Spatial influence determination method and device and storage medium

Abstract

The invention provides a spatial influence determination method and device and a storage medium. The method comprises the following steps: acquiring a soft control probability that players in a team control a first area on a court and a passing success rate that a ball is transmitted to other players in the team; the first area is any area obtained by dividing the court; based on the soft control probability and the no-ball score probability of the player for scoring from the first area within the preset time period, the threat probability of the player for the opponent team in the first area is determined; based on the instantaneous ball control probability, the soft control probability, the ball passing success rate and the threat probability of the player, determining the regional space influence of the player in the first region; and determining the first space influence of the players in the court based on the regional space influence of the players in different first regions of the court.

Description

Technical Field

[0001] This application relates to data processing and analysis techniques, and more particularly to a method, apparatus, and storage medium for determining spatial influence. Background Technology

[0002] In the field of sports data analysis, especially in the analysis of tactics and player performance in football matches, it is necessary to review and analyze football matches. However, in a match, the formation and positioning often cannot actually reflect the players' activity areas.

[0003] In existing technologies, players' activity space is generally reflected by combining individual game data with running heatmaps. However, there is a lack of judgment on the actual spatial impact of players during the game. Summary of the Invention

[0004] This application provides a method, device, and storage medium for determining spatial influence.

[0005] The technical solution of this application embodiment is implemented as follows: This application provides a method for determining spatial influence, the method including: The algorithm obtains the soft control probability of a player controlling the first area of ​​the field and the pass success rate of passing the ball to other players in the team; the first area is any area obtained by dividing the field. Based on the probability of soft control and the probability of a player creating an off-the-ball goal from the first zone within a preset time period, the probability of a player posing a threat to the opposing team in the first zone is determined. The player's spatial influence in the first zone is determined based on the player's instantaneous ball possession probability, soft control probability, passing success rate, and threat probability. The player's primary spatial influence on the field is determined based on the spatial influence of the player in different primary zones of the field.

[0006] The method for determining spatial influence also includes: determining the team's total spatial influence in the first area based on the regional spatial influence of different players in the first area; determining the team's second spatial influence on the field based on the team's total spatial influence in different areas; the spatial size affected by the second spatial influence is not less than the spatial size affected by the first spatial influence.

[0007] In the above method for determining spatial influence, obtaining the soft control probability of a player controlling the first area on the field includes: obtaining the interception time and control time of the player controlling the first area, and determining the total control time of the player controlling the first area based on the interception time and control time; determining the player's advantage time relative to the fastest opponent based on the fastest control time of the opponent's player in the first area and the player's total control time; and converting the advantage time into the player's soft control probability of the first area.

[0008] In the aforementioned method for determining spatial influence, the player's regional spatial influence in the first area is determined based on the player's instantaneous ball possession probability, soft control probability, passing success rate, and threatening probability. This includes: determining the player's on-the-ball spatial influence in the first area based on the player's instantaneous ball possession probability, soft control probability, and passing success rate; determining the non-instantaneous ball possession probability based on the instantaneous ball possession probability, and determining the player's off-the-ball spatial influence in the first area based on the non-instantaneous ball possession probability and threatening probability; and determining the regional spatial influence based on the player's on-the-ball and off-the-ball spatial influence in the first area.

[0009] In the above method for determining spatial influence, the team's second spatial influence on the field is determined based on the team's total spatial influence in different areas. This includes: determining the team's actual spatial influence in different areas by multiplying the team's total spatial influence in different areas by the pre-set regional weights; and determining the second spatial influence based on the team's actual spatial influence in different areas.

[0010] The method for determining the spatial influence mentioned above further includes: determining that the first area meets the controllable condition in response to the highest soft control probability of a player in the team being greater than a preset control probability threshold; determining that the first area has tactical value conditions in response to the maximum passing success rate or maximum threat probability of a player in the team being greater than a preset threshold; and determining that the first area is the dynamic space of the team in response to the first area meeting the controllable condition and having tactical value conditions.

[0011] The method for determining the spatial influence mentioned above also includes: constructing a passing success rate matrix corresponding to the team's passing network based on the passing success rate of players in the team passing the ball to other players in the team, and determining the team's passing connectivity based on the passing success rate matrix; determining the edge volatility of the passing network and the route redundancy between different areas based on the passing success rate matrix; and determining the health of the passing network based on the passing connectivity, edge volatility, and route redundancy.

[0012] The method for determining spatial influence also includes: determining the team's predicted passing connectivity and predicted spatial influence within a preset time period; determining the team's influence decline value based on the predicted spatial influence and spatial influence; and determining the team's corresponding collapse risk based on the predicted passing connectivity and influence decline value.

[0013] This application provides a device for determining spatial influence, comprising: The acquisition module is used to acquire the soft control probability of players in the team controlling the first area of ​​the field, and the pass success rate of passing the ball to other players in the team; the first area is any area obtained by dividing the field; The determination module is used to determine the probability of a player threatening the opposing team in the first zone based on the probability of soft control and the probability of a player creating an off-the-ball goal from the first zone within a preset time period. The determination module is also used to determine a player's spatial influence in the first zone based on the player's instantaneous ball possession probability, soft control probability, passing success rate, and threat probability. The determination module is also used to determine a player's first spatial influence on the field based on the player's regional spatial influence in different first zones of the field.

[0014] This application provides a device for determining spatial influence, the device comprising: Memory is used to store executable instructions or computer programs. When a processor executes computer-executable instructions or computer programs stored in memory, it implements the method for determining spatial influence provided in the embodiments of this application.

[0015] This application provides a computer-readable storage medium storing a computer program or computer-executable instructions, which, when executed by a processor, implements the method for determining spatial influence provided in this application.

[0016] This application provides a computer program product, including a computer program or computer executable instructions. When the computer program or computer executable instructions are executed by a processor, the method for determining spatial influence provided in this application is implemented.

