processor 802 is configured to recalculate all probabilities for each player and update the predicted probabilities. For example, if the predicted probabilities include the probability of winning, the cut line, the probability of making the cut, and the probability of finishing in the top 10, then the processor 802 is configured to recalculate these probabilities and update the predicted probabilities based on the actual score data 806.

[0101] Figure 9 An exemplary simulation method 900 for simulating a golf tournament is shown, which also generates predicted result probabilities updated by actual scores after the start of the game.

[0102] In step 902, the method includes retrieving relevant collective history and historical player data from a statistical database and running the statistical data through a hole event probability algorithm to generate tee shot location hole event probabilities. In one example, the hole event probability generator is configured to extract historical data. The tee shot hole event can correspond to the location where a player hits the ball off the tee. The potential outcomes of this hole event can involve two or more locations. The historical data used to generate the probabilities can include representative occurrences, such as the probability of the ball being hit to a location outside the tee box. Although other data combinations can be utilized, the illustrated example utilizes collective history data and historical player data. For example, if the tournament is a PGA TOUR tournament, the statistical data used can correspond to the tour average of hitting a location outside the tee box for a particular hole and the tour average and player average of hitting a location outside the tee box for a hole with a par rating corresponding to the hole being simulated, so that par-3 holes utilize the statistics on hitting a location outside the tee box for par-3 holes, and par-4 and par-5 holes utilize the statistics on hitting a location outside the tee box for par-4 and par-5 holes. In other examples, par-5 holes can utilize specific statistics for par-5 holes. In the illustrated embodiment, if it is a par-3 hole, the hole event of hitting the green with the tee shot is used; if it is a par-4 or par-5 hole, the hole event of hitting the fairway with the tee shot is used.

[0103] The statistical data used in the model may include: the percentage of fairway hits on par 4 and par 5 holes - player; the percentage of fairway hits on par 4 and par 5 holes - hole; the percentage of green hits from the fairway on par 4 and par 5 holes - player; the percentage of green hits from off the fairway on par 4 and par 5 holes - player; the percentage of green hits from the fairway on par 4 and par 5 holes - hole; the percentage of green hits from off the fairway on par 4 and par 5 holes - hole; the percentage of green hits on par 3 holes; the average score per round of the player; the score distribution of each hole; or a combination thereof.

[0104] As described above, the collective historical data and historical player data can be obtained over various available periods, rounds, or seasons. The statistical data can be obtained over a pre - determined period, round, season, or partial season, and the partial season can include the current season or only previous seasons. In an embodiment, the collective historical data is obtained based on a multi - year average, while the historical player data can be obtained based on a rolling average, which can be less than the collective historical data and can be weighted for recent deviations in one example. For example, the collective historical data can be based on an average of three to five years, which can depend on availability and relevance due to changes such as course changes. The historical player data (such as player statistics) can be based on a shorter period, such as a rolling average of one to three years. In another example, for more frequent tournaments related to the current championship, the rolling average is weighted.

[0105] For par 3 holes, the potential outcomes of the tee - off hole event in the example shown include hitting the green (which can be represented by "1") and missing the green (which can be represented by "0"). The historical data used to generate probabilities can include representative occurrences, such as the percentage of occurrences relative to the player's position (GIR on par 3 holes), the collective average of the hole (tour average of GIR of the hole), and the collective average of par 3 holes (tour average of GIR of par 3 holes).

[0106] For par 4 or par 5 holes, the potential outcomes of the tee - off hole event in the example shown include hitting the fairway (which can be represented by "1") and missing the fairway (which can be represented by "0"). The historical data used to generate probabilities can include representative occurrences, such as the percentage of occurrences relative to the player's position (percentage of fairway hits on par 4 / par 5 holes), the collective average of the hole (tour average of fairway hits of the hole), and the collective average of par 4 / par 5 holes (tour average of fairway hits of par 4 / par 5 holes).

[0107] In the illustrated embodiment, a weighted probability (902) of a tee-off hole event corresponding to the par attribute of the hole is generated. Statistics may be run through a hole event probability algorithm to generate a greens-in-regulation rate (for par-3 holes) and a fairway-in-regulation rate (for par-4 / par-5 holes). In one example, the hole event probability algorithm includes the log5(M) event probability model identified above, where x = the historical incidence rate of a player making the hole event, y = the collective historical incidence rate of the hole event on a particular hole, and z = the collective historical incidence rate of the hole event during play on multiple courses. When applied to a par-3 hole, for the greens-in-regulation hole event, x = (the player's greens-in-regulation rate for par-3 holes), y = (the greens-in-regulation rate for the hole), and z = (the tour greens-in-regulation rate for par-3 holes). When applied to a par-4 / par-5 hole, for the fairway-in-regulation hole event, x = (the probability of the player hitting the fairway), y = (the probability of the hole being hit in the fairway), and z = (the probability of the tour hitting the fairway).

[0108] The corresponding event probabilities may be used as weights in a weighted random generator algorithm to generate a predicted hole event outcome (904) of the tee-off location hole event. The tee-off examples provided above are binary. Accordingly, a binary weighted random generator algorithm may be used. In an exemplary embodiment regarding a par-4 hole, if the probability value output by the event probability algorithm is 0.63, then for hole event prediction, the binary random number generator is weighted to have a 63% chance of outputting a fairway-in-regulation result and a 37% chance of outputting a missed-fairway result for the fairway-in-regulation event.

[0109] For par-4 / par-5 holes, relevant collective history and historical player GIR data can be retrieved from the statistical database, and the position of the tee shot hole event result is used as the statistical "source" position to calculate the subsequent shot position hole event probability (906). The subsequent shot hole event in this example is hitting the green, and the predicted hole event result of the tee shot hole is used to identify the "source" position, which is used to define the historical statistical data for generating the probability of hitting the green event. For example, if the result output in step 904 is the predicted fairway hit result for the tee shot hole, the collective historical data and player historical data retrieved in step 906 correspond to the shots from the fairway position. Therefore, the historical data for generating the probability of hitting the green is the green-in-regulation rate from the fairway rather than from off the fairway. The historical data for generating the event probability is the representative occurrence, such as the percentage of occurrence relative to the player's position (GIR for par-4 / par-5 holes), the collective average of the hole (tournament average of GIR for the hole), and the collective average of par-4 / par-5 holes (tournament average of GIR for par-4 / par-5 holes). If the log5(M) probability model is used, then x = "player's green-in-regulation rate from the fairway", y = "hole's green-in-regulation rate from the fairway", and z = "tournament's green-in-regulation rate from the fairway". The potential results of the subsequent shot hole event in the example shown include hitting the green (which can be represented by "1") and missing the green (which can be represented by "0").

[0110] In step 908, a prediction of the hole event result is generated, as in step 904. The predicted hole result can be used to assign a score probability distribution corresponding to the predicted hole result for the hole (910). For example, if steps 904 and 908 return the predicted hole results of hitting the fairway and hitting the green, the hole event result combination is (1, 1), and the score probability distribution assigned to the hole corresponds to this combination (1, 1). For example, a set of score probability distributions is generated or provided for each hole, which includes the score probability distributions corresponding to each potential hole event result or combination as appropriate. As described herein, a hole event distribution can be generated. In one example, the sets of score probability distributions are based on the historical score distributions of the same historical actual hole event results recorded on the hole. For example, the combination (1, 1) for a par-4 hole may correspond to the following score probability distribution:

[0111] Triple bogey = 0.01

[0112] Double bogey = 0.02

[0113] Bogey = 0.10

[0114] Par = 0.66

[0115] Birdie = 0.20

[0116] Eagle = 0.01

[0117] The recognized probability distribution can be used to apply the random score selector algorithm (912). Returning to the example of a par 4 hole, the random score selector algorithm may select par. Thus, the player's score for that hole in this trial round is 4.

[0118] The round difference adjustment (914) can be applied to the predicted hole or round score using the player's round score average. As described above, the round score average can represent the player's relative performance difference with respect to the tournament round and is applied based on the date on which the simulated round occurs relative to the tournament (first round, second round, third round, fourth round). For example, a player's score in a particular simulated round can be -0.36 higher than their average score. Thus, in this simulation round, the adjustment can be made by reducing the score of the hole by -0.02 points. When applied to the current hole, the adjusted predicted hole score is 3.98. As described above, the difference adjustment can be optional, and in some embodiments, the adjustment is applied to the round score rather than the individual hole score.

[0119] The above method can be repeated for all holes and all rounds of the tournament (916).

[0120] The cut line protocol (18) can be applied according to the tournament rules. The cut line protocol can be applied as described above. In one example, the cut line protocol is similar to the cut line protocol described with reference to Figure 3 Simulations are performed for all tournament rounds of each player because this data may be required for update operations during the actual tournament. In one example, for each set of four rounds in each tournament trial run, advancement is implemented according to the tournament rules and applied to the venue of this trial. The system only counts the simulated third and fourth rounds for players who actually or are expected to advance in this trial (920).

[0121] The above method can be repeated, for example, hundreds or thousands of times to generate multiple simulation trials (922).

[0122] The result probability can be calculated based on the occurrence of the results in the simulation trials. Any desired result probability can be calculated, such as the result probabilities described herein. In one example, the result probability includes one or more of the probability of winning, the cut line value probability, the probability of entering the top 10, the probability of advancing, or a combination thereof.

[0123] The winning probability can be determined as described above. In one example, the winning probability for each player on the field is determined before the start of the tournament based on the number of times the player won first place in a single simulation of the event divided by the total number of simulation trials. In some embodiments, the player with the lowest score among the advancing players is identified as the winner of that simulation trial. Then the total number of wins for each player is added together to arrive at the winning probability before the tournament. If there is a tie, each player with the lowest score can be awarded the winning score. For example, the winning score can be calculated by dividing 1 by the number of players with the lowest score.

[0124] Store the results of the simulation trials for use in the update phase of the method (926). Updates to the result probabilities can be performed during the actual play of the tournament (928). The method can include continuing to calculate the probabilities for each player after the start of the tournament. As described above, the updates can continue at predefined time intervals, after receiving updated scores, or both. The updates can include real-time score data to update the result probabilities in real time. The updates can be performed as described above, for example with reference to Figure 7 and Figure 8 and the accompanying text.

