Athlete evaluation system

Abstract

Provided is an athlete evaluation system that can generate various evaluation data for an athlete on the basis of muscle measurement data for the athlete and also present the evaluation data to an evaluator. The athlete evaluation system includes: a muscle measurement data acquisition unit for acquiring muscle measurement data for an athlete; an evaluation data generation unit for generating evaluation data for the athlete on the basis of the measurement data acquired by the muscle measurement data acquisition unit; and an evaluation data presentation unit for presenting the evaluation data generated by the evaluation data generation unit to an evaluator.

Description

Athlete Evaluation System

[0001] The present invention relates to an athlete evaluation system.

[0002] As a conventional technique, a body information processing program that presents a user's biometric information in real time has been proposed (see, for example, Patent Document 1).

[0003] The body information processing program disclosed in Patent Document 1 acquires biometric data from athletes and performs real-time analysis and processing on the acquired data using a certain algorithm / AI. As a result of the analysis, for example, stress, muscle fatigue, etc. are displayed in real time. Furthermore, a doctor can examine the condition of athletes and recommend suspension of activities. In addition, the monitored and analyzed data can also be utilized for improving the skills and records of athletes.

[0004] International Publication No. 2021 / 221140

[0005] However, according to the above-described body information processing program, although it displays the stress, muscle fatigue, etc. of athletes in real time, it measures skin temperature and energy consumption using a temperature sensor and also takes into account the heart rate and respiratory rate to measure muscle fatigue. Therefore, the problem is that what is presented is the overall muscle fatigue of the athlete and does not consider the fatigue of each part of the body. An athlete's performance cannot necessarily be measured only by overall muscle fatigue, and more comprehensive analysis is required.

[0006] The inventors of the present invention have repeatedly studied in view of the above problems, and found that an athlete evaluation system including a muscle measurement data acquisition unit that acquires measurement data of an athlete's muscles, an evaluation data generation unit that generates evaluation data of the athlete based on the measurement data acquired by the muscle measurement data acquisition unit, and an evaluation data presentation unit that presents the evaluation data generated by the evaluation data generation unit to an evaluator contributes to the solution of the above problems. The present invention has been completed based on these findings.

[0007] The present invention relates to an athlete evaluation system, characterized by comprising: a muscle measurement data acquisition unit that acquires measurement data of an athlete's muscles; an evaluation data generation unit that generates evaluation data of the athlete based on the measurement data acquired by the muscle measurement data acquisition unit; and an evaluation data presentation unit that presents the evaluation data generated by the evaluation data generation unit to an evaluator. The evaluation data generation unit preferably has a risk evaluation engine that outputs an injury risk index of the athlete based on the measurement data, and generates evaluation data that includes at least the injury risk index as an element. The risk evaluation engine preferably outputs the injury risk index of the athlete based on the bias of the muscle response obtained from the measurement data. Preferably, the muscle measurement data acquisition unit measures the same muscle of the athlete multiple times, and the risk evaluation engine outputs the injury risk index of the athlete based on the hierarchical relationship of the muscle obtained from the multiple measurements. The evaluation data generation unit preferably has an asset value estimation module that outputs the asset value of the athlete based on both athlete profile data, which includes at least one selected from the group consisting of the athlete's physical information, trainer intervention information, training information, performance information, and economic information, and market information of the athlete market, and the athlete's injury risk index, and generates the evaluation data which includes at least the asset value as an element. The evaluation data generation unit preferably generates the evaluation data which includes the trainer's contribution based on both athlete profile data, which includes at least the athlete's past injury risk index and the treatment history the athlete has received from trainers, and the athlete's injury risk index. The evaluation data presentation unit preferably has a user interface which customizes the evaluation data presented according to the authority granted to the evaluator.Preferably, the evaluation data generation unit generates evaluation data including recommended measures to reduce the athlete's injury risk index, and the evaluation data presentation unit is customized to present the recommended measures to at least one of the athlete and the trainer. Preferably, the evaluation data generation unit generates evaluation data including the athlete's condition, and the evaluation data presentation unit is customized to present the athlete's condition to the coach. Preferably, the evaluation data generation unit generates evaluation data including a list of the condition of each athlete belonging to the team, and the evaluation data presentation unit is customized to present the list of conditions to the coach. Preferably, the evaluation data generation unit generates evaluation data including the athlete's economic value based on the athlete's asset value, and the evaluation data presentation unit is customized to present the athlete's economic value to at least one of the manager and a third party. Preferably, the evaluation data generation unit generates evaluation data including the sum of the economic values ​​of each athlete belonging to the team, and the evaluation data presentation unit is customized to present the sum of the economic values ​​to at least one of the manager and a third party.

[0008] The present invention provides an athlete evaluation system that generates various evaluation data of an athlete based on muscle measurement data and can further present said evaluation data to the evaluator.

[0009] An explanatory diagram showing the configuration of one embodiment of the athlete evaluation system of the present invention. A block diagram showing the configuration of the athlete evaluation system of the present invention. A block diagram showing an example of the configuration of the processing device according to the embodiment. A diagram showing an example of the configuration of muscle measurement data. A diagram showing an example of the configuration of muscle response information. A diagram showing an example of the configuration of muscle response information. A block diagram showing an example of the configuration of the athlete evaluation system of the present invention. A schematic diagram showing an example of a UI screen displayed on the display unit of the terminal. A schematic diagram showing an example of a UI screen displayed on the display unit of the terminal. A schematic diagram showing an example of a UI screen displayed on the display unit of the terminal. A schematic diagram showing an example of a UI screen displayed on the display unit of the terminal.