[0017] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit the technical solutions provided in the embodiments of this application. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort, wherein: Figure 1 This is a flowchart illustrating a method for determining spatial influence provided in an embodiment of this application; Figure 2 This is an exemplary flowchart of determining the influence of a second space provided in an embodiment of this application. Figure 1 ; Figure 3 This is an exemplary flowchart of determining soft control probability provided in an embodiment of this application; Figure 4 This is a schematic diagram illustrating an exemplary process for determining regional spatial influence, provided in an embodiment of this application. Figure 5 This is an exemplary flowchart of determining the influence of a second space provided in an embodiment of this application. Figure 2 ; Figure 6 This is an exemplary flowchart illustrating the process of determining the dynamic space of a team, provided in an embodiment of this application. Figure 7 This is a schematic diagram of an exemplary process for determining health status provided in an embodiment of this application; Figure 8 This is an exemplary flowchart illustrating the process of determining crash risk, provided in an embodiment of this application. Figure 9 This is a schematic diagram of the structure of the spatial influence determination device provided in the embodiments of this application; Figure 10 This is a schematic diagram of the structure of the spatial influence determination device provided in the embodiments of this application. Detailed Implementation

[0019] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It is understood that the specific embodiments described herein are merely for explaining the relevant application and not for limiting the application. All other embodiments obtained by those skilled in the art without inventive effort are within the scope of protection of this application.

[0020] In the following description, references to "some embodiments" refer to a subset of all possible embodiments. However, it is understood that "some embodiments" may be the same or different subsets of all possible embodiments and may be combined with each other without conflict. Unless otherwise defined, all technical and scientific terms used in the embodiments of this application have the same meaning as commonly understood by one of ordinary skill in the art to which the embodiments of this application pertain. The terminology used in the embodiments of this application is for the purpose of describing the embodiments of this application only and is not intended to limit the application. It should also be noted that, for ease of description, only the parts relevant to the application are shown in the accompanying drawings.

[0021] This application provides a method for determining spatial influence, such as... Figure 1 As shown, it includes the following steps: Step S101: Obtain the soft control probability of a player in the team controlling the first area on the field, and the passing success rate of passing the ball to other players in the team; the first area is any area obtained by dividing the field.

[0022] In the embodiments of this application, the method for determining spatial influence can be implemented by a device for determining spatial influence. The device for determining spatial influence is a device with the function of determining spatial influence. For example, the device for determining spatial influence can be an electronic device such as a tablet computer, a laptop computer, a handheld computer, a personal digital assistant (PDA), a desktop computer, a server, a cloud computing platform, or a smart terminal. No specific electronic device is limited here.

[0023] In the embodiments of this application, the spatial influence determination device can divide the sports field into several grid units according to preset rules. Each grid cell This represents a primary area. For example, the spatial influence determination device will be used to determine the field. Divided into sixteen regions twelve regions Or other numbers of areas, or, according to the area of ​​the court. For example, dividing the area into offensive zone, forward zone, etc.

[0024] In the embodiments of this application, the team Chinese players For a certain first region Soft control probability It refers to a player on a team relative to an opponent's player. In a certain first region The advantage in control within the pass. This advantage can be achieved through the physical interception time of the pass. With control time The total control time formed by the sum of these The probability value, obtained by measuring and transforming the data through a logic function, represents the likelihood of a player controlling a certain first zone within the team.

[0025] In the embodiments of this application, the passing success rate of passing the ball to other players in the team is... Passing success rate refers to the probability that a player in a team will successfully pass the ball to another player in the team at a certain moment. It reflects the passing ability and connectivity of the team's players in a certain first zone.

[0026] In the embodiments of this application, the spatial influence determination device can use match data (such as player positions, passing paths, touch frequency, ball line geometry, receiver movement and opponent interception physical characteristics parameterization, etc.) to calculate the soft control probability of any player in the team in the first area, as well as the passing success rate, using an algorithm model.

[0027] Step S102: Based on the soft control probability and the probability that a player will create a goal from the first zone without the ball within a preset time period, determine the probability of a player threatening the opposing team in the first zone.

[0028] In the embodiments of this application, the probability of scoring without the ball... This refers to a player within a specific first zone on a team, within a predetermined time window. The potential for creating a goal-scoring opportunity within the first zone. It also defines the potential threat a player poses after establishing control of the zone without the ball. The preset time period can be three minutes, five minutes, or other time periods. For example, the preset time period can be set based on actual needs and application scenarios, and this application does not limit this.

[0029] In the embodiments of this application, the probability of scoring without the ball can be obtained by statistically analyzing the historical performance of a player in the team, such as whether he created a shooting opportunity or a scoring opportunity. Of course, it can also be predicted based on the current game video. If it is a prediction, the probability of scoring without the ball is a value obtained by model analysis based on historical event sequence data.

[0030] In the embodiments of this application, threat probability It is an important indicator for measuring the degree of threat a player poses to the opponent in the first zone. For example, the probability of threat is determined by formula (1): (1); in, For players In time First area The corresponding probability of scoring without the ball, For players In time First area The corresponding soft control probability, For players In time First area The corresponding threat probability.

[0031] Step S103: Based on the player's instantaneous ball control probability, soft control probability, passing success rate, and threat probability, determine the player's regional spatial influence in the first area.

[0032] In the embodiments of this application, the instantaneous ball control probability of a single player It can be pre-set or pre-stored, so it can be retrieved directly. Alternatively, it can be based on the ball's distance, the last touch, and the instantaneous ball control probability estimated by the player.

[0033] In the embodiments of this application, after obtaining the player's instantaneous ball control probability Soft control probability Passing success rate and the probability of threat This allows for the integration of on-the-ball and off-the-ball channels to determine a player's spatial influence in the first area. .

[0034] In the embodiments of this application, regional spatial influence is a comprehensive evaluation of a player's overall influence within a specific first area of ​​the team. Regional spatial influence is composed of both on-the-ball spatial influence and off-the-ball spatial influence. On-the-ball spatial influence mainly reflects the performance of players in possession of the ball, including the stability of ball control and the accuracy of passing; while off-the-ball spatial influence reflects the contribution of players to the offensive threat by choosing their positions and attracting defensive attention when not in possession of the ball.