[0125] The systems and methods disclosed herein can include other functions and features. For example, the operating functions of system 10 ( Figure 10 ) and the method can be configured to execute on a dedicated processor that is specifically configured to perform the operations provided by system 10 and the method. The various embodiments of the present disclosure, including the example functional operations described in this disclosure, can be implemented in digital electronic circuitry, tangibly embodied computer software or firmware, computer hardware (including the structures disclosed in this specification and their structural equivalents), or in a combination of one or more of them. That is, the various embodiments of the present disclosure can be implemented as one or more computer programs, i.e., one or more modules of computer program instructions encoded on a tangible non-transitory computer-readable medium for execution by, or to control the operation of, a data processing apparatus. The processes and logical flows described in this specification can be performed by one or more programmable computers executing one or more computer programs to perform functions by operating on input data and generating output. These processes and logical flows can also be performed by, and the apparatus can also be implemented as, special purpose logic circuitry, such as an FPGA (field programmable gate array) or an ASIC (application specific integrated circuit).

[0126] It should be noted that the operating characteristics and functions provided by the system 10 and the method can improve the efficiency of computing devices that are used to facilitate the functions provided by the system 10 and the various methods disclosed herein. For example, by utilizing the alternative methods described herein, the selection of the voxel event probability described herein, and / or other information provided and / or generated in the system 10, the amount of computer operations that the devices in the system 10 need to perform using the processor and memory of the system 10 is less than that of traditional methods. In such an environment, less processing power needs to be utilized because the processor and memory do not need to be dedicated to processing. Therefore, the utilization rate of computer resources can be greatly saved by using the software, techniques, and algorithms provided by the present disclosure. In some embodiments, the various operating functions of the system 10 can be configured to be executed on one or more graphics processors and / or dedicated integrated processors.

[0127] It should be noted that in some embodiments, the various functions and features of the system 10 and the method can operate without any manual intervention and can be entirely performed by computing devices. In some embodiments, for example, many computing devices can interact with the devices of the system 10 to provide the functions supported by the system 10. In addition, in some embodiments, the computing devices of the system 10 can operate continuously without manual intervention to reduce the possibility of introducing errors into the system 10. In some embodiments, the system 10 and the method can also utilize the features and functions described in the present disclosure to provide effective computing resource management. For example, in some embodiments, the devices in the system 10 can transmit signals indicating that only a specific amount of computer processor resources (e.g., processor clock cycles, processor speed, etc.) can be dedicated to utilizing volume rendering, generating a surgical plan for a subject, performing a registration process, and / or performing any other operations performed by the system 10, or any combination thereof. For example, the signal can indicate that multiple processor cycles of the available processor can be utilized to enhance the image set through volume rendering, and / or specify the selected processing power dedicated to generating or performed by the system 10 for any operation.

[0128] In some embodiments, any device in system 10 can send a signal to a storage device to cause the storage device to dedicate only a selected amount of storage resources to the various operations of system 10. In some embodiments, system 10 and the method can also include transmitting signals to a processor and a memory to perform the operational functions of system 10 and the method only during a time period when the utilization rate of the processing resources and / or storage resources in system 10 is at a selected value. In some embodiments, system 10 and the method can include sending a signal to a storage device used in system 10, the signal indicating that a particular portion of the memory should be utilized to store any data used or generated by system 10. It is noted that the signals transmitted to the processor and the memory can be used to optimize the utilization rate of computing resources when performing the operations carried out by system 10. Thus, compared with the prior art, such functions provide significant operational efficiency and improvements.

[0129] Also refer to Figure 11 , at least a portion of the methods and techniques described with respect to the exemplary embodiments of system 10 can be combined with a machine, such as but not limited to computer system 1100 or other computing devices, a set of instructions in which, when executed, can cause the machine to perform any one or more of the above methods or functions. The machine can be configured to facilitate the various operations carried out by system 10. For example, the machine can be configured to (but not limited to) assist system 10 in the following ways: providing processing capabilities to assist in handling the load encountered in system 10, providing storage capacity to store instructions or data throughout system 10, or assisting in any other operations carried out by or within system 10. As another example, computer system 1100 can assist in generating models associated with prediction generation, these predictions relating to hole events, result generation, hole score generation, score probability distribution, prediction results, prediction result probabilities, score difference adjustment, cut line values, player probabilities relative to the cut line, updates to any of the above, or combinations thereof, present in the environment monitored by system 10. As another example, computer system 1100 can assist in collecting and / or importing and processing historical data including player tournament statistics, which can include hole statistics. As another example, computer system 1100 can assist in generating score probability distributions, random score generation, weighted result generation, or combinations thereof. As another example, computer system 1100 can assist in outputting and / or distributing predictions to television broadcasts, streaming broadcasts, digital platforms for viewing, operating, formatting, or combinations thereof.

[0130] In some embodiments, the machine can operate as a stand-alone device. In some embodiments, the machine can be connected to other machines and systems and assist them in performing operations, such as but not limited to any of the functions, generators, regulators, engine actuators, or other functions described herein, any of which can be provided to the machine by such other machines or systems for the system 10 to perform the operations described herein. The machine can be connected to any component in the system 10. In a network deployment, the machine can operate as a server or a client user machine in a server-client user network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine can include a server computer, a client user computer, a personal computer (PC), a tablet, a laptop, a desktop computer, a control system, a network router, a switch, or a bridge, or any machine capable of executing a set of instructions (sequential or otherwise), the set of instructions specifying the operations to be taken by the machine. Further, although one machine is shown in the figures, the "machine" should also be regarded as including any collection of machines that, individually or jointly, execute a set (or multiple sets) of instructions to perform one or more of the methods discussed herein.

[0131] The computer system 1100 can include a processor 1102 (e.g., a central processing unit (CPU), a graphics processing unit (GPU), or both), a main memory 1104, and a static memory 1106 that communicate with each other via a bus 1108. The computer system 1100 can also include a video display unit 1110, which can be, but is not limited to, a liquid crystal display (LCD), a flat panel, a solid state display, or a cathode ray tube (CRT). The computer system 1100 can include an input device 1112 (e.g., but not limited to a keyboard), a cursor control device 1114 (e.g., but not limited to a mouse), a disk drive unit 1116, a signal generation device 1118 (e.g., but not limited to a speaker or a remote control), and a network interface device 1120.

[0132] The disk drive unit 1116 can include a machine-readable medium 1122 on which is stored a set or multiple sets of instructions 1124, such as but not limited to software embodying any one or more of the methods (including those illustrated above) or functions described herein. The instructions 1124 can also reside, completely or at least partially, in the main memory 1104, the static memory 1106, the processor 1102, or a combination thereof during execution by the computer system 1100. The main memory 1104 and the processor 1102 can also constitute a machine-readable medium.

[0133] Dedicated hardware implementations can also be constructed to implement the methods described herein, and the dedicated hardware implementations include, but are not limited to, application specific integrated circuits, programmable logic arrays, and other hardware devices. Applications of apparatus and systems that may include various embodiments generally include various electronic systems and computer systems. Some embodiments implement functionality in two or more particular interconnected hardware modules or devices, where related control and data signals communicate between or through the modules, or as part of an application specific integrated circuit. Accordingly, the exemplary systems are applicable to software, firmware, and hardware implementations.

[0134] In accordance with various embodiments of the present disclosure, the methods described herein are intended to operate as software programs running on a computer processor. Additionally, software implementations may include, but are not limited to, distributed processing or component / object distributed processing, parallel processing, or virtual machine processing, and may also be constructed to implement the methods described herein.

[0135] The present disclosure contemplates a machine-readable medium 1122 that includes instructions 1124 such that a device connected to a communication network 1135, another network, or a combination thereof can send or receive voice, video, or data, and communicate using the above instructions via the communication network 1135, another network, or a combination thereof. Instructions 1124 can also be sent or received via a network interface device 1120 through the communication network 1135, another network, or a combination thereof.

[0136] Although the machine-readable medium 1122 is shown as a single medium in the exemplary embodiment, the term "machine-readable medium" should be considered to include a single medium or multiple media (e.g., a centralized or distributed database and / or associated caches and servers) that store a set or multiple sets of instructions. The term "machine-readable medium" should also be considered to include any medium that is capable of storing, encoding, or carrying a set of instructions that are executed by a machine and cause the machine to perform any one or more of the methods of the present disclosure.

[0137] Thus, the terms "machine-readable medium", "machine-readable device", or "computer-readable device" should be regarded as including, but not limited to: storage devices, solid-state memories such as memory cards or other packages containing one or more read-only (non-volatile) memories, random access memories, or other rewritable (volatile) memories; magneto-optical or optical media such as magnetic disks or tapes; or other separate information archives or collections of archives, which are regarded as equivalent to distributed media of tangible storage media. The "machine-readable medium", "machine-readable device", or "computer-readable device" can be non-transitory and may not include waves or signals themselves in some embodiments. Accordingly, the present disclosure is regarded as including any one or more of the machine-readable media or distributed media listed herein, and including equivalent and successor media recognized in the art for storing software implementations herein.

[0138] The setups described herein are intended to provide an overall understanding of the structures of various embodiments and are not intended as a complete description of all elements and features of the devices and systems that may utilize the structures described herein. Other setups can be derived from these setups, such that structural and logical substitutions and changes can be made without departing from the scope of the present disclosure. The drawings are also for reference only and may not be drawn to scale. Some of the scales may be exaggerated while others may be minimized. Accordingly, the specification and the drawings should be regarded as illustrative rather than restrictive.

[0139] Thus, although specific setups have been illustrated and described herein, it should be understood that any setup intended to achieve the same purpose can be substituted for the specific setup shown. The present disclosure is intended to cover any and all modifications or variations of the various embodiments and setups of the present invention. Combinations of the above setups and other setups not specifically described herein will be apparent to those skilled in the art after reading the above description. Accordingly, the present disclosure is not limited to the specific setups disclosed as the best mode contemplated for carrying out the present invention, but the present invention will include all embodiments and setups falling within the scope of the appended claims.

[0140] The above is provided to illustrate, explain, and describe embodiments of the present invention. Modifications and adjustments to these embodiments are obvious to those skilled in the art, and these modifications and adjustments can be made without departing from the scope or spirit of the present invention. By reviewing the above embodiments, it is obvious to those of ordinary skill in the art that the above embodiments can be modified, reduced, or enhanced without departing from the scope and spirit of the claims.