[0010] The present invention will be described in further detail. Unless otherwise specified, the numerical range "X to Y" represents a range from X or greater to Y or less, including both values ​​at both ends. Furthermore, when a numerical range is indicated, the upper and lower limits may be combined as appropriate, and the resulting numerical range is also disclosed. In addition, the same reference numeral is used for identical elements in the drawing description, and redundant explanations are omitted. Also, the dimensional ratios in the drawings are exaggerated for explanatory purposes and may differ from the actual ratios.

[0011] In this invention, "athlete" means a competitor in various sports, regardless of whether the sport is an individual or team sport. Regardless of whether the sport is an individual or team sport, the athlete may belong to a team, and the team may be managed by an individual or legal entity. In this invention, "evaluator" means an individual, legal entity, organization, or department selected from a group consisting of athletes, trainers, coaches, managers, and third parties. The trainers include training staff, medical staff, and analytics staff both inside and outside the team. The coaches include the team's manager and coaches. The managers include the team's owner, general manager, and organizational department, as well as officers of the team operator. The third parties include scouts from other teams, athletes other than those being evaluated under this invention, commentators, fans, sports organizations, individuals who have already provided loans or investments to the team operator, and individuals who are considering providing loans or investments to the team operator in the future.

[0012] One embodiment of the athlete evaluation system of the present invention will be described in more detail with reference to the attached drawings.

[0013] (Configuration of the athlete evaluation system) Figure 1 is a schematic diagram showing an example of the configuration of the athlete evaluation system according to the embodiment.

[0014] The athlete evaluation system of the present invention includes a muscle measurement data acquisition unit that acquires measurement data of an athlete's muscles.

[0015] The athlete evaluation system is configured such that a muscle measurement data acquisition unit 2 and a terminal 3 are connected wirelessly or via a wired connection, and a processing unit 1 and the terminal 3 are connected to each other via a network 4. The muscle measurement data acquisition unit 2 is operated, for example, by a trainer 6 (lower right diagram in Figure 1) and measures information regarding the condition of muscles in various parts of the athlete 5 being measured (information regarding the condition of other parts of the body such as fat and bone may be measured simultaneously), but it may also be operated by the athlete 5 themselves (upper right diagram in Figure 1). The terminal 3 may be operated by the trainer 6 operating the muscle measurement data acquisition unit 2, or it may be operated by the athlete 5 operating the muscle measurement data acquisition unit 2 themselves.

[0016] The processing unit 1 is a server-type information processing device that operates in response to requests from the terminal 3, and is equipped with electronic components such as a CPU (Central Processing Unit) and flash memory that have functions for processing information. Furthermore, the functions of the processing unit 1 may be realized through a cloud service.

[0017] The muscle measurement data acquisition unit 2 is, for example, a muscle flexibility measuring device that presses an indenter against various parts of the athlete 5 by operating an actuator, and outputs data showing the relationship between the reaction force and displacement acting on the indenter as measurement data. The measurement data is plotted on a logarithmic scale graph, and multiple straight lines are fitted to the plotted graph to be used as information for deriving an index for the stiffness of each of the multiple layers (skin, fat, muscle, etc.) of each part. The index for stiffness corresponding to the muscle layer is treated as muscle response information. Furthermore, the measurement data may be output multiple times by repeating the measurement multiple times, with the period from pressing the indenter until the measurement data is output being considered one measurement. For example, by changing the force and timing of pressing the indenter in each of the multiple measurements, measurement data suggesting the hysteresis of the muscle can be obtained through a series of multiple measurements. The hysteresis is, for example, hysteresis inherent to muscle. A single measurement may not be able to fully measure the state of the muscle that shows signs of fatigue or injury that have not yet manifested. By changing the measurement pattern of the multiple measurements, taking the aforementioned hysteresis into consideration, it is possible to elicit muscle conditions that show signs of fatigue or injury that have not yet manifested. In order to measure the hysteresis, the measurement pattern for the next cycle may be changed in real time based on feedback from the measurement results of the multiple measurement cycles. Alternatively, a standardized measurement pattern for accessing the hysteresis of muscles may be prepared in advance, and the measurement pattern may be changed by referring to this standardized measurement pattern. The standardized measurement pattern may be prepared individually according to age, gender, physical information, the type of sport of the athlete 5, etc. Furthermore, the muscle measurement data acquisition unit 2 may be equipped with a display unit such as a display and display instructions for the measurement site and measurement method according to the athlete's age, gender, physical information, the type of sport of the athlete 5, etc. It is not necessary for the muscle measurement data acquisition unit 2 to have such a display unit; the display unit of the terminal 3 may display instructions for the measurement site and measurement method.Furthermore, the muscle measurement data acquisition unit 2 is not limited to the muscle flexibility measurement device; any device capable of acquiring information indicating the state of the muscles, such as an electromyography device or a device that measures bioelectrical impedance by passing a weak electric current through the body, may also be used.

[0018] The terminal 3 is an information processing device such as a PC (Personal Computer), tablet terminal, or smartphone, and is equipped with electronic components such as a CPU and flash memory that have functions for processing information within the main body.

[0019] The aforementioned network 4 is a communication network capable of high-speed communication, and is, for example, a wired or wireless communication network such as the Internet or a LAN (Local Area Network).