[0035] In the embodiments of this application, the spatial influence determination device can input the above four parameters (instantaneous ball possession probability, soft control probability, passing success rate, and threat probability) into an influence calculation model. The influence calculation model will calculate and determine the spatial influence of players in the first area of ​​the team. By comprehensively considering multiple parameters, the influence calculation model can more comprehensively evaluate the actual role of players in the first area of ​​the team.

[0036] Step S104: Determine the player's first spatial influence on the field based on the player's regional spatial influence in different first zones of the field.

[0037] In the embodiments of this application, first spatial influence refers to the overall spatial influence of players across the entire court. First spatial influence is a global indicator derived by weighted summation of the spatial influence of players in each first zone. This indicator reflects not only the performance of players in each first zone but also their overall influence throughout the entire game.

[0038] For example, the method for determining the first space influence is shown in formula (2): (2); in, For players In time The primary spatial influence of the entire stadium area at that time. The weight of the first region, For players First area Its regional spatial influence.

[0039] For example, if the team Chinese players If a player has a higher spatial influence in the left flank of the attacking third and a lower influence in the midfield, then the team's primary spatial influence may be biased towards the attacking side. Similarly, another team... Chinese players The manner in which spatial influence is exerted in each first region is also determined by formula (2). for , .

[0040] In the embodiments of this application, different weights are assigned according to the importance of different first regions. For example, the weight of offensive zones may be higher than that of defensive zones, thus more reasonably reflecting the overall performance of the players on the team. Furthermore, the weighting coefficients can be dynamically adjusted according to different stages of the game to adapt to changes in the game's pace.

[0041] Thus, the model constructed by the method of determining spatial influence can not only quantify the influence of players in different first zones of the team, but also comprehensively derive the overall spatial influence of the model constructed by the method of determining spatial influence on the entire field, thereby more comprehensively measuring the tactical performance and spatial control ability of players and their teams in the game.

[0042] In some embodiments, such as Figure 2 As shown, the device for determining spatial influence can also perform the following steps S201 and S202: Step S201: Determine the team's total spatial influence in the first area based on the spatial influence of different players in the team in the first area.

[0043] In the embodiments of this application, after determining the spatial influence of each player in each first area on the court, the spatial influence device can select the player with the greatest influence in that first area as the team's spatial influence in the first area.

[0044] For example, if the team consists of 11 players, and player 8 has the highest spatial influence in the first area 1, then player 8 is taken as the total spatial influence of the first area.

[0045] For example, the method for determining the team's total spatial influence in the first area based on the regional spatial influence of different players in the team is shown in formula (3): (3); in, For the team In time First area The corresponding total spatial influence.

[0046] In the embodiments of this application, the maximum spatial influence of a player in the first area is taken as the total spatial influence of the team in the corresponding first area. This can also indicate which player controls the first area, and the position of that player can be given priority when making strategic deployments. At the same time, the player with the greatest spatial influence in each area can also be obtained.

[0047] In embodiments of this application, the total spatial influence can also be the overall team influence value obtained by summing the regional spatial influence of all players within the same area. In this way, the total spatial influence not only considers individual player performance but also reflects the effectiveness of teamwork and overall strategy. For example, within the offensive third, if multiple offensive players simultaneously possess high regional spatial influence, the total spatial influence of a particular team in the offensive third will significantly increase, meaning that the team has strong control and offensive threat within the offensive third.

[0048] Step S202: Based on the team's total spatial influence in different areas, determine the team's second spatial influence on the field; the spatial size affected by the second spatial influence shall not be less than the spatial size affected by the first spatial influence.

[0049] In the embodiments of this application, the second spatial influence refers to a summary evaluation of the spatial control of the entire game at a higher level. The second spatial influence is a global indicator derived by integrating and weighting the total spatial influence of multiple first areas. The second spatial influence is used to measure the team's sustained control of key areas throughout the game and its impact on the game's outcome.

[0050] For example, the method for determining the team's influence in the second space of the field is shown in formula (4): (4); in, For the team In time The secondary space influence corresponding to the entire stadium at that time.

[0051] In the embodiments of this application, the spatial size affected by the second spatial influence is no less than that affected by the first spatial influence. One is the spatial influence of a single player on the field, and the other is the spatial influence of the entire team on the field. The second spatial influence not only covers the local influence of a single area, but also reflects the overall influence formed by a team's interaction across multiple areas. For example, a team may have a high first spatial influence on the attacking third at a certain moment, but if a team cannot establish effective control in the midfield area, it may affect the final value of the second spatial influence, thereby exposing the shortcomings of a team's tactical system.

[0052] In the embodiments of this application, by introducing the second spatial influence, the team's spatial control ability in the game can be evaluated more systematically, and the gap between the team's strategic intentions and actual execution at different stages can be revealed. The method of introducing the second spatial influence makes up for the shortcomings of traditional statistical methods, making football tactical analysis more scientific, data-driven and visualized.

[0053] In some embodiments, such as Figure 3 As shown, when the spatial influence determination device performs the step S102 above, "obtaining the soft control probability of players in the team controlling the first area on the field", it can perform the following steps S301 to S303: Step S301: Obtain the interception time and control time of the player controlling the first area, and determine the total control time of the player controlling the first area based on the interception time and control time.

[0054] In the embodiments of this application, Time to Intercept (TTI) refers to the length of time a defending player can successfully intercept the opponent's possession of the ball. TTI reflects the defending player's ability to defend key defensive areas; that is, when an opponent attempts to enter a key defensive area, the defending player can react and intercept in the shortest possible time. The shorter the TTI, the stronger the defending player's control over the key defensive area.

[0055] In the embodiments of this application, Time to Control (TTC) refers to the time a player maintains stable ball control within the first area. The shorter the player's control time, the higher their ball control ability within the first area.

[0056] In the embodiments of this application, Total Time of Control (TTR) is the sum of interception time and control time. Total Time of Control is used to comprehensively measure a player's overall control ability in the first zone. The smaller the TTR value, the stronger the player's control ability in the first zone.

[0057] For example, the method for determining the player's total control time in the first zone is shown in formula (5): (5); in, For players In time First area Corresponding pair of balls Total control time For players In time First area Corresponding pair of balls Interception time, For players In time First area Corresponding pair of balls Control time, The location of the ball.