Claims

1. A golf tournament simulation modeling system, comprising: A memory storing instructions; A processor that executes the instructions to perform operations, the operations including: Simulating a golf tournament to generate a prediction result of the golf tournament, including: Generating, for a participating player, one or more hole event probabilities for each hole of each round of the golf tournament, at least partially based on historical statistical data of golf matches stored in a statistical database; Using the hole event probabilities as weights to generate hole event results; Assigning a score probability distribution to each hole based on one or more hole event results generated for each hole; Generating a random score for each hole based on the respective hole score probability distribution; Repeating the simulation of the golf tournament to generate multiple simulations and corresponding prediction results, and calculating the probabilities of one or more prediction results from the multiple simulations; and Updating one or more prediction results and / or prediction result probabilities of the multiple simulations based on actual score data after the actual start of the game.

2. The system according to claim 1, wherein The historical statistical data represents the historical occurrences of specific hole events in an actual tournament for a collective of players for multiple holes, for a collective of players for a specific hole being simulated, and for an individual player who has undergone the simulation for multiple holes.

3. The system according to claim 2, wherein The hole event probabilities are based on historical statistical data related to holes having a par value corresponding to the hole being simulated.

4. The system according to claim 1, wherein, The hole event result of the first hole event of the first hole specifies the elements required to identify the historical statistical data for generating the hole event probability of the second hole event of the first hole.

5. The system according to claim 1, wherein The first hole event probabilities for par-4 and par-5 holes include the probability that a player's tee shot hits the fairway, and the first hole event probability for a par-3 hole includes the probability that a player's tee shot hits the green.

6. The system according to claim 5, wherein, The tee shot hole event probabilities use the historical statistical data, including: For par-3 holes: the on-green rate of players on par-3 holes, the collective on-green rate for the hole, and the collective on-green rate for par-3 holes; and For par-4 and par-5 holes: the probability that a player on par-4 and par-5 holes hits the fairway, the collective probability of hitting the fairway for the hole, and the collective probability of hitting the fairway for par-4 and par-5 holes.

7. The system according to claim 5, wherein The second hole event probabilities for par-4 and par-5 holes include the probability that the player hits the green from the position determined by the prediction result of the first hole event.

8. The system according to claim 7, wherein, In the case where the predicted hole event position result of the tee shot position hole event calculated for the hole is the fairway, the historical statistical data of subsequent shot position hole events includes historical statistical data corresponding to the historical occurrences of hitting the green from the fairway, including the on-green rate of players on par-4 and par-5 holes from the fairway, the collective on-green rate from the fairway for the hole, and the collective on-green rate from the fairway for par-4 and par-5 holes; and in the case where the predicted hole event position result of the tee shot position hole event calculated for the hole is not the fairway, the historical statistical data of subsequent shot position hole events includes historical statistical data corresponding to the historical occurrences of hitting the green from off the fairway, including the on-green rate of players on par-4 and par-5 holes from off the fairway, the collective on-green rate from off the fairway for the hole, and the collective on-green rate from off the fairway for par-4 and par-5 holes.

9. The system according to claim 1, wherein, The hole event probability algorithm is adopted to generate the hole event probability, wherein the hole event probability algorithm includes: where x is the historical incidence rate of a player's hole events, y is the collective historical incidence rate of hole events on a specific hole, and z is the collective historical incidence rate of hole events during competitions on multiple golf courses.

10. The system according to claim 1, wherein The score probability distribution represents the historical score distribution of the hole in the case of various potential hole event results or combinations of hole event results for the hole.

11. The system according to claim 1, wherein, The update operation includes: when a player completes a hole-in-one, replacing the predicted hole score with the actual hole score; updating the predicted round score in consideration of the replaced actual hole score; adding up the updated predicted round scores in all tournament rounds to generate an updated predicted tournament score for the participating players; adding up the updated predicted round scores in the preliminary round to set an updated advancement line; including the predicted round scores in the semi-final round in the scores of the non-advanced players; and excluding the predicted round scores in the semi-final round from the scores of the non-advanced players.

12. The system according to claim 1, wherein The operation further includes: transmitting the prediction result probability of each player to the database using the player identification ID and timestamp to display the latest probability, thereby allowing digital trend display on television broadcasts and digital platforms.

13. A system for updating a golf tournament simulation, comprising: a memory storing instructions; a processor executing the instructions to perform operations, the operations including: real-time updating each tournament simulation of the golf tournament by: when a player completes a hole-in-one, replacing the predicted hole score with the actual hole score; updating the predicted round score in consideration of the replaced actual hole score; generating an updated predicted tournament score for all participating players according to the updated predicted round scores for all participating players in all tournament rounds; establishing an updated advancement line based on the updated predicted round scores in the preliminary round; in the updated predicted tournament score, including the predicted round scores in the semi-final round in the scores of the advanced players and excluding the predicted round scores in the semi-final round from the scores of the non-advanced players; and updating the prediction result; and updating one or more prediction result probabilities according to the collectively updated prediction results.

14. The system according to claim 13, wherein, The one or more prediction result probabilities include: winning probability, probability of entering the top 10, probability of reaching the advancement line, and advancement probability.

15. A method for simulating a golf event, comprising: performing one round of simulation for each participating player in the golf event: generating a predicted hole score for each hole in the golf round, including: for each hole, calculating the hole event probability of each hole event among one or more hole events assigned to a hole in the golf round; using the event probabilities calculated for the respective hole events as weights to generate predicted hole event results for each hole event among the one or more hole events; allocating a score probability distribution to the hole from multiple score probability distributions, the score probability distribution corresponding to one or more predicted hole results generated for the hole; and using the allocated score probability distribution to generate the predicted hole score for the hole; and Generate a predicted round score based on the predicted hole scores.

16. The method according to claim 15, wherein Calculating the one or more hole event probabilities is at least partially based on historical statistical data representing the historical occurrences of hole events in actual tournaments by a collective of players for multiple holes, by a collective of players for a particular simulated hole, and by individual players who have undergone the simulation for multiple holes.

17. The method according to claim 15, wherein Calculating the one or more hole event probabilities includes processing historical statistical data representing the historical occurrences of hole events in actual tournaments through the following event probability model: where x is the historical incidence rate of a player making a hole event, y is the collective historical incidence rate of hole events on a particular hole, and z is the collective historical performance of hole events during play on multiple courses.

18. The method according to claim 17, wherein, The hole event probability corresponds to the probability of a hole event occurring on the hole, and the historical statistical data is related to holes having hole attributes corresponding to the simulated hole.

19. The method according to claim 18, wherein, The first hole event probability for a par 4 hole includes the probability that a player's tee shot hits the fairway, where x is the probability that players on par 4 and par 5 holes hit the fairway, y is the probability that the collective hits the fairway for the hole, and z is the collective probability that par 4 and par 5 holes hit the fairway.

20. The method according to claim 19, wherein, The second hole event probability for the par 4 hole includes the probability that a player hits the green from the position specified by the prediction result of the first hole event on a subsequent shot.

21. The method according to claim 20, wherein, In the case where the prediction result of the first hole event is hitting the fairway, the historical statistical data corresponds to the historical occurrences of hitting the green from the fairway, x is the green-in-regulation rate of players on par 4 and par 5 holes from the fairway, y is the collective green-in-regulation rate from the fairway on the hole, and z is the collective green-in-regulation rate from the fairway for par 4 and par 5 holes; and in the case where the prediction result of the first hole event is missing the fairway, the historical statistical data corresponds to the historical occurrences of hitting the green from off the fairway, x is the green-in-regulation rate of players on par 4 and par 5 holes from off the fairway, y is the collective green-in-regulation rate from off the fairway on the hole, and z is the collective green-in-regulation rate from off the fairway for par 4 and par 5 holes.

22. The method according to claim 15, further comprising generating a predicted hole event outcome for each of the one or more hole events using the event probability calculated for each hole event as a weight, including: Input the calculated hole event probabilities into a weighted random generator algorithm.

23. The method according to claim 15, wherein Each hole is associated with multiple score probability distributions, and each score probability distribution corresponds to a specific predicted hole event outcome or a combination of predicted hole event outcomes for the hole.

24. The method according to claim 23, wherein, The score probability distribution represents the historical score distribution on the hole in the case of a particular hole event occurring.

25. The method according to claim 23, wherein, Assigning the score probability distribution includes pairing the one or more predicted hole event outcomes of the hole with the score probability distribution corresponding to the predicted hole event outcome.

26. The method according to claim 15, wherein Generating the predicted hole score using the assigned score probability distribution includes inputting the assigned score probability distribution into a random score selector algorithm to generate a predicted hole score.

27. The method according to claim 15 further comprises: Apply a score adjustment to the predicted hole scores.

28. The method according to claim 15, wherein, The adjustment is applied to each hole score.

29. The method according to claim 15 further comprises: Adjust the predicted hole scores based on the difference between the round score means of all tournament rounds and a particular tournament round of the simulated player in the tournament.

30. A computer-implemented method for updating a golf tournament simulation, comprising: Generate predicted round scores for each round of the simulated tournament, including: Generate predicted hole scores for each hole in the round, including: Retrieve relevant collective history and historical player data from a statistical database to generate hole event probabilities for each hole event in one or more hole events in the round; Process the collective history and historical player data through a hole event probability algorithm to generate hole event probabilities for each hole event; Use the generated hole event probabilities as weights in a weighted random generator algorithm to calculate predicted hole event outcomes for each hole event; Assign a score probability distribution to each hole, the score probability distribution corresponding to one or more predicted hole event outcomes for the hole; and Input the assigned score probability distribution into a random score selector algorithm to generate predicted hole scores for each hole; and Calculate the predicted round score based on the predicted hole scores; Repeat generating predicted round scores for all tournament rounds for each competing player, and further repeat to generate multiple tournament simulations; Calculate one or more outcome probabilities from the multiple tournament simulations; Store the tournament simulations for update processing; and Update all simulations as needed during the actual conduct of the tournament and update the predicted outcome probabilities.

31. The method according to claim 30, wherein, The predicted round score is the sum of the predicted hole scores for each hole in the round.

32. The method according to claim 30, wherein, The predicted round score includes an adjusted sum of the predicted hole scores for the round, or a sum of the adjusted predicted hole scores for the round.

33. The method according to claim 31 further comprises: Apply a score adjustment at least partially based on the historical player data of the simulated player.

34. The method according to claim 33, wherein The adjustment is applied to each hole score.

35. The method according to claim 33, wherein, The adjustment is applied to the predicted round score.

36. The method according to any one of claims 4 to 6, wherein The historical player data includes the differences of the player in actual historical competitions.

37. The method according to claim 36, wherein, The difference of the player in actual historical competitions is the difference relative to the average score of the tournament round corresponding to the simulated round for all tournament rounds.

38. The method according to claim 32, further comprising: Adjust the predicted hole score based on the difference between the average round score of the simulated player in all tournament rounds and the average round score of the player in the tournament in the simulated specific round.