[0020] As an example, the processing device 1 receives the measurement data obtained by the muscle measurement data acquisition unit 2 via the terminal 3, converts the measurement data into muscle response information for each part in response to a request from the terminal 3, evaluates the risk of injury or accidents based on the muscle response information for each part, and displays the results on the terminal 3. More specifically, it evaluates the risk according to the bias in muscle response (for example, a bias between the left and right sides) obtained from the measurement data. This assumes that the probability of various accidents increases when there is a bias in the stiffness of the left and right muscles, such as when the other muscle is subjected to a greater burden than usual in an attempt to compensate for one muscle that is fatigued, leading to injury, or when there is a greater difference in fatigue between the left and right muscles than the athlete 5 is aware of, making it difficult to move as intended and increasing the risk of falling. The trainer 6 and the athlete 5 check the information displayed on the terminal 3 and use it as one item to indicate the performance of the athlete 5. Furthermore, imbalances in muscles and bones can exist even in situations where the risk is low due to factors such as dominant leg or arm. Therefore, it is desirable to establish individualized evaluation criteria rather than simply considering the presence of an imbalance as a risk.

[0021] Figure 2 is a block diagram showing the configuration of the athlete evaluation system of the present invention.

[0022] The measurement data 111 obtained by the muscle measurement data acquisition unit 2 is used by the evaluation data generation unit 10A of the processing unit 1 to evaluate, for example, the athlete's injury risk, and evaluation data 114 is generated. The evaluation data 114 is presented to each evaluator via the evaluation data presentation unit 10B of the processing unit 1.

[0023] (Configuration of the processing apparatus) Figure 3 is a block diagram showing an example of the configuration of the processing apparatus 1 according to the embodiment.

[0024] The processing unit 1 comprises a control unit 10, which is composed of a CPU and the like, controls each part and executes various programs; a storage unit 11, which is composed of a storage medium such as flash memory and stores information; and a communication unit 12, which communicates with the outside via a network.

[0025] The control unit 10, by executing the information processing program 110 described later, functions as the evaluation data generation unit 10A, which includes the measurement data acquisition means 100, the muscle response calculation means 101, the risk assessment engine 102, and the asset value estimation module 103, as well as the evaluation data presentation unit 10B, etc.

[0026] The measurement data acquisition means 100 acquires the measurement data from the muscle measurement data acquisition unit 2 via the communication unit 12 and stores it in the storage unit 11 as measurement data 111.

[0027] The muscle response calculation means 101 fits the measurement data 111 of a certain area onto a logarithmic scale graph to form multiple straight lines, and derives indices for the stiffness of multiple layers in that area based on the slope of each straight line. Based on the property that muscles lose flexibility and become stiff when fatigued, an index (Gn) for the stiffness of the layer corresponding to the muscle layer is stored in the storage unit 11 as muscle response information 112. In addition to the Gn (nonlinear modulus of elasticity) of the layer corresponding to the muscle layer, the linear modulus of elasticity G, viscosity coefficient r, and delayed response φ of the layer may also be stored as indices in the storage unit 11 as muscle response information 112.

[0028] The risk assessment engine 102 obtains the muscle response of each part of the athlete 5 from the muscle response information 112, calculates the bias in the muscle response, for example, the left-right ratio of each part, evaluates the risk of the left-right ratio based on the risk assessment criteria information 113, and outputs an injury risk index. The injury risk index is stored in the storage unit 11 as evaluation data 114. Note that the bias in the muscle response is not limited to the left-right ratio of each part, but any combination can be used, such as the front-to-back ratio, the up-and-down ratio, the ratio of the left front to the right back, etc. Furthermore, biases in the distribution of multiple parts may be used in addition to the ratio of two values. Furthermore, biases at different times for the same part may be used. Furthermore, it may be extended not only to the ratio of each part of an individual, but also to the bias in the muscle response in the formation of multiple athletes (the ratio of muscle responses of two positions or the bias in the overall distribution of muscle responses). Note that the risk assessment engine 102 can output the injury risk index from any muscle response, regardless of the bias in the muscle response.

[0029] Here, the risk assessment criteria information 113 may, for example, set a predetermined threshold as a risk assessment criterion, and the risk assessment engine 102 may probabilistically generate the risk of injury by comparing the left-right ratio with the threshold. In this case, the threshold may be common to all athletes, or different values ​​may be set for each athlete. The threshold may also be set according to characteristics such as being right-handed or left-handed. Furthermore, the threshold may be a predetermined value, or it may be updated based on the history of the left-right ratio of the athlete 5, or it can be set from various perspectives. For example, the threshold of the risk assessment criteria information 113 is determined based on the perspective of the athlete 5 themselves (their subjective performance evaluation, match results, etc.). In other words, the threshold is determined by the bias when the athlete 5 subjectively feels that they are performing at a certain level and the bias when they feel that they are not performing at a certain level. Furthermore, the threshold may be determined not only from the perspective of the athlete 5 himself, but also from the perspective of the coach (objective performance evaluation), the perspective of the manager (objective performance evaluation), data acquired from a wearable device worn by the athlete 5 (bias in tilt and acceleration data obtained from a gyro sensor), data acquired from motion capture (for example, based on balance measured in the off-season), video analysis (performance and balance of the athlete 5 obtained through image processing and video processing), force measurement data using force plates, etc. (for example, based on balance measured in the off-season), statistical methods (for example, analysis using sabermetrics), machine learning, and combinations thereof. These methods may be used when setting the threshold based on bias at a certain point in time, or when setting the threshold based on the history of bias over a certain period.