[0058] Step S302: Based on the fastest control time of the opponent's player in the first zone and the player's total control time, determine the player's advantage time relative to the fastest opponent.

[0059] In the embodiments of this application, the spatial influence determination device can obtain the fastest control time among the opposing players in the first area, and then determine the player's advantage time relative to the fastest opponent based on the fastest control time and the player's total control time.

[0060] In an embodiment of this application, the opposing team has 11 players, and the fastest control time is the total control time of the player with the shortest total control time among these 11 players.

[0061] For example, the method for determining a player's advantage time relative to the fastest opponent is shown in formula (6): (6); in, For players opposing team In time First area The player with the shortest total control time is selected based on their total control time.

[0062] Step S303: Convert the advantage time into the player's soft control probability in the first zone.

[0063] In the embodiments of this application, soft control probability (Soft Control Probability) Soft control probability is a probabilistic expression used to quantify a player's actual control ability in a certain area. The calculation of soft control probability typically uses a logistic function (such as the sigmoid function) to map the advantage time to the [0,1] interval, representing the degree of soft control a player has in a specific area.

[0064] See formula (7) for an example conversion formula: (7); in, It is the Sigmoid function. These are adjustment parameters used to adjust the steepness of the curve; they can be adjusted according to actual needs. (Through...) The nonlinear transformation method it represents can convert absolute values ​​into intuitive probability values, which facilitates subsequent visualization and tactical decision-making.

[0065] For example, when When positive, it indicates that the player's control time over the area is better than that of the opposing team's fastest player to complete the control action. A value close to 1 indicates that the player has almost complete control of the area; conversely, if... If it is negative, then A value close to 0 indicates that the player has a weaker ability to control the area.

[0066] Thus, by converting advantageous time into soft control probability, a continuous and interpretable quantitative indicator can be provided for dynamically assessing a player's actual impact on space at different stages of the game. Compared to traditional binary judgments (such as control / no control), the method of converting advantageous time into soft control probability is closer to the complex situations in actual combat, and helps improve the accuracy and practicality of data analysis.

[0067] In some embodiments, when the spatial influence determination device performs step S103 above, such as Figure 4 As shown, the following steps S401 to S403 can also be performed: Step S401: Based on the player's instantaneous ball control probability, soft control probability, and passing success rate, determine the player's influence in the ball space corresponding to the first area.

[0068] In the embodiments of this application, instantaneous ball control probability The instantaneous possession probability refers to the probability that a player in a football match will actually control the ball at a given moment. This probability is typically determined by factors such as the player's distance from the ball, their body orientation, their last touch, and role estimation. For example, in a football match, if a player is running and away from the ball, their instantaneous possession probability is lower; conversely, if the player is approaching the ball and preparing to receive it, their instantaneous possession probability is higher.

[0069] In the embodiments of this application, the instantaneous ball control probability is combined Soft control probability and passing accuracy It can assess the spatial influence of a player in possession of the ball in the target analysis. An exemplary implementation can be found in formula (8): (8); in, For players In time First area The corresponding impact of space on the ball.

[0070] Step S402: Based on the instantaneous ball possession probability, determine the non-instantaneous ball possession probability, and based on the non-instantaneous ball possession probability and the threat probability, determine the player's off-ball space influence in the first area.

[0071] In the embodiments of this application, the sum of the instantaneous ball control probability and the non-instantaneous ball control probability is 1. Therefore, knowing the instantaneous ball control probability allows us to know the non-instantaneous ball control probability. .

[0072] In the embodiments of this application, the product of the non-instantaneous ball control probability and the threat probability is determined as the player's influence in the off-ball space corresponding to the first area. An exemplary implementation method is shown in formula (9): (9); in, For players In time First area The corresponding influence in the off-ball space.

[0073] Step S403: Determine the area space influence based on the player's influence in the ball space and the influence in the non-ball space in the first area.

[0074] In the embodiments of this application, zonal spatial influence is the final comprehensive evaluation index used to describe a player's overall impact on the game within a specific area. Zonal spatial influence is obtained by weighted summation of on-the-ball spatial influence and off-the-ball spatial influence. For example, a player with high zonal spatial influence in the attacking third indicates that the player can effectively control the ball in the attacking third and create threats through off-the-ball movement, thus significantly influencing the game's outcome in that area.

[0075] In the embodiments of this application, the spatial influence determination device determines the regional spatial influence based on the player's spatial influence with and without the ball in the first area. Here, the weighting of the spatial influence with and without the ball is 1. An exemplary implementation is shown in formula (10): (10); in, For regional spatial influence.

[0076] In the embodiments of this application, the calculation method for regional spatial influence can be adjusted according to specific application scenarios. Of course, in tactical systems that emphasize ball possession, the weight of the influence of space with the ball can be appropriately increased; while in tactical systems that focus on counter-attacks, the weight of the influence of space without the ball can be increased.

[0077] In this way, by comprehensively considering the spatial influence of both on and off the ball, the actual role of players in the game can be reflected more fully, and the system can help the coaching team to formulate more reasonable tactical arrangements.

[0078] In some embodiments, when the spatial influence determining device performs step S202 above, such as Figure 5 As shown, the following steps S501 and S502 can also be performed: Step S501: The product of the team's total spatial influence in different areas and the pre-set regional weights is determined as the team's actual spatial influence in different areas.

[0079] In the embodiments of this application, the region weight This refers to numerical coefficients assigned based on the importance of different areas on the field to the tactical value of the game. For example, areas near the opponent's goal (such as the penalty area) pose a greater attacking threat, so these areas may have higher weights; areas near the sidelines may have lower weights unless these areas involve quick counter-attacks or crossing opportunities. Of course, area weights can also focus on the spatial influence of the striker's position, assigning higher weights to areas involved in the striker's position and lower weights to other areas. This is a fixed-weight algorithm. Area weights can also be dynamically adjusted based on historical data, expert evaluation, or machine learning models.