39. The method according to claim 32, further comprising: Apply a round adjustment to each predicted hole score output by the random score selector algorithm or the round score calculated from the predicted hole scores if there is a historical competition difference in the average round score of the simulated player in the simulated round relative to the average round score of the player in all tournament rounds.

40. The method according to any one of claims 33 to 10, wherein The historical competition includes a rolling average of one or more seasons.

41. The method according to any one of claims 33 to 40, wherein Newer historical data points in the historical competition have a greater weight.

42. The method according to any one of claims 31 to 41, further comprising: Apply a cut line protocol to each tournament simulation according to tournament rules; And do not include the predicted round scores of the replay rounds in the predicted tournament scores of players predicted not to advance.

43. The method according to claim 42, wherein, The cut line protocol includes: Conduct round simulations for the preliminary rounds to generate predicted round scores for all players in each preliminary round; Establish a tournament cut line based on the predicted round scores from the preliminary rounds; and Conduct a round simulation for the semi-final round of the players predicted to advance to generate the predicted round scores of the players predicted to advance in the semi-final round.

44. The method according to claim 42, wherein The advancement line protocol includes: Conduct a round simulation for the preliminary round and the semi-final round to generate the predicted round scores of all players in the preliminary round and the semi-final round; and Establish a golf tournament advancement line based on the predicted round scores from the preliminary round.

45. The method according to any one of claims 30 to 44, wherein, The hole event probability corresponds to the probability of a hole event occurring on the hole.

46. The method according to any one of claims 30 to 45, wherein The relevant collective history and historical player data represent the historical occurrence of the hole event in actual competitions in tournaments at the same or similar levels.

47. The method according to any one of claims 30 to 46, wherein, The relevant collective history data represents the historical occurrence of the hole event of the collective players for multiple holes and the specific hole being simulated in the actual tournament, and the historical player data represents the historical occurrence of the reserved events of the player being simulated for multiple holes.

48. The method according to any one of claims 30 to 47, wherein The relevant collective history and historical player data correspond to the occurrence of the hole event on the hole whose hole attributes correspond to the hole being simulated.

49. The method according to claim 48, wherein The attribute is the par value.

50. The method according to any one of claims 30 to 49, wherein, The hole event result of the first hole event of the first hole specifies the elements required to identify the relevant collective history and historical player data for generating the hole event probability of the second hole event of the first hole.

51. The method according to any one of claims 30 to 40, further comprising: Calculate that the hole event probability of a par-4 hole and / or a par-5 hole is greater than the hole event probability of a par-3 hole.

52. The method according to any one of claims 30 to 51, wherein The one or more hole events include a first hole event, where the first hole event includes the hitting position of the tee shot, and the first hole event probability includes the probability that the player's tee shot hits the hitting position.

53. The method according to claim 52, wherein The result of the hitting position of the tee shot is based on the attributes of the hole.

54. The method according to claim 53, wherein, The attribute of the hole is the par grade of the hole. The first hole event probability of a par-4 hole includes the probability that the player's tee shot hits the fairway, and the first hole event probability of a par-3 hole includes the probability that the player's tee shot hits the green.

55. The method according to claim 54, wherein, Relative to at least one hole, the one or more hole events further include a second hole event, and the second hole event includes the hitting position of the subsequent shot.

56. The method according to claim 55, wherein, The result of the subsequent hitting position is based on the attributes of the hole.

57. The method according to claim 56, wherein The attribute of the hole is the par grade of the hole.

58. The method according to claim 57, wherein, The second hole event probability of a par-4 hole includes the probability that the player hits the green from the position determined by the predicted result of the first hole event.

59. The method according to any one of claims 30 to 51, wherein, Each hole includes a first hole event corresponding to the hitting position.

60. The method according to claim 59, wherein, The first hole event corresponds to the tee shot position hole event, including the green of a par-3 hole and the fairway of a par-4 hole and a par-5 hole.

61. The method according to claim 60, wherein, The relevant collective history and historical player data of the tee shot position hole event include: For a par-3 hole: the player's green-in-regulation rate of the par-3 hole, the collective green-in-regulation rate for the hole, and the collective green-in-regulation rate of the par-3 hole; and For a par-4 hole and a par-5 hole: the probability that the player of the par-4 hole and the par-5 hole hits the fairway, the collective probability of hitting the fairway for the hole, and the collective probability of hitting the fairway of the par-4 hole and the par-5 hole.

62. The method according to claim 60 or 61, wherein, The one or more hole events include the second hole event of at least some holes.

63. The method according to claim 62, wherein, The second hole event includes a subsequent hitting position hole event corresponding to the hitting position after the tee shot.

64. The method according to claim 63, wherein, Generating the predicted hole score of a par-4 hole includes: Retrieve relevant collective history and historical player data from the statistical database, and use the predicted hole event position result of the tee shot position hole event calculated for the hole as the statistical position to calculate the probability of the subsequent shot position hole event; and Use the corresponding position hole event probability as the weight in the weighted random generator algorithm to calculate the predicted hole event position result of the subsequent shot position hole event.

65. The method according to claim 64, comprising: Repeat the calculation of the predicted hole result of the subsequent shot position hole event for a par-5 hole in a manner similar to that of a par-4 hole.

66. The method according to claim 64 or 65, In the case where the predicted hole event position result of the tee shot position hole event calculated for the hole is the fairway, the collective history and historical player data related to the subsequent shot position hole event include historical statistical data corresponding to the historical occurrences of hitting the green from the fairway, including the greens-in-regulation rates of players on par-4 and par-5 holes from the fairway, the collective greens-in-regulation rate on the hole from the fairway, and the collective greens-in-regulation rate of par-4 and par-5 holes from the fairway; and In the case where the predicted hole event position result of the tee shot position hole event calculated for the hole is off the fairway, the collective history and historical player data related to the subsequent shot position hole event include historical statistical data corresponding to the historical occurrences of hitting the green from off the fairway, including the greens-in-regulation rates of players on par-4 and par-5 holes from off the fairway, the collective greens-in-regulation rate on the hole from off the fairway, and the collective greens-in-regulation rate of par-4 and par-5 holes from off the fairway.

67. The method according to any one of claims 30 to 66, wherein, The hole event probability algorithm includes: where x is the historical occurrence rate of a player performing a hole event, y is the collective historical occurrence rate of the hole event on a specific hole, and z is the collective historical occurrence rate of the hole event during play on multiple courses.

68. The method according to claim 67, wherein, The first hole event probability for par-4 and par-5 holes includes the probability that a player's tee shot hits the fairway, where x is the probability that a player on par-4 and par-5 holes hits the fairway, y is the probability that the hole is collectively hit on the fairway, and z is the probability that par-4 and par-5 holes are collectively hit on the fairway.

69. The method according to claim 68, wherein The second hole event probability for the par-4 and par-5 holes includes the probability that a player hits the green from the position specified by the prediction result of the first hole event during the subsequent shot.

70. The method according to claim 69, wherein, In the case where the prediction result of the first hole event is hitting the fairway, the collective history and player collective history data correspond to the historical occurrences of hitting the green from the fairway, x is the greens-in-regulation rate of players on par-4 and par-5 holes from the fairway, y is the collective greens-in-regulation rate on the hole from the fairway, and z is the collective greens-in-regulation rate of par-4 and par-5 holes from the fairway; and in the case where the prediction result of the first hole event is missing the fairway, the historical statistical data correspond to the historical occurrences of hitting the green from off the fairway, x is the greens-in-regulation rate of players on par-4 and par-5 holes from off the fairway, y is the collective greens-in-regulation rate on the hole from off the fairway, and z is the collective greens-in-regulation rate of par-4 and par-5 holes from off the fairway.

71. The method according to any one of claims 66 to 70, wherein, The first hole event probability for a par-3 hole includes the probability that a player's tee shot hits the green, where x is the greens-in-regulation rate of players on par-3 holes, y is the collective greens-in-regulation rate for the hole, and z is the collective greens-in-regulation rate of par-3 holes.

72. The method according to any one of claims 30 to 71, wherein One or more predicted hole event outcomes for each hole are binary.

73. The method according to any one of claims 30 to 72, wherein Each hole is associated with multiple score probability distributions, and each score probability distribution corresponds to a specific predicted hole event outcome or combination of predicted hole event outcomes for the hole.

74. The method according to claim 73, wherein, The score probability distribution represents the historical score distribution of the hole in the case of the occurrence of respective potential hole event outcomes or combinations thereof.

75. The method according to claim 74, wherein, Assigning the score probability distribution includes: pairing the one or more predicted hole event outcomes of the hole with the score probability distribution corresponding to the predicted hole event outcome.

76. The method according to any one of claims 30 to 75, wherein, Calculating one or more outcome probabilities includes calculating the probability of a predicted outcome, including: Analyzing whether the predicted outcome occurs in multiple simulations; and Dividing the number of simulations in which the predicted outcome occurs by the total number of simulations.

77. The method according to claim 76, wherein, The one or more predicted outcomes include: scores or score ranges on one or more holes in one round of the tournament, scores or score ranges on one or more holes in two or more rounds of the tournament, hole events on one or more holes in one round of the tournament, hole events on one or more holes in two or more rounds of the tournament, or combinations thereof.

78. The method according to claim 76 or 77, wherein, The one or more predicted outcomes include: designated scores or scores within a designated range in one or more rounds of the tournament, designated hole scores on one or more holes in one or more rounds, or combinations thereof.

79. The method according to any one of claims 76 to 78, wherein, The one or more predicted outcomes include: the ranking of a player's finishing position by round, the player's finishing position, the range of the player's finishing position, or combinations thereof.

80. The method according to any one of claims 76 to 79, wherein, The one or more predicted outcomes include: the probability that a player finishes the game with the lowest round score, the probability that a player finishes the game with a round score within a designated finishing position ranking, or combinations thereof.

81. The method according to any one of claims 76 to 80, wherein The one or more predicted outcomes include: the ranking of a player's finishing position in one or more rounds of the tournament, the ranking of the player's finishing position in the tournament, the player's finishing position in one or more rounds of the tournament, the range of the player's finishing position in one or more rounds of the tournament, tournament win, advancement, advancement line, or combinations thereof.

82. The method according to any one of claims 76 to 81, wherein, The one or more predicted outcomes include: the probability ranking of a player's finishing position in one or more rounds of the tournament, the probability ranking of the player's finishing position in the tournament, the probability of the player's finishing position in one or more rounds of the tournament, the probability that the player finishes within the range of the finishing position in one or more rounds of the tournament, the probability that the player wins the tournament, the probability that the player advances, the advancement line probability, or combinations thereof.