[0030] When outputting the injury risk index, it is not necessary to evaluate all of the obtained muscle response information 112 equally. A weighted probability evaluation may be performed, such as increasing the weight of the measurement data 111 that has a high correlation with the risk of injury and decreasing the weight of the measurement data 111 that has a low correlation with the risk of injury. For example, a probability evaluation may be performed by increasing the weight of the measurement data 111 at a predetermined time after a match or practice. The evaluation data generation unit 10A may apply weighting to the measurement data 111 based on measurement timing or measurement conditions, such as before, during, or after a match or practice, and calculate an index indicating the muscle state of the athlete 5 based on the weighting.

[0031] The asset value estimation module 103 outputs the asset value of the athlete 5 based on both the injury risk index and the athlete profile data described later.

[0032] The evaluation data presentation unit 10B processes information to be displayed on the display unit of the terminal 3 according to the operation of the evaluation data generation unit 10A. Furthermore, if the risk evaluation engine 102 expands the concept of bias, the method for displaying the expanded bias will also be expanded accordingly.

[0033] Furthermore, the evaluation data generation unit 10A may consist of multiple individual evaluation data generation units for each evaluator, and the evaluation data presentation unit 10B may present the evaluation data 114. For example, an athlete evaluation data generation unit, a trainer evaluation data generation unit, a coach evaluation data generation unit, a manager evaluation data generation unit, and a third-party evaluation data generation unit may each cause the evaluation data presentation unit 10B to present the evaluation data 114. Conversely, one evaluation data generation unit 10A may generate all the evaluation data 114 for each evaluator, and the evaluation data presentation unit 10B may have a customized user interface (UI) for the evaluation data 114 presented according to the authority granted to each evaluator.

[0034] The storage unit 11 stores information processing programs 110 that cause the control unit 10 to operate as the means 100-103 and 10B described above, measurement data 111, muscle response information 112, risk assessment criteria information 113, evaluation data 114, etc.

[0035] (Operation of the processing device) Next, the operation of this embodiment will be described.

[0036] First, the trainer 6 operates the muscle measurement data acquisition unit 2 to measure information about the muscles in each part of the athlete 5.

[0037] The muscle measurement data acquisition unit 2 is, for example, a muscle flexibility measuring device, which presses an indenter against each part of the athlete 5 by operating an actuator, and outputs data showing the relationship between the reaction force and displacement acting on the indenter as muscle measurement data.

[0038] The measurement data output by the muscle measurement data acquisition unit 2 is transmitted to the processing unit 1 via the terminal 3 and the network 4. However, if the muscle measurement data acquisition unit 2 has a communication function, it may be transmitted directly to the processing unit 1 without going through the terminal 3.

[0039] Next, the measurement data acquisition means 100 of the processing device 1 acquires measurement data from the muscle measurement data acquisition unit 2 via the communication unit 12 and stores it in the storage unit 11 as measurement data 111.

[0040] Figure 4 shows an example of the configuration of the measurement data 111.

[0041] The measurement data 111a is information managed for each athlete, and has an athlete name for identifying the athlete, a measurement date, a part name for identifying a part of the athlete's body, and the displacement and reaction force measured by the muscle measurement data acquisition unit 2. The unit of displacement is, for example, mm, and the unit of reaction force is, for example, N, but units of the same dimension may be used. The actually measured value is input in the "reaction force" column. In the measurement date column, in addition to the date format and / or information in the date format, time information in relation to activities such as practice and competition of the athlete, such as "before practice", "during practice", "after practice", "n hours after practice", "before competition", "during competition", "after competition", or "n hours after competition", or text format information indicating the situation at the time of measurement may be included.

[0042] Next, the muscle response calculation means 101 fits a plurality of straight lines on a graph in a logarithmic scale for the measurement data 111 of the muscle of a certain part, calculates an index for the hardness of the layer corresponding to the muscle in a certain part based on the slope of the straight line corresponding to the muscle layer, and stores the index in the storage unit 11 as the muscle response information 112.

[0043] FIG. 5 is a diagram showing a configuration example of the muscle response information 112.

[0044] The muscle response information 112a is information indicating the response of the muscle calculated from the measurement data 111a, and has an athlete name, a part name, the measurement date when the measurement data 111a was measured, and Gn which is a numerical value indicating the response of the muscle. Note that Gn is an index for the hardness of the layer corresponding to the muscle layer as described above.

[0045] FIG. 6 is a diagram showing a configuration example of the muscle response information 112.

[0046] The muscle response information 112b is information indicating the bias of each part of the muscle response information 112a, and has an athlete name, a part name, a measurement date, and a left-right ratio as an example of the bias of the muscle response.

[0047] Note that the above operation may be performed only once, but it is desirable to perform it regularly in order to observe the process of the muscle response.

[0048] Further, as the bias of the response, the total risk of the five athletes 5 may be evaluated from the left - right ratios of a plurality of sites. For example, the risk may be evaluated from the bias of the response of the entire body, called the "trunk" excluding the upper part from the neck and the arms and legs.