[0080] In the embodiments of this application, actual spatial influence refers to an indicator that reflects the team's substantial impact on the game within a specific area, obtained by multiplying the total spatial influence by the regional weight. Actual spatial influence not only considers the size of the player's range of movement but also incorporates the tactical importance of the specific area, thereby more accurately measuring the team's control and influence in key positions.

[0081] For example, the actual spatial influence of a team in different areas can be determined by formula (11): (11); in, For the team In time The second spatial influence corresponding to the first region z In the embodiments of this application, there is a close relationship between regional weight and actual spatial influence. As an adjustment factor, regional weight determines whether the spatial influence of a certain region is amplified or weakened, thereby enabling the actual spatial influence to more realistically reflect the strategic significance of that region in the game.

[0082] Step S502: Determine the second spatial influence based on the team's actual spatial influence in different areas.

[0083] In the embodiments of this application, the second spatial influence refers to a quantitative indicator of the team's overall control over the field space and its tactical influence throughout the entire match, derived by comprehensively considering the actual spatial influence of each area. The second spatial influence is an assessment of the team's overall performance and can be used to compare the tactical execution effectiveness between different stages of the match and different opponents.

[0084] For example, the method for determining the team's influence in the second space of the field is shown in formula (12): (12); in, For the team In time The second spatial influence of the entire stadium is given here. The weight of each area is increased here. The weight of each first area in the above formula (4) is 1.

[0085] In the embodiments of this application, the team is used. The formulaic discussion, of course, applies to the opposing team. The method for determining these is consistent and will not be elaborated upon here.

[0086] In some embodiments, such as Figure 6 As shown, the device for determining spatial influence can also perform the following steps S601 to S603: Step S601: In response to the highest soft control probability of a player in the team being greater than a preset control probability threshold, determine that the first region meets the controllable condition.

[0087] In the embodiments of this application, the preset control probability threshold is a value set based on actual training data or competition experience, used to distinguish areas with a control advantage from areas without a significant control advantage. It can be 0.9, 0.5, 0.6, or other probability thresholds. For example, if the preset control probability threshold is 0.8, when the soft control probability exceeds 0.8, the spatial influence determination device determines that the first area corresponding to the soft control probability is within the control range of a certain team.

[0088] In the embodiments of this application, by comparing the player's highest soft control probability in the first area with a preset control probability threshold, it can be determined whether the first area belongs to the space that the team can control. If the highest soft control probability is higher than the preset control probability threshold, the first area is considered to meet the controllability condition; if the highest soft control probability is higher than the preset control probability threshold, the first area is considered not to meet the controllability condition.

[0089] For example, the method for determining whether the first region meets the controllable condition is shown in formula (13): (13); in, For and the relationship, This is a preset control probability threshold.

[0090] In the embodiments of this application, by introducing soft control probability and a preset control probability threshold, a quantitative judgment is achieved on whether a certain area on the field is controlled by the team. By introducing soft control probability and a preset control probability threshold, the areas where the team holds the initiative during the game can be accurately identified, thereby providing the coaching team with more targeted tactical suggestions.

[0091] Step S602: In response to the fact that the maximum passing success rate or the maximum threat probability of the players in the team is greater than a preset threshold, determine that the first area has tactical value conditions.

[0092] In embodiments of this application, a preset threshold can be a value set based on training data or expert experience to determine whether a first area has tactical value. For example, if the preset threshold is 0.7, and the pass success rate or threat probability exceeds 0.7, then the first area is considered to have high tactical value.

[0093] For example, the method for determining whether the first region has tactical value can be found in formula (14): (14); in, , As weight, This is a preset threshold.

[0094] In the embodiments of this application, by comparing the player's maximum passing success rate or maximum threat probability in the first area with a preset threshold, it can be determined whether the first area has tactical value. If one of the indicators (maximum passing success rate or maximum threat probability) exceeds the preset threshold, the first area is considered to have tactical value; if one of the indicators does not exceed the preset threshold, the first area is considered not to have tactical value.

[0095] Step S603: In response to the first area satisfying the controllable condition and the first area having tactical value condition, the first area is determined as the team's dynamic space.

[0096] In the embodiments of this application, dynamic space refers to the area that simultaneously satisfies both controllability and tactical value conditions. That is, a first area is only considered the team's dynamic space if it is both controlled by the team and has a high pass success rate or threatening probability.

[0097] For example, the method for determining whether the first region is the team's dynamic space is shown in formula (15): (15); in, Let's determine whether the first region z of team T at time t is a dynamic space. If it is 1, then it is a dynamic space; otherwise, it is a static space.

[0098] In the embodiments of this application, this dual-condition setting ensures that the dynamic space not only reflects the team's actual control over the space, but also embodies the tactical importance of the first zone in the game. Based on this dual-condition setting, the space where the team truly has an impact during the game can be located more accurately.

[0099] In this way, by introducing multi-dimensional indicators such as soft control probability, passing success rate, and threat probability, and setting corresponding preset thresholds for judgment, the dynamic space of the target team can be accurately identified. This allows for a comprehensive assessment of the target team's spatial control ability and tactical influence in the game, providing more accurate data support for the coaching team and further improving the overall technical and tactical level of the target team.

[0100] In some embodiments, such as Figure 7 As shown, the device for determining spatial influence can also perform the following steps S701 to S703: Step S701: Based on the passing success rate of players in the team passing the ball to other players in the team, construct the passing success rate matrix corresponding to the passing network of the team, and determine the passing connectivity of the team based on the passing success rate matrix.

[0101] In the embodiments of this application, the passing success rate matrix is ​​a mathematical representation used to quantify passing behavior within a team. The elements of this matrix represent the probability of a successful pass between two players. This matrix is ​​calculated by statistically analyzing actual passing data between players. For example, using passing events from historical matches as input, an N×N matrix (where N is the number of players on the field) is constructed, where Aij represents the success rate of a pass from player i to player j. After constructing the passing success rate matrix, connectivity algorithms in graph theory, such as spectral clustering and minimum spanning trees, are used to evaluate the passing connectivity of the entire passing network, or the eigenvalues ​​of the passing success rate matrix are used to determine the corresponding connectivity.