83. The method according to any one of claims 76 to 82, wherein The predicted outcome probabilities include: the probability of winning, the probability of entering the top 10, the probability of reaching the advancement line, and the probability of advancement.

84. The method according to any one of claims 30 to 83, wherein The update includes: When a player completes a hole, replacing the predicted hole score with the actual hole score; Updating the predicted round score considering the replaced actual hole score; Adding up the updated predicted round scores in all tournament rounds to generate an updated predicted tournament score for the participating player; Adding up the updated predicted round scores in the preliminary round to set an updated advancement line; Include the predicted round scores of the semi-final round in the scores of the non-advancing players; and Do not include the predicted round scores of the semi-final round in the scores of the non-advancing players.

85. The method according to any one of claims 30 to 84, wherein When receiving the actual on-site score data, perform updates at intervals of less than 30 seconds during the competition.

86. The method according to any one of claims 30 to 85, wherein Perform updates during the actual golf tournament until the tournament ends.

87. The method according to any one of claims 30 to 86, further comprising: Use the player identification ID and timestamp to move the information of each player to the database to display the latest probabilities, thereby allowing trend display digitally on television broadcasts and digital platforms.

88. A system, comprising a processor and a storage medium storing instructions, which when executed by the processor cause the system to perform the method according to any one of claims 30 to 87.

89. A machine-readable medium carrying machine-readable instructions, which when executed by a processor of a machine cause the machine to perform the method according to any one of claims 30 to 89.

90. A computer-implemented golf tournament simulation modeling system, comprising: A statistical database including historical statistical data of golf ball games; A hole event probability generator configured to use the historical statistical data to generate one or more hole event probabilities for each hole of each round of a golf tournament based on at least a portion of the historical statistical data; A hole event result generator configured to use the hole event probabilities as weights to generate hole event results, wherein the hole event generator includes a weighted result generator or is configured to access the operations of a weighted result generator, the weighted result generator being configured to use the hole event probabilities as weights to generate the results of hole events; A hole score generator configured to assign a score probability distribution to each hole based on the one or more hole event results generated for each hole, wherein the hole score generator includes a score distribution engine or is configured to access the operations of a score distribution engine, the score distribution engine being configured to generate or provide a hole score probability distribution of potential combinations of hole event results, wherein the hole score generator includes a random score generator or is configured to access the operations of a random score generator, the random score generator being configured to generate a random score based on the hole score probability distribution identified by the hole score generator; A prediction engine configured to output a prediction regarding the golf tournament, wherein the prediction engine includes a prediction result generator configured to generate a prediction result, wherein the prediction engine includes a prediction result probability generator configured to generate one or more probabilities of the prediction result based on the prediction of the prediction result in multiple simulations of the golf tournament; and An update processor configured to update one or more prediction results and / or prediction result probabilities based on actual score data after the actual start of the competition.

91. The golf tournament simulation modeling system according to claim 90, wherein, The historical statistical data used by the hole event probability generator includes historical statistical data representing the historical occurrences of specific hole events of collective players for multiple holes, collective players for a specific hole being simulated, and individual players who have undergone simulations for multiple holes in the actual tournament.

92. The golf tournament simulation modeling system according to claim 90 or 91, wherein, The hole event probability generator is configured to generate hole event probabilities based on historical statistics related to holes having hole attributes corresponding to simulated holes.

93. The golf tournament simulation modeling system according to claim 92, wherein, The attribute is a par value.

94. The golf tournament simulation modeling system according to any one of claims 90 to 69, wherein, The one or more hole events include a first hole event.

95. The golf tournament simulation modeling system according to any one of claims 90 to 94, wherein, For at least one hole, the hole events include a first hole event of the first hole and a second hole event of the first hole, wherein both the first hole event and the second hole event include a stroke position.

96. The golf tournament simulation modeling system according to any one of claims 90 to 95, wherein The hole event result of the first hole event of the first hole specifies elements required to identify the historical statistics for generating the hole event probability of the second hole event of the first hole.

97. The golf tournament simulation modeling system according to any one of claims 90 to 96, wherein, The hole event probability generator is configured to generate hole event probabilities for par-4 and par-5 holes that are greater than the hole event probabilities for par-3 holes.

98. The golf tournament simulation modeling system according to any one of claims 90 to 97, wherein, The hole event probability generator is configured to generate a first hole event probability for a par-4 hole, including the probability that a player's tee shot hits the fairway; and to generate a first hole event probability for a par-3 hole, including the probability that a player's tee shot hits the green.

99. The golf tournament simulation modeling system according to claim 98, wherein, The hole event probability generator is configured to use the historical statistics to generate tee shot hole event probabilities, including: For par-3 holes: the player-on-green rate for par-3 holes, the collective-on-green rate for the hole, and the collective-on-green rate for par-3 holes; and For par-4 and par-5 holes: the probability that a player hits the fairway for par-4 and par-5 holes, the collective fairway hit rate for the hole, and the collective fairway hit rate for par-4 and par-5 holes.

100. The golf tournament simulation modeling system according to any one of claims 94 to 98, wherein, The one or more hole events include second hole events for at least some holes.

101. The golf tournament simulation modeling system according to claim 100, wherein, The second hole event includes a subsequent stroke position hole event corresponding to a stroke position after a tee shot.

102. The golf tournament simulation and modeling system according to claim 101, wherein, The hole event probability generator is configured to generate second hole event probabilities for par-4 and par-5 holes, including the probability that a player hits the green from a position determined by the predicted result of the first hole event generated by the hole event result generator.

103. The golf tournament simulation modeling system according to claim 101, wherein, In the case where the predicted hole event position result of the tee shot position hole event calculated for the hole is the fairway, the historical statistics of the subsequent stroke position hole event include historical statistics corresponding to the historical occurrence of hitting the green from the fairway, including the player-on-green rate from the fairway for par-4 and par-5 holes, the collective-on-green rate from the fairway for the hole, and the collective-on-green rate from the fairway for par-4 and par-5 holes; and, in the case where the predicted hole event position result of the tee shot position hole event calculated for the hole is not the fairway, the historical statistics of the subsequent stroke position hole event include historical statistics corresponding to the historical occurrence of hitting the green from off the fairway, including the player-on-green rate from off the fairway for par-4 and par-5 holes, the collective-on-green rate from off the fairway for the hole, and the collective-on-green rate from off the fairway for par-4 and par-5 holes.

104. The golf tournament simulation modeling system according to any one of claims 90 to 103, wherein, The hole event probability generator is configured to execute a hole event probability algorithm to generate the hole event probabilities, wherein the hole event probability algorithm includes: where x is the historical occurrence rate of a player performing a hole event, y is the collective historical occurrence rate of hole events on a particular hole, and z is the collective historical occurrence rate of hole events during play on multiple courses.

105. The golf tournament simulation and modeling system according to claim 104, wherein, The first-hole event probability for par-4 and par-5 holes includes the probability that a player's tee shot hits the fairway. Here, x is the probability that a player on par-4 and par-5 holes hits the fairway, y is the probability that the group hits the fairway for the hole, and z is the probability that the group on par-4 and par-5 holes hits the fairway.

106. The golf tournament simulation modeling system according to claim 104 or 105, wherein, The first-hole event probability for par-3 holes includes the probability that a player's tee shot hits the green. Here, x is the green-in-regulation rate of a player on par-3 holes, y is the group green-in-regulation rate for the hole, and z is the group green-in-regulation rate on par-3 holes.

107. The golf tournament simulation modeling system according to claim 104 or 105, wherein, The second-hole event probability for the par-4 and par-5 holes includes the probability that a player hits the green from a position specified by the prediction result of the first-hole event in subsequent shots.

108. The golf tournament simulation modeling system according to claim 107, wherein, In the case where the prediction result of the first-hole event is hitting the fairway, the historical statistical data used by the hole event probability generator corresponds to the historical occurrence of hitting the green from the fairway. Here, x is the green-in-regulation rate of a player on par-4 and par-5 holes from the fairway, y is the group green-in-regulation rate from the fairway for the hole, and z is the group green-in-regulation rate on par-4 and par-5 holes from the fairway; and in the case where the prediction result of the first-hole event is missing the fairway, the historical statistical data corresponds to the historical occurrence of hitting the green from off the fairway. Here, x is the green-in-regulation rate of a player on par-4 and par-5 holes from off the fairway, y is the group green-in-regulation rate from off the fairway for the hole, and z is the group green-in-regulation rate on par-4 and par-5 holes from off the fairway.

109. The golf tournament simulation modeling system according to any one of claims 90 to 108, wherein, The historical statistical data includes a rolling average over one or more seasons.

110. The golf tournament simulation modeling system according to any one of claims 90 to 109, wherein, The more recent historical data in the historical statistical data has a greater weight.

111. The golf tournament simulation modeling system according to any one of claims 90 to 110, wherein, Each hole is associated with multiple score probability distributions, and each score probability distribution corresponds to a specific predicted hole event result or a combination of predicted hole event results for the hole.

112. The golf tournament simulation modeling system according to claim 111, wherein, The score probability distribution represents the historical score distribution of the hole in the case of the occurrence of each potential hole event result or its combination.

113. The golf tournament simulation modeling system according to any one of claims 90 to 112, wherein, The prediction result probability generator is configured to analyze whether the prediction result appears in multiple simulations and divide the number of simulations in which the prediction result appears by the total number of simulations.

114. The golf tournament simulation modeling system according to claim 113, wherein, The one or more prediction results include: the score or score range on one or more holes in one round of the tournament, the score or score range on one or more holes in two or more rounds of the tournament, the hole events on one or more holes in one round of the tournament, the hole events on one or more holes in two or more rounds of the tournament, or a combination thereof.

115. The golf tournament simulation modeling system according to claim 113 or 114, wherein The one or more prediction results include: the specified score or the score within the specified range in one or more rounds of the tournament, the specified hole score on one or more holes in one or more rounds, or a combination thereof.

116. The golf tournament simulation modeling system according to any one of claims 113 to 115, wherein, The one or more prediction results include: the ranking of a player's finishing position by round, the player's finishing position, the range of the player's finishing position, or a combination thereof.

117. The golf tournament simulation modeling system according to any one of claims 113 to 116, wherein, The one or more prediction results include: the probability that a player finishes the game with the lowest round score, the probability that a player finishes the game with a round score within the specified finishing position ranking, or a combination thereof.