[0049] Further, the measurement data of the muscle is not limited to hardness as long as it relates to the state of the muscle. For example, muscle strength may be measured. In this case, the performance of the athlete 5 can be evaluated based on the bias of muscle strength including the Hamstrings - to - quadriceps ratio (HQ ratio). This is useful because the HQ ratio is considered to be involved in the stability and movement ability of the knee joint.

[0050] The muscle response information 112 calculated by the processing device 1 by the above operation is displayed on the display unit of the terminal 3 by the evaluation data presentation unit 10B as one of the evaluation data 114 of the athlete 5, and the bias of the response of these sites is also displayed as the evaluation data 114. When the muscle measurement data acquisition unit 2 has a display function, it may be directly displayed on the display unit of the muscle measurement data acquisition unit 2 without passing through the terminal 3.

[0051] First, the evaluation data presentation unit 10B controls the display of the muscle response information 112a for each site.

[0052] Next, the risk evaluation engine 102 calculates the left - right ratio for each site of the muscle response information 112a as the muscle response information 112b, and the evaluation data presentation unit 10B controls the display.

[0053] Next, the risk evaluation engine 102 compares the risk evaluation reference information 113 with the left - right ratio, probabilistically generates the injury risk index which is the risk of injury, and stores the injury risk index in the storage unit 11 as the evaluation data 114. The evaluation data presentation unit 10B controls the display of the evaluation data 114.

[0054] If the injury risk index is above a predetermined value, the evaluation data display unit 10B may display a phrase suggesting "re-measurement" before, during, or simultaneously with the display of the evaluation data 114, and may also display details such as the area to be measured and the measurement angle. The predetermined value is set as appropriate. This is to allow for evaluation that takes into account the history of the muscles by re-measuring the area if an injury or severe fatigue is found in that area.

[0055] (Use of athlete profile data) The evaluation data generation unit 10A may receive athlete profile data, which includes at least one selected from the group consisting of the athlete's physical information, trainer intervention information, training information, performance information, and economic information, as well as market information of the athlete market, and generate the evaluation data 114 based on both the athlete profile data and the injury risk index.

[0056] The evaluation data generation unit 10A may calculate the asset value or economic value of athlete 5 or the team by, for example, analyzing an index indicating the muscle condition of athlete 5 (for example, a biological injury risk index including fatigue level, etc.) in association with the economic information of athlete 5 or market information of the athlete market. By integrally handling biological information centered on the muscle condition of athlete 5 and economic information including the contract terms of athlete 5 or market information of the athlete market including trends in the transfer market or fan engagement, the impact of changes in athlete 5's condition on the asset value or economic value of athlete 5 can be quantitatively evaluated.

[0057] The aforementioned physical information of an athlete may include age, height, weight, muscle mass, body fat percentage, genetic data, dietary data, sleep data, health check data, medical history, mental state, and past injury risk indicators. The aforementioned trainer intervention information of an athlete may include the treatment history and content of treatment received from a trainer. The aforementioned training information of an athlete may include training menus, training menu completion rates, instruction history and content of instruction received from coaches, and data from various sensors during training (position sensors, speed sensors, acceleration sensors, pressure sensors, piezoelectric sensors, blood flow sensors, heart rate sensors, images / videos). The aforementioned performance information of an athlete may include match participation data, match results, and data from various sensors during matches (position sensors, speed sensors, acceleration sensors, pressure sensors, piezoelectric sensors, blood flow sensors, heart rate sensors, images / videos). The aforementioned economic information of an athlete may include the amount of merchandise sold by the athlete, the number of years the athlete has been with the team, data on the athlete's popularity, the athlete's past and current contract terms, and the remaining contract years of the athlete. The aforementioned athlete market information may include trends in the athlete transfer market, cases of losses due to injuries, information based on fan engagement, data on sponsor advertising, past advertising examples, and information such as physical, training, performance, and economic information of similar athletes on other teams.

[0058] Figure 7 is a block diagram showing an example configuration of the athlete evaluation system of the present invention.

[0059] Athlete profile data 115 is input to the control unit 10 from the athlete data lake 7. The athlete data lake 7 stores all information about athlete 5, other athletes inside and outside the team, and the athlete market in any format such as text, audio, images, or video, which is input manually or automatically from various input devices, various sensors, and various databases. For example, the information stored in the athlete data lake 7 may be divided into three layers: a personal data layer, a team data layer, and a market data layer. The personal data layer includes basic data for each athlete, and may store all information such as information about each athlete's physique, training, and performance in any format. The team data layer includes internal team management information, and may store all information such as information about trainers' treatments and treatment history, coaches' instruction content and instruction history, and information about players' participation in games in any format. The market data layer includes market information and economic information outside the team, and may store all information such as information about the transfer market outside the team, advertising market, and other teams in any format.

[0060] The athlete evaluation system of the present invention may further include an athlete profile integration unit that outputs integrated data of the athlete profile data 7 and the measurement data 111.

[0061] When the athlete profile data 115 is input to the evaluation data generation unit 10A, various evaluation data 114 that cannot be generated using only the injury risk index can be generated.