[0102] For example, the pass success rate matrix is ​​shown in formula (16): (16); in, For pass completion rate, passing network The corresponding pass success rate matrix can be found in formula (17): (17); in, .

[0103] In the embodiments of this application, eigenvalues This is determined to be the team's passing connectivity.

[0104] In the embodiments of this application, passing connectivity refers to the ability of nodes (players) in a passing network to connect with each other through a series of passing paths. High passing connectivity means that the corresponding team has good passing fluidity in the game, can quickly organize attacks, and maintain possession advantage. Conversely, low passing connectivity may indicate that the corresponding team's passing structure is unclear, making it easy for the opponent to cut off the connection, resulting in the obstruction of the attack. Therefore, the assessment of passing connectivity is of great significance for tactical analysis.

[0105] In the embodiments of this application, by constructing a passing success rate matrix and analyzing the passing connectivity of the passing success rate matrix, the stability and flexibility of the team's passing structure can be objectively reflected, thereby providing coaches with a scientific basis to optimize tactical arrangements and improve the team's overall cooperation efficiency.

[0106] Step S702: Based on the passing success rate matrix, determine the edge volatility of the passing network and the route redundancy between different areas.

[0107] In the embodiments of this application, edge volatility refers to the degree of fluctuation in the success rate of passing between any pair of players in a passing network over time. Edge volatility reflects the stability of passing relationships. If the success rate of passing between a pair of players fluctuates significantly, it indicates that the cooperation between the two pairs of players is unstable or uncertain, and may be affected by factors such as defensive pressure and player condition. Edge volatility can be measured by calculating the standard deviation of the time series of passing success rates; the larger the value, the more drastic the fluctuation.

[0108] For example, the implementation of edge volatility can be found in formula (18): (18); in, W is the mean, and W is the time window. Let be the marginal volatility.

[0109] In the embodiments of this application, route redundancy This refers to the existence of multiple feasible passing paths between players in a passing network. High route redundancy indicates that the teams involved in the passing network can flexibly choose different passing routes when facing interceptions, thus avoiding being limited by a single strategy. Conversely, low route redundancy may lead to overly concentrated passing routes among the teams involved in the passing network, making them easier for opponents to disrupt.

[0110] In the embodiments of this application, the dynamic characteristics of the passing network can be further refined by calculating edge volatility and route redundancy. This method helps coaches identify potential risk points and areas for improvement, and enhances the team's adaptability in complex game environments.

[0111] Step S703: Determine the health of the passing network based on passing connectivity, edge volatility, and route redundancy.

[0112] In the embodiments of this application, the health of the passing network is a comprehensive evaluation index used to measure the stability, reliability, and sustainability of the entire passing system. The health of the passing network comprehensively considers information from three dimensions: passing connectivity, side volatility, and route redundancy. A higher health value indicates a more stable and efficient passing network, and stronger ball control and offensive organization capabilities for the team during the game.

[0113] For example, the method for determining the health of the passing network is shown in formula (19): (19); in, For the health of the passing network, , , As weight.

[0114] In the embodiments of this application, by constructing a health model of the passing network, the coaching team can be provided with intuitive decision support, which can help the coaching team evaluate the effectiveness of the current tactics and carry out targeted training or personnel adjustments for weak links, thereby improving the team's overall competitive level.

[0115] Thus, by constructing a passing success rate matrix and analyzing its passing connectivity, edge volatility, and route redundancy, the health of the passing network can be determined. This allows for a comprehensive evaluation of the target team's passing performance during the match, identifying key passing bottlenecks and potential risks, thereby optimizing tactical arrangements and improving the target team's tactical execution and win rate.

[0116] In some embodiments, such as Figure 8 As shown, the device for determining spatial influence can also perform the following steps S801 to S803: Step S801: Determine the team's predicted passing connectivity and predicted spatial influence within a preset time period.

[0117] In embodiments of this application, predicting pass connectivity Passing connectivity refers to the strength and stability of the passing network among players within a team over a given time period. Predicted passing connectivity reflects a team's ability to efficiently pass the ball during tactical execution and can assess the connectivity of the entire passing network structure within a preset time period. The calculation of predicted passing connectivity typically combines historical match data and the current match status for modeling; for example, Markov chain models or dynamic graph neural networks are used to simulate and predict passing behavior.

[0118] In the embodiments of this application, spatial influence is predicted. Predicted spatial influence refers to the comprehensive reflection of a team's potential control and threat level over various grid units on the field within a preset time period. It measures the team's dynamic control over space within a given timeframe, encompassing not only physical ball possession advantages (such as interception time and control time) but also tactical spatial impact (such as passing hub value and off-the-ball scoring opportunities). For example, predicted spatial influence can be constructed by integrating data from multiple dimensions, including instantaneous ball possession tendency, player accessibility, passing probability, and off-the-ball scoring opportunities, to create a unified influence core. This core can then be used to assess the team's actual influence on the field space within a preset time period.

[0119] In the embodiments of this application, by quantifying the above two indicators, a more comprehensive understanding of the team's tactical performance and spatial control ability over a period of time can be obtained, thereby providing a basis for subsequent risk assessment.

[0120] Step S802: Based on the predicted spatial influence and spatial influence, determine the team's influence decline value.

[0121] In the embodiments of this application, the influence decline value refers to the difference between a team's current spatial influence in an actual match and the team's predicted spatial influence over a preset time period. The influence decline value measures the fluctuation in a team's performance during a game, particularly when the team is affected by factors such as opponent countermeasures, player injuries, and tactical adjustments, and whether the team's control of space significantly decreases. The influence decline value can be calculated using methods such as the difference method, the relative deviation method, or the normalized error method, depending on the design requirements of the evaluation model.

[0122] In the embodiments of this application, when the difference between the predicted spatial influence and the actual spatial influence increases, it indicates that the team's level in the game is gradually declining.

[0123] Step S803: Based on the predicted pass connectivity and the impact decline value, determine the corresponding collapse risk of the team.