118. The golf tournament simulation modeling system according to any one of claims 113 to 117, wherein, The one or more predicted outcomes include: a player's ranking of finishing position in one or more rounds of the tournament, a player's ranking of finishing position in the tournament, a player's finishing position in one or more rounds of the tournament, a range of finishing positions in one or more rounds of the tournament, a tournament win, a promotion, a promotion line, or a combination thereof.

119. The golf tournament simulation modeling system according to any one of claims 113 to 118, wherein, The one or more predicted results include: a probability ranking of a player's finishing position in one or more rounds of the tournament, a probability ranking of a player's finishing position in the tournament, a probability of a player's finishing position in one or more rounds of the tournament, a probability of a player finishing within a range of finishing positions in one or more rounds of the tournament, a probability of a player winning the tournament, a probability of a player advancing, a probability of a qualifying line, or a combination thereof.

120. The golf tournament simulation modeling system according to any one of claims 113 to 119, wherein, The predicted result probabilities include: probability of winning, probability of entering the top 10, probability of reaching the promotion line and probability of promotion.

121. The golf tournament simulation modeling system according to any one of claims 90 to 120, wherein, The update processor is configured to replace the predicted hole score with the actual hole score when the player completes a hole-in, update the predicted round score taking into account the replaced actual hole score, add the updated predicted round scores in all tournament rounds to generate an updated predicted tournament score for the participating players, add the updated predicted round scores in the preliminary round to establish an updated promotion line, count the predicted round scores of the semi-final rounds in the scores of the players who did not qualify, and do not count the predicted round scores of the semi-final rounds in the scores of the players who did not qualify.

122. The golf tournament simulation modeling system according to any one of claims 90 to 121, wherein, The update processor is configured to perform updates at intervals of less than 30 seconds during a game as actual live score data is received.

123. The golf tournament simulation modeling system according to any one of claims 90 to 122, wherein, The update processor is configured to perform updates during the course of an actual golf event until the event ends.

124. The golf tournament simulation modeling system according to any one of claims 90 to 123, wherein, The system is also configured to transmit each player's predicted outcome probabilities to a database using player identification IDs and timestamps to display the most up-to-date probabilities, thereby allowing trends to be displayed digitally on television broadcasts and digital platforms.

125. A method of performing a golf tournament simulation using the golf tournament simulation modeling system of any one of claims 90 to 124.

126. A machine-readable medium carrying machine-readable instructions which, when executed by a processor of a machine, cause the machine to perform the system of any one of claims 90 to 124.

127. A computer-implemented method of updating a golf tournament simulation, comprising: Each tournament simulation of said golf tournament is updated by: When a player completes a hole-in, the predicted hole score is replaced with the actual hole score; updating a predicted round score to take into account the actual hole score after replacement; summing the updated predicted round scores for all players across all tournament rounds to generate updated predicted tournament scores for all players; In the preliminary round, the updated predicted round scores are added together to establish an updated promotion line, the predicted round scores of the semi-final round are counted towards the scores of the promoted players, and the predicted round scores of the semi-final round are not counted towards the scores of the non-promoted players; as well as Update the prediction result; And Update one or more prediction result probabilities according to the collectively updated prediction result, including: Analyze whether the prediction result appears in each tournament simulation; And Divide the number of simulations in which the prediction result is predicted to occur by the total number of simulations.

128. The method according to claim 125, wherein, The prediction result includes: the ranking of the player's finishing position in one or more rounds of the tournament, the ranking of the player's finishing position in the tournament, the player's finishing position in one or more rounds of the tournament, the range of finishing positions in one or more rounds of the tournament, tournament win, advancement, advancement line, or a combination thereof.

129. The method according to claim 125 or 126, wherein, The prediction result probability includes: the probability ranking of the player's finishing position in one or more rounds of the tournament, the probability ranking of the player's finishing position in the tournament, the probability of the player's finishing position in one or more rounds of the tournament, the probability of the player finishing within the range of finishing positions in one or more rounds of the tournament, the probability of the player winning the tournament, the probability of the player advancing, the advancement line probability, or a combination thereof.

130. The method according to any one of claims 125 to 127, wherein, The prediction result probability includes: the winning probability, the probability of entering the top 10, the probability of reaching the advancement line, and the advancement probability.

131. The method according to any one of claims 125 to 128, wherein, Perform the update continuously in real time during the game.

132. The method according to any one of claims 125 to 129, wherein, When receiving actual live score data, perform the update at intervals of less than 30 seconds during the game.

133. The method according to any one of claims 125 to 130, wherein, Perform the update during the actual golf event until the event ends.

134. The method according to any one of claims 125 to 131, further comprising: Use the player identification ID and timestamp to move the information of each player to the database to display the latest probability, thereby allowing trend display digitally on television broadcasts and digital platforms.

135. A system, including a processor and a storage medium storing instructions, which when executed by the processor cause the system to perform the method according to any one of claims 135 to 132.

136. A machine-readable medium carrying machine-readable instructions, which when executed by a processor of a machine cause the machine to perform the method according to any one of claims 125 to 132.

137. A method for simulating a golf tournament, including: Perform a round simulation: Generate a predicted hole score for each hole in the golf round, including: for each hole, Calculate the hole event probability of each hole event among one or more hole events assigned to a hole in the golf round; Use the event probability calculated for each hole event as a weight to generate a predicted hole event result for each hole event among the one or more hole events; Assign a score probability distribution to the hole from a plurality of score probability distributions, the score probability distribution corresponding to one or more predicted hole results generated for the hole; and Use the assigned score probability distribution to generate the predicted hole score for the hole; and Generate a predicted round score according to the predicted hole scores.

138. The method according to claim 133, wherein The hole event probability corresponds to the probability of a hole event occurring on the hole.

139. The method according to claim 133 or 134, wherein Calculating the one or more hole event probabilities is at least partially based on historical statistical data representing the historical occurrences of hole events in an actual tournament for a collective of players for multiple holes, for a collective of players for a particular simulated hole, and for individual players who have undergone the simulation for multiple holes.

140. The method according to claim 135, wherein, The historical statistical data is related to holes having hole attributes corresponding to the simulated holes.

141. The method according to claim 136, wherein, The attribute is a par value.

142. The method according to any one of claims 135 to 137, wherein The hole event outcome of the first hole event of a first hole specifies the elements required to identify the historical statistical data for use in generating the hole event probability of a second hole event of the first hole. The method according to any one of claims 132 to 138, further comprising: Calculating the hole event probability for par 4 and / or par 5 holes is greater than the hole event probability for par 3 holes.

144. The method according to any one of claims 132 to 139, wherein, The one or more hole events include a first hole event, where the first hole event includes a tee shot hitting location, and the first hole event probability includes the probability that a player's tee shot hits the hitting location.

145. The method according to claim 140, wherein, The tee shot hitting location outcome is based on the attributes of the hole.

146. The method according to claim 141, wherein, The attribute of the hole is the par rating of the hole.

147. The method according to claim 142, wherein, The first hole event probability for a par 4 hole includes the probability that a player's tee shot hits the fairway, and the first hole event probability for a par 3 hole includes the probability that a player's tee shot hits the green.

148. The method according to any one of claims 140 to 143, wherein Relative to at least one hole, the one or more hole events further include a second hole event, and the second hole event includes a hitting location of a subsequent shot.

149. The method according to claim 144, wherein, The subsequent shot hitting location outcome is based on the attributes of the hole.

150. The method according to claim 145, wherein, The attribute of the hole is the par rating of the hole.

151. The method according to claim 146, wherein, The second hole event probability for a par 4 hole includes the probability that the player hits the green from the location determined by the predicted outcome of the first hole event. The method according to any one of claims 133 to 147, further comprising: Assigning the one or more hole events to each hole, calculating a corresponding hole event probability for each hole, and generating a corresponding hole event outcome.

153. The method according to any one of claims 133 to 148, wherein, Calculating the one or more hole event probabilities includes processing historical statistical data representing the historical occurrences of hole events in an actual tournament through the following event probability model: where x is the historical incidence rate of a player performing a hole event, y is the collective historical incidence rate of hole events on a particular hole, and z is the collective historical performance of hole events during play on multiple courses.

154. The method according to claim 149, wherein, The hole event probability corresponds to the probability of a hole event occurring on the hole, and the historical statistical data is related to holes having hole attributes corresponding to the simulated holes.

155. The method according to claim 150, wherein, The first hole event probability for a par 4 hole includes the probability that a player's tee shot hits the fairway, where x is the probability that a player hits the fairway for par 4 and par 5 holes, y is the probability that the hole is collectively hit on the fairway, and z is the collective probability that par 4 and par 5 holes are hit on the fairway.

156. The method according to claim 151, wherein, The second hole event probability for the par 4 hole includes the probability that the player hits the green from the location specified by the predicted outcome of the first hole event in a subsequent shot.

157. The method according to claim 152, wherein, In the case where the predicted result of the first hole event is hitting the fairway, the historical statistics correspond to the historical occurrences of hitting the green from the fairway. x is the green-in-regulation rate of players on par-4 and par-5 holes from the fairway, y is the collective green-in-regulation rate on the hole from the fairway, and z is the collective green-in-regulation rate of par-4 and par-5 holes from the fairway; and, in the case where the predicted result of the first hole event is missing the fairway, the historical statistics correspond to the historical occurrences of hitting the green from off the fairway. x is the green-in-regulation rate of players on par-4 and par-5 holes from off the fairway, y is the collective green-in-regulation rate on the hole from off the fairway, and z is the collective green-in-regulation rate of par-4 and par-5 holes from off the fairway.

158. The method according to any one of claims 149 to 153, wherein, The probability of the first hole event for a par-3 hole includes the probability that the player's tee shot hits the green. Here, x is the green-in-regulation rate of the player on par-3 holes, y is the collective green-in-regulation rate for the hole, and z is the collective green-in-regulation rate of par-3 holes.

159. The method according to any one of claims 133 to 154, further comprising generating a predicted hole event result for each of the one or more hole events using the event probability calculated for each hole event as a weight, including: Input the calculated probability of the hole event into a weighted random generator algorithm.

160. The method according to claim 155, wherein, One or more predicted hole event results for each hole are binary.

161. The method according to any one of claims 133 to 156, wherein, Each hole is associated with multiple score probability distributions, and each score probability distribution corresponds to a specific predicted hole event result or a combination of predicted hole event results for the hole.

162. The method according to claim 157, wherein, The score probability distribution represents the historical score distribution on the hole in the case of a specific hole event occurring.