[0062] For example, if the athlete profile data 115 includes the athlete 5's physical information, training information, performance information, and economic information, as well as market information for the athlete market, the evaluation data generation unit 10A can generate the athlete 5's asset value and economic risk indicator as evaluation data 114 by combining it with the injury risk indicator. For example, based on information on cases of loss due to injury, the unit predicts the number of days athlete 5 would be out of action if a similar injury occurred, and calculates the ratio of the number of days to the athlete 5's contract period. The economic risk indicator can be generated by multiplying this ratio by the athlete 5's contract amount, and then by the injury risk indicator, which is the probability that athlete 5 will drop out. Furthermore, the evaluation data generation unit 10A can generate the athlete 5's economic value as evaluation data 114 based on both the athlete 5's asset value and economic risk indicator. The athlete 5's economic value can be generated, for example, by multiplying the athlete 5's asset value by the athlete 5's economic risk indicator. The evaluation data generation unit 10A can generate the sum of the economic values ​​of each athlete belonging to the team as evaluation data 114.

[0063] The asset value estimation module 103 outputs the asset value of the athlete 5 and stores it in the storage unit 11 as evaluation data 114.

[0064] For example, if the athlete profile data 115 includes all or part of the data on sponsor advertisements and past advertising examples, the evaluation data generation unit 10A can generate the sponsor advertising value of the athlete 5 as evaluation data 114 by combining it with the injury risk index. For example, it can generate the return on investment of the advertisement, taking into account the risk of the athlete 5 getting injured during the advertising contract period.

[0065] For example, if the athlete profile data 115 includes all or part of the athlete 5's physical information, training information, and performance information, the evaluation data generation unit 10A can generate the athlete 5's condition as evaluation data 114 by combining it with the injury risk index. For example, if the athlete profile data 115 includes the athlete 5's mental state, the evaluation data generation unit 10A can also generate the condition that takes into account the athlete 5's mental state. The evaluation data generation unit 10A can generate a list of the conditions of each athlete belonging to the team as evaluation data 114. Based on the list, the evaluation data generation unit 10A can generate a list of athletes in the team that are desirable to participate in the match as evaluation data 114. Based on the list of athletes in the team that are desirable to participate in the match, the evaluation data generation unit 10A can generate a list of recommended tactics for the match as evaluation data 114.

[0066] For example, if the athlete profile data 115 includes all or part of the athlete 5's physical information, training information, and performance information, the evaluation data generation unit 10A can generate the substituteability of athlete 5 as evaluation data 114 by combining it with the injury risk index and the condition of the athletes belonging to the team. If the condition of an athlete in the same position as athlete 5 among the athletes belonging to the team is superior, the substituteability of athlete 5 increases. The substituteability of athlete 5 may also be used when generating the economic value of athlete 5. For example, based on information on cases of loss due to injury, the number of days athlete 5 would be out of action if athlete 5 suffered a similar injury is predicted, and the ratio of the number of days to the athlete 5's contract period is calculated. The economic risk index can be generated by multiplying the ratio by the athlete 5's contract amount, and further multiplying it by the injury risk index, which is the probability that athlete 5 will leave the team. By multiplying the asset value of athlete 5 by the economic risk indicator of athlete 5, and further multiplying by the substitutability of athlete 5, a more realistic economic value of athlete 5 can be generated.

[0067] The evaluation data generation unit 10A can generate evaluation data 114 for proposed athletes to be acquired from other teams, based on market information of the athlete market and the economic value and condition of each athlete belonging to the team.

[0068] For example, if the athlete profile data 115 includes the athlete 5's past injury risk indicators and trainer intervention information, the evaluation data generation unit 10A can generate evaluation data 114 that reflects the trainer's contribution, such as the effectiveness of treatments received from the trainer, by combining it with the athlete 5's current injury risk indicators. The trainer's treatment history, treatment details, and contribution may also be stored in the storage unit 11, allowing athletes and evaluators to search for the trainer's treatment history, treatment details, and contribution. In the search, the evaluation data presentation unit 10B may refer to the storage unit 11 and present information indicating that the trainer has a superior contribution. Furthermore, by combining the trainer's treatment details stored in the storage unit 11 with the athlete 5's current injury risk indicators, the evaluation data generation unit 10A can generate evaluation data 114 that reflects recommended treatments to reduce the injury risk indicators.

[0069] For example, if the athlete profile data 115 includes the athlete 5's past injury risk indicators, coaching history and content from coaches, and match results, the evaluation data generation unit 10A can combine this with the athlete 5's current injury risk indicators to generate evaluation data 114 representing the coach's contribution, such as the effectiveness of the coaching received. If the coach appropriately assesses the athlete 5's condition and provides guidance, resulting in the athlete 5's performance in matches being maximized and the injury risk not worsening, the coach's contribution will be higher.

[0070] For example, if the athlete profile data 115 includes the athlete 5's past injury risk indicators, match participation data, and match results, the evaluation data generation unit 10A can combine this with the athlete 5's current injury risk indicators to generate the coach's contribution, such as the effectiveness of the coach's athlete selection, as evaluation data 114. If the coach appropriately judges the athlete 5's condition and selects them for matches, resulting in the athlete 5 performing at their best and the injury risk not worsening, the coach's contribution will be higher.

[0071] In addition, the evaluation data generation unit 10A can generate various evaluation data based on both the athlete profile data 115 and the injury risk index of athlete 5, such as recommended training menus for athlete 5, changes in the team's overall portfolio, weekly reports of those changes, monthly reports of those changes, the market value of athlete 5 in the transfer market, the ranking of that market value within the team, and the estimated acquisition price of the entire team.