[0124] In the embodiments of this application, collapse risk refers to the probability that a team may lose control of the game in a short period of time. Specific manifestations of this risk include a broken passing network, a sharp drop in spatial influence, and the suppression of key players. To assess this risk, two key factors are primarily relied upon: first, predicted passing connectivity, and second, the decline in influence. Predicted passing connectivity reflects the team's passing efficiency and network stability under ideal conditions. The decline in influence reveals the degree of performance degradation of the team in actual match play.

[0125] For example, the method for determining the collapse risk of a team is shown in formula (20): (20); in, For time, , For threshold, Risk of collapse.

[0126] In embodiments of this application, the calculation of collapse risk can also employ a multidimensional regression model or a classifier model. Input variables include predicted pass connectivity, influence decline value, and other auxiliary parameters (such as player substitutions, number of red and yellow cards, match phase, etc.). The output is the probability that the team will collapse in the next time period. To improve the accuracy of the model, time series analysis methods can also be introduced to retrospectively analyze the team's historical performance to identify potential collapse patterns.

[0127] In the embodiments of this application, by combining predicted passing connectivity and influence decline values, a team's collapse risk score can be dynamically generated, and different early warning mechanisms can be triggered based on the score level. For example, when the collapse risk exceeds a set threshold, the coaching team can be prompted to take emergency measures, such as adjusting the formation, replacing players, or changing the tactical style.

[0128] Therefore, by introducing new indicators such as predicted passing connectivity, predicted spatial impact, and impact decline value, and combining them to determine the team's risk of collapse, a more comprehensive assessment of the team's dynamic performance in a match can be achieved. This improves the accuracy and real-time nature of tactical analysis, thereby providing the coaching team with more targeted guidance and effectively enhancing the team's overall competitive level.

[0129] This application provides a method for determining spatial influence. The method includes: obtaining the soft control probability of a player controlling a first area on the field and the passing success rate of passing the ball to other players in the team; the first area is any area divided by the field; based on the soft control probability and the probability of a player creating a goal from the first area within a preset time period, determining the player's threat probability against the opponent team in the first area; based on the player's instantaneous ball control probability, soft control probability, passing success rate, and threat probability, determining the player's regional spatial influence in the first area; based on the player's regional spatial influence in different first areas of the field, determining the player's first spatial influence on the field. The method for determining spatial influence provided by this application firstly quantifies the player's actual influence on a certain area by comprehensively considering the soft control probability, passing success rate, and off-the-ball scoring probability, thereby more comprehensively evaluating the player's tactical role in the game; secondly, by combining the instantaneous ball control probability, the regional spatial influence not only reflects static control ability but also dynamic game participation; finally, by aggregating the spatial influence of multiple areas, the overall spatial influence of the player across the entire field is obtained, overcoming the problem that traditional formation analysis and heat maps cannot accurately reflect the player's actual influence space.

[0130] This application provides a spatial influence determination device 9, the device comprising: The acquisition module 91 is used to acquire the soft control probability of a player in the team controlling the first area on the field, and the passing success rate of passing the ball to other players in the team; the first area is any area obtained by dividing the field; Module 92 is used to determine the probability of a player threatening the opposing team in the first zone based on the probability of soft control and the probability of a player creating an off-the-ball goal from the first zone within a preset time period. The determination module 92 is also used to determine the player's spatial influence in the first area based on the player's instantaneous ball possession probability, soft control probability, passing success rate, and threat probability. Module 92 is also used to determine a player's first spatial influence on the field based on the player's regional spatial influence in different first zones of the field.

[0131] In one embodiment of this application, the determining module 92 is further configured to determine the team's total spatial influence in the first area based on the regional spatial influence of different players in the first area; and to determine the team's second spatial influence on the field based on the team's total spatial influence in different areas; the spatial size affected by the second spatial influence is not less than the spatial size affected by the first spatial influence.

[0132] In one embodiment of this application, the acquisition module 91 is further configured to acquire the interception time and control time of the player controlling the first area, and determine the total control time of the player controlling the first area based on the interception time and control time; determine the player's advantage time relative to the fastest opponent based on the fastest control time of the opponent player in the opposing team and the player's total control time; and convert the advantage time into the player's soft control probability of the first area.

[0133] In one embodiment of this application, the determining module 92 is further configured to determine the player's influence in the ball space corresponding to the first area based on the player's instantaneous ball control probability, soft control probability, and passing success rate; determine the non-instantaneous ball control probability based on the instantaneous ball control probability, and determine the player's influence in the non-ball space corresponding to the first area based on the non-instantaneous ball control probability and threat probability; and determine the area space influence based on the player's influence in the ball space and non-ball space influence in the first area.

[0134] In one embodiment of this application, the determining module 92 is further configured to determine the team's actual spatial influence in different regions by multiplying the team's total spatial influence in different regions by a pre-set regional weight; and to determine the second spatial influence based on the team's actual spatial influence in different regions.

[0135] In one embodiment of this application, the determining module 92 is further configured to determine that the first area meets the controllable condition in response to the highest soft control probability of a player in the team being greater than a preset control probability threshold; determine that the first area has tactical value conditions in response to the maximum passing success rate or maximum threat probability of a player in the team being greater than a preset threshold; and determine that the first area is the dynamic space of the team in response to the first area meeting the controllable condition and the first area having tactical value conditions.

[0136] In one embodiment of this application, the determining module 92 is further configured to construct a passing success rate matrix corresponding to the passing network of the team based on the passing success rate of players in the team passing the ball to other players in the team, and determine the passing connectivity of the team based on the passing success rate matrix; determine the edge volatility of the passing network and the route redundancy between different areas based on the passing success rate matrix; and determine the health of the passing network based on the passing connectivity, edge volatility, and route redundancy.

[0137] In one embodiment of this application, the determining module 92 is further configured to determine the team's predicted passing connectivity and predicted spatial influence within a preset time period; determine the team's influence decline value based on the predicted spatial influence and spatial influence; and determine the team's corresponding collapse risk based on the predicted passing connectivity and influence decline value.

[0138] This application provides a spatial influence determination device 10, comprising: Memory 101 is used to store computer-executable instructions or computer programs; The processor 102 is used to implement the above-mentioned method for determining spatial influence when executing computer-executable instructions or computer programs stored in the memory 101.