163. The method according to claim 157 or 158, wherein Assigning the score probability distribution includes: pairing the one or more predicted hole event results of the hole with the score probability distribution corresponding to the predicted hole event results.

164. The method according to any one of claims 133 to 159, wherein, Generating the predicted hole score using the assigned score probability distribution includes: inputting the assigned score probability distribution into a random score selector algorithm to generate a predicted hole score. The method according to any one of claims 133 to 160, further comprising: Apply a score adjustment to the predicted hole score.

166. The method according to claim 161, wherein, The adjustment is applied to each hole score.

167. The method according to claim 161, wherein, The adjustment is applied to the predicted round score.

168. The method according to any one of claims 161 to 164, wherein The adjustment includes a differential adjustment based on the differences of the player in actual historical matches.

169. The method according to claim 164, wherein, The differences of the player in actual historical matches are the differences relative to the average score of the tournament rounds corresponding to the simulated rounds for all tournament rounds. The method according to any one of claims 133 to 160, further comprising: Adjust the predicted hole score based on the differences between the round score means of all tournament rounds and a specific tournament round of the simulated player in the tournament.

171. The method according to any one of claims 133 to 166, further comprising: Generate multiple round simulations for the simulated player.

172. The method according to claim 167, further comprising calculating the prediction result probability of the prediction result, including: Analyze whether the prediction result appears in each round simulation; And Divide the number of round simulations in which the prediction result is predicted to appear by the total number of round simulations. The method according to claim 167, wherein, The prediction result includes one or more of the following: the score of the player on one or more holes in a round, the round score of the player, the round score range of the player, or a combination thereof.

174. The method according to any one of claims 133 to 169, wherein, The golf event includes a multi-round golf tournament, and the method further comprises performing one tournament simulation, including: performing round simulations for each round of the tournament for the player. The method according to claim 170, further comprising: Generate the predicted tournament score of the player from the tournament simulation.

176. The method according to claim 170 or 171, further comprising: Output one or more prediction results from the tournament simulation.

177. The method according to claim 172, wherein, The one or more prediction results include: one or more predicted hole scores of the player, one or more predicted round scores of the player, the predicted tournament score of the player, or a combination thereof. The method according to any one of claims 133 to 173, wherein The golf event includes a multi-round golf tournament, and the method further includes performing multiple tournament simulations, including: for each tournament simulation, performing a round simulation for each round of the tournament. The method according to claim 174, further comprising: Generating the predicted tournament score of the player based on the predicted round scores of each simulation.

180. The method according to claim 174 or 175, further includes calculating a prediction result probability of the prediction result, including: Analyzing whether the prediction result occurs in each tournament simulation; And Dividing the number of simulations in which the prediction result occurs by the total number of simulations.

181. The method according to claim 176, wherein, The prediction result includes: a specified score or a score within a specified range of the player in one or more rounds of the tournament, a specified hole score of the player on one or more holes in one or more rounds, or a combination thereof.

182. The method according to any one of claims 133 to 177, further comprising: Performing the round simulation for all players actually participating in the round of the game.

183. The method according to claim 178 further comprises: Generating the predicted round score of each player.

184. The method according to claim 178 or 179, further comprising: Outputting one or more prediction results from the tournament simulation.

185. The method according to claim 180, wherein, The one or more prediction results include: the ranking of the player by round completion position, the completion position of the player in the round, the range of the completion position of the player in the round, the player ending within a specified completion position in the round, or a combination thereof. The method according to any one of claims 133 to 181, further comprising: Performing multiple round simulations of the round for each player participating in the round of the game.

187. The method according to claim 182, further includes calculating a prediction result probability of the prediction result of the simulated round, including: Analyzing whether the prediction result occurs in each round simulation; And Dividing the number of simulations in which the prediction result is predicted to occur by the total number of simulations.

188. The method according to claim 183, wherein, The one or more prediction results include: the ranking of the player by round completion position, the completion position of the player in the round, the range of the completion position of the player in the round, the player ending within a specified completion position in the round, or a combination thereof.

189. The method according to claim 183 or 184, wherein The prediction result probability includes: the probability that the player finishes the game with the lowest round score, the probability that the player finishes the game with a round score within a specified range, or a combination thereof. The method according to any one of claims 133 to 185, wherein, The golf event includes a multi-round golf tournament, and the method further includes performing one tournament simulation, including: performing a round simulation for each round of the tournament for each player actually participating in the tournament. The method according to claim 186, further comprising: Generating a predicted tournament score for each player based on the predicted round scores. The method according to claim 187, wherein, Generating the predicted tournament score includes: performing a cut line protocol. The method according to claim 188, wherein In the case where it is predicted that the player will not advance, the predicted tournament score is limited to the predicted round score of the preliminary round. The method according to claim 188 or 189, wherein The cut line protocol includes: Performing a round simulation of the preliminary round to generate the predicted round scores of all players in each round of the preliminary round; Establishing a tournament cut line based on the predicted round scores from the preliminary round; and Performing a round simulation of the quarterfinal round for the players predicted to advance to generate the predicted round scores of the players predicted to advance in the quarterfinal round. The method according to claim 188 or 189, wherein, The cut line protocol includes: Perform round simulations for the preliminary round and the semi-final round to generate predicted round scores for all players in the preliminary round and the semi-final round; and Establish a golf tournament advancement line based on the predicted round scores from the preliminary round. The method according to any one of claims 186 to 191, further comprising: Generate one or more prediction results from the tournament simulation. The method according to claim 192, wherein The prediction results include: the ranking of a player's finishing position in one or more rounds of the tournament, the ranking of a player's finishing position in the tournament, a player's finishing position in one or more rounds of the tournament, a range of a player's finishing positions in one or more rounds of the tournament, a player's finishing position in the tournament, a range of a player's finishing positions in the tournament, the advancement line, whether a player advances, or a combination thereof.

198. The method according to any one of claims 133 to 193, wherein, The golf event includes a multi-round golf tournament, and the method further includes performing multiple tournament simulations, including: for each tournament simulation, performing a round simulation for each round of the tournament for each player actually participating in the tournament. The method according to claim 194, further comprising: Generate a predicted tournament score for each player based on the predicted round scores. The method according to claim 194 or 195, wherein The advancement line protocol includes: for each tournament simulation, Perform a round simulation for the preliminary round to generate predicted round scores for all players in each preliminary round; Establish a tournament advancement line based on the predicted round scores from the preliminary round; and Perform a round simulation for the semi-final round of the players predicted to advance to generate predicted round scores for the players predicted to advance in the semi-final round. The method according to claim 194 or 195, wherein The advancement line protocol includes: for each tournament simulation, Perform round simulations for the preliminary round and the semi-final round to generate predicted round scores for all players in the preliminary round and the semi-final round; and Establish a golf tournament advancement line based on the predicted round scores from the preliminary round.

202. The method according to any one of claims 194 to 197, further comprising calculating one or more prediction result probabilities for one or more prediction results, including: Analyzing whether the prediction result occurs in each tournament simulation; And Dividing the number of tournament simulations in which the prediction result is predicted to occur by the total number of tournament simulations. The method according to claim 198, wherein, The one or more prediction results include: the ranking of a player's finishing position in one or more rounds of the tournament, the ranking of a player's finishing position in the tournament, a player's finishing position in one or more rounds of the tournament, a range of finishing positions of one or more players in one or more rounds of the tournament, a player winning the tournament, a player advancing, the advancement line, or a combination thereof. The method according to claim 198 or 199, wherein, The one or more prediction result probabilities include: the probability ranking of a player's finishing position in one or more rounds of the tournament, the probability ranking of a player's finishing position in the tournament, the probability of a player's finishing position in one or more rounds of the tournament, the probability of a player finishing within a range of finishing positions in one or more rounds of the tournament, the probability of a player winning the tournament, the probability of a player advancing, the advancement line value, the probability of the advancement line within a value range, or a combination thereof. The method according to any one of claims 198 to 200, wherein The predicted result probabilities include: winning probability, probability of entering the top 10, probability of reaching the advancement line, and advancement probability. The method according to any one of claims 133 to 201, further comprising: Update the simulation based on the actual scores during the game of the simulated golf tournament.

207. The method according to claim 202, wherein The update includes: when actual scores occur during the game, replacing the predicted hole scores with the actual hole scores. The method according to claim 202 or 203, comprising: Update all simulations based on the actual scores during the game of the simulated golf tournament, where the update includes: When a player completes a hole, replacing the predicted hole score with the actual hole score; Updating the predicted round score considering the replaced actual hole score; Adding up the updated predicted round scores in all tournament rounds to generate an updated predicted tournament score for the participating players; Adding up the updated predicted round scores in the preliminary round to set an updated advancement line; Including the predicted round scores of the semi-final round in the scores of the non-advanced players; and Not including the predicted round scores of the semi-final round in the scores of the non-advanced players. The method according to any one of claims 202 to 204, wherein The update includes updating the prediction result. The method according to any one of claims 202 to 205, wherein The update includes updating the predicted result probabilities.

211. The method according to any one of claims 202 to 206, wherein, Perform the update continuously in real time during the game.

212. The method according to any one of claims 202 to 207, wherein When receiving actual on-site score data, perform the update at intervals of less than 30 seconds during the game.

213. The method according to any one of claims 202 to 208, wherein, Perform the update during the actual golf tournament until the tournament ends. The method according to any one of claims 133 to 209, further comprising: Use the player identification ID and timestamp to move the information of each player to the database to display the latest probabilities, thereby allowing trend display digitally on television broadcasts and digital platforms.

215. A system, including a processor and a storage medium storing instructions, which when executed by the processor cause the system to perform the method according to any one of claims 133 to 210.

216. A machine-readable medium carrying machine-readable instructions, which when executed by a processor of a machine cause the machine to perform the method according to any one of claims 133 to 210.

217. A system, including: A golf tournament simulation modeling system programmed to perform multiple simulations of a golf tournament to generate predicted results of the golf tournament, the golf tournament simulation modeling system including: A memory storing instructions; A processing unit that executes the programming operations of the golf tournament simulation modeling system; A hole event result generator programmed to use hole event probabilities as weights to generate one or more hole event results for each hole in each round of a golf tournament for the participating players, the hole event probabilities being generated at least in part by a hole event probability generator communicating with a statistical database based on historical statistical data of golf games stored in the statistical database; A hole score generator programmed to, for each participating player and hole, assign a score probability distribution based on one or more hole event results generated for the hole for the participating player, and generate a predicted hole score including a random score based on the corresponding hole score probability distribution; A prediction engine programmed to calculate the probabilities of one or more predicted results from the multiple simulations; and An update processor programmed to update one or more predicted results and / or predicted result probabilities of the multiple simulations based on actual score data during an actual golf tournament.