[0072] (Customized UI for evaluation data) The evaluation data presentation unit 10B may have a user interface (UI) that customizes the evaluation data 114 presented according to the authority granted to the evaluator. However, it is not necessary for all of the evaluation data to be customized for each evaluator, and common items may be displayed to improve shared understanding and communication among the evaluators. For example, the muscle response information 112 calculated by the evaluation data generation unit 10A may be presented via a UI that can be referenced as common items by multiple evaluators such as trainers, team doctors, coaches, managers, and executives. This can suppress discrepancies in evaluation criteria and judgment axes among each evaluator and promote the unification of decision-making regarding the condition evaluation of the athlete 5 and team strategy. This UI may have a configuration that synchronizes information via common items (e.g., Gn score, fatigue index, etc.) while maintaining a customized view for each evaluator.

[0073] Figure 8 is a schematic diagram showing an example of a screen displayed on the display unit of the terminal 3.

[0074] Screen 30 is a screen that displays the muscle response and left-right ratio values ​​for each part of a selected athlete, and includes a display tab 301 which is the currently selected and displayed tab, a switch tab 302 which switches to different display content when selected, an athlete selection frame 303 for selecting the athlete for which information will be displayed, a period selector 304 for selecting the period for which information will be displayed, a right-side display area 305 which displays muscle response information for each part on the right, a left-side display area 306 which displays muscle response information for each part on the left, and a left-right ratio display area 307 which displays the left-right ratio of each part.

[0075] For parts of the left-right ratio display area 307 where the left-right ratio is greater than or equal to the standard, warning displays 307a1 and 307c1 are displayed by changing the display color, display brightness, transparency, etc., as shown in left-right ratio displays 307a and 307c. To make it easier to understand intuitively, a drawing of the human body may be displayed, and for parts where the left-right ratio is greater than or equal to the standard, the warning displays 307a1 and 307c1 may be displayed by a map display, such as circling the relevant part in the drawing.

[0076] Figure 9 is a schematic diagram showing an example of a screen displayed on the display unit of the terminal 3.

[0077] Screen 31 is a screen that graphically displays the muscle response of each part of a selected athlete, and includes a display tab 311 which is the currently selected and displayed tab, a switch tab 312 which switches to different display content when selected, an athlete selection frame 313 for selecting the athlete for whom information will be displayed, a body part selector 314 for selecting the body part for which information will be displayed, a period selector 315 for selecting the period for which information will be displayed, and a graph display area 316 which graphically displays the time series of muscle response of the selected body part.

[0078] The graph display area 316 displays, for example, a graph 316a showing the change in the front of the right thigh and a graph 316b showing the change in the front of the left thigh, and displays a warning display 316c for periods when the left-right ratio exceeds a standard. The warning display may be expressed using a "Warning" icon on the plot of the relevant data, or by changing the color, brightness, transparency, etc. of the data plot or its surroundings.

[0079] The athlete 5 and the trainer 6 check the contents of screens 30 and 31 and confirm the muscle response and injury risk indicators of the athlete 5. The athlete 5 and the trainer 6 also check the risks of the athlete 5 from various perspectives by switching the athlete selection frame 303 and the period selector 304 on screen 30, the athlete selection frame 313, the body part selector 314 and the period selector 314 on screen 31, etc. Here, for example, the evaluation data 114 may have a customized UI so that the athlete 5 can only view their own information on screens 30 and 31 according to their given permissions, while the trainer 6 can view screens 30 and 31 while switching the information of the athletes they are in charge of, according to their given permissions.

[0080] Figure 10 is a schematic diagram showing an example of a screen displayed on the display unit of the terminal 3.

[0081] Screen 32 is a screen that displays the injury risk and recommended treatment for each part of a selected athlete, and includes an athlete selection frame 321 for selecting the athlete to whom the information will be displayed, a doll body part selector 322 for selecting the body part on which the recommended treatment will be displayed, and a recommended treatment display area 323 on which the injury risk and recommended treatment for the selected body part are displayed.

[0082] The athlete 5 and the trainer 6 confirm the contents of the screen 32 and check the injury risk and recommended treatment for athlete 5. For example, the evaluation data 114 may have a customized UI so that athlete 5 can view only their own information on the screen 32 according to their given permissions, while trainer 6 can view the screen 32 while switching between the information of the athletes they are in charge of, according to their given permissions. For example, the evaluation data 114 may have a customized UI so that the recommended treatments displayed to athlete 5 and trainer 6 are different, depending on the permissions given to athlete 5 and trainer 6, respectively.

[0083] Figure 11 is a schematic diagram showing an example of a screen displayed on the display unit of the terminal 3.

[0084] Screen 33 is a screen that displays the condition of each athlete in the team and suggestions for athletes who are likely to participate in the match, and has a condition display area 331 where the condition is displayed and a match participant athlete display area 332 where the suggestions are displayed.

[0085] For example, the evaluation data 114 may have a customized UI so that a coach authorized to display the screen 33 can check the contents of the screen 33 and view the condition of each athlete in the team and the proposed players for the match. For example, the evaluation data 114 may have a customized UI so that the proposed players for the match displayed to the coach are different depending on the authority granted to each coach according to their respective roles, such as manager, offensive coach, defensive coach, etc., such as a general proposal, an offensive proposal, or a defensive proposal.

[0086] Figure 12 is a schematic diagram showing an example of a screen displayed on the display unit of the terminal 3.

[0087] Screen 34 is a screen that displays the economic value of each athlete in the team and the economic value of the team as a whole, and has economic value display areas 341 and 342 on which the economic values ​​are displayed.