[0139] This application provides a computer-readable storage medium storing one or more computer programs that can be executed by one or more processors to implement the aforementioned method for determining spatial influence. The computer-readable storage medium can be transient or non-transient.

[0140] This application provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program. When the computer program is read and executed by a computer, it implements some or all of the steps in the method for determining spatial influence described above. This computer program product can be implemented specifically through hardware, software, or a combination thereof. In one optional embodiment, the computer program product is specifically embodied as a computer storage medium; in another optional embodiment, the computer program product is specifically embodied as a software product, such as a software development kit (SDK), etc. In some embodiments, the storage medium may be a computer-readable storage medium, which may be volatile memory, such as random-access memory (RAM); or non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), solid-state drive (SSD), ferromagnetic random access memory (FRAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), flash memory, magnetic surface memory, optical disk, or compact disk-read-only memory (CD-ROM); or it may be various devices including one or any combination of the above-mentioned memories, such as mobile phones, computers, tablet devices, personal digital assistants, etc. Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of hardware embodiments, software embodiments, or embodiments combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0141] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1A device that provides the functions specified in one or more boxes.

[0142] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0143] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0144] In some embodiments, executable instructions may take the form of a program, software, software module, script, or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may be deployed in any form, including as a standalone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.

[0145] As an example, executable instructions may, but do not necessarily, correspond to files in a file system. They may be stored as part of a file containing other programs or data, for example, in one or more scripts within a Hyper Text Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple co-located files (e.g., files storing one or more modules, subroutines, or code sections). As an example, executable instructions may be deployed to execute on a single computing device, or on multiple computing devices located in one location, or on multiple computing devices distributed across multiple locations and interconnected via a communication network. The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, and improvements made within the spirit and scope of this application are included within the scope of protection of this application. It should be understood that the phrase "one embodiment" or "an embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. It should be understood that in the various embodiments of this application, the sequence numbers of the above-described processes do not imply a sequential order of execution; the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application. The sequence numbers of the above-described embodiments are merely descriptive and do not represent the superiority or inferiority of the embodiments. It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components may be combined, or integrated into another system, or some features may be ignored or not performed. The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, and improvements made within the spirit and scope of this application are included within the scope of protection of this application.

Claims

1. A method for determining spatial influence, the method comprising: The probability of a player controlling the first zone of the field and the pass success rate of passing the ball to other players in the team are obtained. The first region is any region obtained by dividing the court; Based on the soft control probability and the probability that the player creates an off-the-ball goal from the first area within a preset time period, the probability of the player posing a threat to the opposing team in the first area is determined. Based on the player's instantaneous ball possession probability, soft control probability, passing success rate, and threat probability, the player's regional spatial influence in the first area is determined; The player's first spatial influence on the court is determined based on the player's regional spatial influence in different first zones of the court.

2. The method for determining spatial influence according to claim 1, further comprising: Based on the regional spatial influence of different players in the team in the first area, determine the team's total spatial influence in the first area; Based on the team's total spatial influence in different areas, the team's second spatial influence in the stadium is determined. The size of the space affected by the second spatial influence is no less than the size of the space affected by the first spatial influence.

3. The method for determining spatial influence according to claim 1, wherein obtaining the soft control probability of a player in a team controlling the first area on the field includes: The interception time and control time of the player in the first area are obtained, and the total control time of the player in the first area is determined based on the interception time and the control time. Based on the fastest control time of an opponent player in the opposing team of the team in the first area, and the player's total control time, the player's advantage time relative to the fastest opponent is determined; The advantage time is converted into the player's soft control probability for the first area.

4. The method for determining spatial influence according to claim 1, wherein determining the player's regional spatial influence in the first area based on the player's instantaneous ball control probability, soft control probability, passing success rate, and threat probability includes: Based on the player's instantaneous ball control probability, soft control probability, and passing success rate, the player's influence in the ball-handling space corresponding to the first area is determined; Based on the instantaneous ball possession probability, the non-instantaneous ball possession probability is determined, and based on the non-instantaneous ball possession probability and the threat probability, the off-the-ball space influence of the player in the first area is determined. The spatial influence of the area is determined based on the player's influence in the ball space and the influence in the non-ball space within the first area.

5. The method for determining spatial influence according to claim 2, wherein determining the team's second spatial influence in the stadium based on the team's total spatial influence in different areas includes: The product of the team's total spatial influence in different regions and the pre-set regional weights is determined as the team's actual spatial influence in different regions. The second spatial influence is determined based on the team's actual spatial influence in different regions.

6. The method for determining spatial influence according to any one of claims 1 to 5, the method further comprising: In response to the highest soft control probability of a player in the team being greater than a preset control probability threshold, it is determined that the first region meets the controllable condition; In response to the fact that the maximum pass success rate or maximum threat probability of the players in the team is greater than a preset threshold, it is determined that the first area has tactical value. In response to the first region satisfying the controllable conditions and the first region possessing the tactical value conditions, the first region is determined to be the dynamic space of the team.

7. The method for determining spatial influence according to any one of claims 1 to 5, the method further comprising: Based on the passing success rate of players in the team passing the ball to other players in the team, a passing success rate matrix corresponding to the passing network of the team is constructed, and the passing connectivity of the team is determined based on the passing success rate matrix; Based on the passing success rate matrix, the edge volatility of the passing network and the route redundancy between different regions are determined. The health of the passing network is determined based on the passing connectivity, the edge volatility, and the route redundancy.

8. The method for determining spatial influence according to claim 7, further comprising: Determine the team's predicted pass connectivity and predicted spatial influence within the preset time period; Based on the predicted spatial influence and the spatial influence, the influence reduction value of the team is determined; Based on the predicted pass connectivity and the decrease in influence, the collapse risk corresponding to the team is determined.

9. A device for determining spatial influence, comprising: Memory is used to store executable instructions or computer programs. A processor, when executing computer-executable instructions or computer programs stored in the memory, implements the method for determining spatial influence as described in any one of claims 1 to 8.

10. A computer-readable storage medium storing a computer program or computer-executable instructions for implementing, when executed by a processor, the method for determining spatial influence as described in any one of claims 1 to 8.

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