218. The system according to claim 213, wherein The historical statistical data represents the historical occurrences of hole events in an actual tournament for a collective of players for multiple holes, for a collective of players for a particular simulated hole, and for an individual player who has undergone the simulation for multiple holes at a particular hole.

219. The system according to claim 214, wherein, The hole event probability is based on historical statistical data related to a hole having a par value corresponding to the simulated hole. The system according to claim 213, wherein, The hole event result of the first hole event of the first hole specifies the elements required to identify the historical statistical data for generating the hole event probability of the second hole event of the first hole.

221. The system according to claim 213, wherein, The first hole event probabilities for par-4 and par-5 holes include the probability that a player's tee shot hits the fairway, and the first hole event probability for a par-3 hole includes the probability that a player's tee shot hits the green. The system according to claim 217, wherein The tee shot hole event probability uses the historical statistical data and includes: For a par-3 hole: the rate at which players on a par-3 hole reach the green, the collective rate at which players on the hole reach the green, and the collective rate at which players on par-3 holes reach the green; and For par-4 and par-5 holes: the probability that a player on a par-4 or par-5 hole hits the fairway, the collective probability that players on the hole hit the fairway, and the collective probability that players on par-4 and par-5 holes hit the fairway.

223. The system according to claim 217, wherein, The second hole event probabilities for par-4 and par-5 holes include the probability that the player hits the green from the position determined by the predicted result of the first hole event. The system according to claim 219, wherein In the case where the predicted hole event position result of the tee shot position hole event calculated for the hole is the fairway, the historical statistical data of the subsequent shot position hole event includes the historical statistical data corresponding to the historical occurrences of hitting the green from the fairway, including the rate at which players on par-4 and par-5 holes reach the green from the fairway, the collective rate at which players on the hole reach the green from the fairway, and the collective rate at which players on par-4 and par-5 holes reach the green from the fairway; and, in the case where the predicted hole event position result of the tee shot position hole event calculated for the hole is not the fairway, the historical statistical data of the subsequent shot position hole event includes the historical statistical data corresponding to the historical occurrences of hitting the green from off the fairway, including the rate at which players on par-4 and par-5 holes reach the green from off the fairway, the collective rate at which players on the hole reach the green from off the fairway, and the collective rate at which players on par-4 and par-5 holes reach the green from off the fairway.

225. The system according to claim 213, wherein, A hole event probability algorithm is employed to generate the hole event probability, wherein the hole event probability algorithm includes: where x is the historical occurrence rate of a player performing a hole event, y is the collective historical occurrence rate of hole events on a particular hole, and z is the collective historical occurrence rate of hole events during play on multiple courses.

226. The system according to claim 213, wherein, The score probability distribution represents the historical score distribution of the hole in the case of various potential hole event results or combinations of hole event results occurring for the hole.

227. The system according to claim 213, wherein The update processor is configured to: When a player completes a hole, replace the predicted hole score with the actual hole score; Update the predicted round score considering the replaced actual hole score; Sum the updated predicted round scores for all tournament rounds to generate an updated predicted tournament score for the competing player; In the preliminary round, add the updated predicted hole scores to establish an updated cut line; Include the predicted hole scores of the semi-final round in the scores of the non - advancing players; and Do not include the predicted hole scores of the semi-final round in the scores of the non - advancing players.

228. The system according to claim 213, wherein, The update processor is also programmed to transmit the prediction result probabilities of each player to a database using the player identification ID and timestamp to display the latest probabilities, thereby allowing trend display digitally on television broadcasts and digital platforms.

229. A system for updating a golf tournament simulation, comprising: An update processor programmed to perform update operations relative to a golf tournament simulation after the start of an actual golf game; A memory storing instructions; A processing unit that executes the instructions to perform the programming operations of the update processor, the operations including: Real - time update each tournament simulation of the golf tournament by: When a player completes a hole, replace the predicted hole score with the actual hole score; Update the predicted round score considering the replaced actual hole score; Generate updated predicted tournament scores for all participating players based on the updated predicted round scores for all participating players in all tournament rounds; Establish an updated cut line based on the updated predicted round scores in the preliminary round; In the updated predicted tournament scores, include the predicted round scores of the semi - final round in the scores of the advancing players and do not include the predicted round scores of the semi - final round in the scores of the non - advancing players; and Update the prediction results; and Update one or more prediction result probabilities based on the collectively updated prediction results. The system according to claim 225, wherein The one or more prediction result probabilities include: winning probability, probability of finishing in the top 10, probability of reaching the cut line, and advancement probability.

231. A method for simulating a golf event, comprising: Performing a hole - by - hole simulation for each participating player in a golf event using a golf tournament simulation modeling system, the golf tournament simulation modeling system being programmed to perform a simulation of a golf tournament, the golf tournament simulation modeling system including a memory storing instructions and a processing unit that executes the instructions to perform the programming operations of the golf tournament simulation modeling system, the operations including: Generating a predicted hole score for each hole in a golf round, including: for each hole, A hole event probability generator calculates the hole event probability for each of one or more hole events assigned to a hole in a golf round; A hole event result generator uses the event probabilities calculated for each individual hole event as weights to generate a predicted hole event result for each of the one or more hole events; A hole score generator assigns a score probability distribution from a plurality of score probability distributions to the hole, the score probability distribution corresponding to one or more predicted hole results generated for the hole; and The hole score generator uses the assigned score probability distribution to generate the predicted hole score for the hole; and A prediction engine generates a predicted round score based on the predicted hole scores. The method according to claim 227, wherein Calculating the probability of the one or more hole events is at least partially based on historical statistical data, which represents the historical occurrences of hole events in an actual tournament for a collective of players for multiple holes, for a collective of players for a specific simulated hole, and for individual players who have undergone the simulation for multiple holes. The method according to claim 227, wherein, Calculating the probability of the one or more hole events includes: a scoring distribution engine processing historical statistical data representing the historical occurrences of hole events in an actual tournament through the following event probability model: where x is the historical incidence rate of a player having a hole event, y is the collective historical incidence rate of hole events on a specific hole, and z is the collective historical performance of hole events during play on multiple courses. The method according to claim 229, wherein, The probability of the hole event corresponds to the probability of a hole event occurring on the hole, and the historical statistical data is related to a hole having hole attributes corresponding to the simulated hole. The method according to claim 230, wherein, The first hole event probability for a par-4 hole includes the probability that a player's tee shot hits the fairway, where x is the probability that players on par-4 and par-5 holes hit the fairway, y is the probability that the collective hits the fairway for the hole, and z is the collective probability that par-4 and par-5 holes hit the fairway.

236. The method according to claim 231, wherein, The second hole event probability for the par-4 hole includes the probability that a player hits the green on a subsequent shot from a position specified by the prediction result of the first hole event. The method according to claim 232, wherein, In the case where the prediction result of the first hole event is hitting the fairway, the historical statistical data corresponds to the historical occurrences of hitting the green from the fairway, x is the green-in-regulation rate of players on par-4 and par-5 holes from the fairway, y is the collective green-in-regulation rate on the hole from the fairway, and z is the collective green-in-regulation rate of par-4 and par-5 holes from the fairway; and in the case where the prediction result of the first hole event is missing the fairway, the historical statistical data corresponds to the historical occurrences of hitting the green from off the fairway, x is the green-in-regulation rate of players on par-4 and par-5 holes from off the fairway, y is the collective green-in-regulation rate on the hole from off the fairway, and z is the collective green-in-regulation rate of par-4 and par-5 holes from off the fairway. The method according to claim 227, wherein, Using the event probabilities calculated for each hole event as weights to generate a predicted hole event result for each hole event in the one or more hole events, includes: inputting the calculated probability of the hole event into a weighted random generator algorithm. The method according to claim 227, wherein, Each hole is associated with multiple score probability distributions, and each score probability distribution corresponds to a specific predicted hole event result or a combination of predicted hole event results for the hole.

240. The method according to claim 23, wherein The score probability distribution represents the historical score distribution on the hole in the case of a specific hole event occurring.

241. The method according to claim 23, wherein, Assigning the score probability distribution includes: pairing the one or more predicted hole event results of the hole with the score probability distribution corresponding to the predicted hole event result.

242. The method according to claim 227, wherein, Using the assigned score probability distribution to generate the predicted hole score includes: inputting the assigned score probability distribution into a random score selector algorithm to generate a predicted hole score. The method according to claim 227, further comprising: A modification engine applies a score adjustment to the predicted hole score. The method according to claim 227, wherein, The adjustment is applied to each hole score. The method according to claim 227, further comprising: The modification engine adjusts the predicted hole score based on the difference between the round score means of all tournament rounds and a specific tournament round of the simulated player in the tournament.

246. A method of a golf game that uses a system as described in any one of claims 213 to 224 to simulate a golf tournament.

247. A machine-readable medium carrying machine-readable instructions that, when executed by a processor of a machine, cause the machine to execute a system as described in any one of claims 213 to 224.

248. A method of a golf game that uses a system as described in claim 225 or 226 to simulate a golf tournament.

249. A machine-readable medium carrying machine-readable instructions that, when executed by a processor of a machine, cause the machine to execute a system as described in claim 225 or 226.

250. A system comprising a processor and a storage medium storing instructions that, when executed by the processor, cause the system to execute a method as described in any one of claims 227 to 241.

251. A machine-readable medium carrying machine-readable instructions that, when executed by a processor of a machine, cause the machine to execute a method as described in any one of claims 227 to 241.

252. A method of a golf game that uses a system as described in any one of claims 1 to 12 to simulate a golf tournament.

253. A machine-readable medium carrying machine-readable instructions that, when executed by a processor of a machine, cause the machine to execute a system as described in any one of claims 1 to 12.

254. A method of a golf game that uses a system as described in claim 13 or 14 to simulate a golf tournament.

255. A machine-readable medium carrying machine-readable instructions that, when executed by a processor of a machine, cause the machine to execute a system as described in claim 13 or 14.

256. A system comprising a processor and a storage medium storing instructions that, when executed by the processor, cause the system to execute a method as described in any one of claims 15 to 29.

257. A machine-readable medium carrying machine-readable instructions that, when executed by a processor of a machine, cause the machine to execute a method as described in any one of claims 15 to 29.

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