[0088] For example, the evaluation data 114 may have a customized UI so that managers and third parties who are authorized to display the screen 34 can check the contents of the screen 34 and view the economic value of each athlete in the team and the economic value of the team as a whole. For example, the evaluation data 114 may have a customized UI so that a third party can view only the area 342 of the screen 34 that displays the economic value of the team as a whole, depending on the authority granted to them, while a manager can view the area 341 that displays the ranking of the economic value of each athlete in the team, depending on the authority granted to them. In addition to these, for example, the evaluation data 114 may have a customized UI so that an athlete 5 can view only their own economic value on the screen 34, depending on the authority granted to them, while a trainer 6 can view the screen 34 while switching between viewing the economic value of the athletes they are in charge of, depending on the authority granted to them.

[0089] The present invention will be described in more detail below based on examples, but the present invention is not limited to these examples.

[0090] Example 1 After a practice match, Trainer B measured Athlete A's muscles using the muscle measurement data acquisition unit. The evaluation data generation unit generated evaluation data indicating that the Gn value of the left hamstring had increased by 28% since the previous measurement, and the difference with the right leg had also increased by 36%. The evaluation data presentation unit displayed the evaluation data on a terminal operated by Athlete A. The evaluation data generation unit further generated Athlete A's injury risk, recommended treatment, recommended training menu, condition, eligibility score, and economic value. The evaluation data presentation unit displayed an alert on Trainer B's terminal stating "Injury Risk: High". Trainer B performed a range of motion test and muscle response evaluation on Athlete A, and performed cooling and stretching on the relevant areas. Team doctor C, considering Athlete A's medical history and physical condition on the day, recorded a medical finding of "Recommendation to temporarily refrain from playing". The evaluation data presentation unit displayed Athlete A's physical changes and recommended training menu on Coach D's terminal. Coach D reduced athlete A's running distance and contact practice volume by 30% during the following day's training, compared his technical performance with other athletes in the same position, and restructured the individual strengthening menu for the following week. The evaluation data display unit presented information on athlete A's condition and "availability score (0.58)" to manager E's terminal. Manager E decided not to use athlete A in the next match, revised the tactical plan using a substitute athlete based on the team's overall position-specific evaluation data, and updated the pre-match briefing materials. The evaluation data display unit presented information on the terminal of executive F, a member of the team's management team, regarding "a temporary decrease in athlete A's economic value due to increased risk (-12%)" and "future loss avoidance amount (+1.8 million yen)." Executive F considered adjusting the timing of transfer negotiations and reviewing the rental policy, taking into account the risks and value fluctuations of other athletes. One week later, trainer B measured athlete A's muscles at the muscle measurement data acquisition unit. The evaluation data generation unit generated evaluation data indicating that the left-right difference in Gn had returned to an acceptable range, and the evaluation data presentation unit displayed it on trainer B's terminal. Trainer B confirmed the effectiveness of the rehabilitation protocol, saved the improvement record as athlete profile data, and stored it in the athlete data lake. The team doctor diagnosed the athlete as being at an "acceptable level for return to play" and provided feedback on the return-to-play decision to manager E and coach D.

[0091] Currently known athlete evaluation systems do not calculate an athlete's current risk of injury. Furthermore, the suspension of an athlete's activities by a team results in economic losses for the team. However, currently known athlete evaluation systems do not measure the economic losses incurred when an athlete is advised by a doctor to suspend activities. A system is needed that can not only measure an athlete's muscle fatigue but also evaluate all impacts based on the athlete's muscle condition, such as the risk of injury and the resulting economic risks to the team. However, this invention generates various evaluation data of an athlete based on measurement data of the athlete's muscles and can further present this evaluation data to the evaluator.

[0092] In the above embodiment, the functions of each means 100-103 and 10B of the control unit 10 were implemented by program, but all or part of each means may be implemented by hardware such as ASIC. Furthermore, the program used in the above embodiment can be stored and provided on a recording medium such as a CD-ROM. Also, the steps described in the above embodiment can be rearranged, deleted, or added without altering the essence of the present invention.

[0093] 1... Processing unit, 2... Measuring device, 3... Terminal, 4... Network, 5... Athlete, 6... Trainer, 7... Athlete data lake, 10... Control unit, 11... Storage unit, 12... Communication unit, 100... Measurement data acquisition means, 101... Muscle response calculation means, 102... Risk assessment engine, 103... Asset value estimation module, 10A... Evaluation data generation unit, 10B... Evaluation data presentation unit, 110... Information processing program, 111... Measurement data, 112... Muscle response information, 113... Risk assessment criteria information, 114... Evaluation data, 115... Athlete profile data.

Claims

1. An athlete evaluation system comprising: a muscle measurement data acquisition unit that acquires measurement data of an athlete's muscles; an evaluation data generation unit that generates evaluation data of the athlete based on the measurement data acquired by the muscle measurement data acquisition unit; and an evaluation data presentation unit that presents the evaluation data generated by the evaluation data generation unit to an evaluator.

2. An athlete evaluation system according to claim 1, wherein the evaluation data generation unit has a risk evaluation engine that outputs an injury risk index for the athlete based on the measurement data, and generates evaluation data that includes at least the injury risk index as an element.

3. An athlete evaluation system according to claim 2, wherein the risk evaluation engine outputs the injury risk index of the athlete based on the bias of muscle response obtained from the measurement data.

4. An athlete evaluation system according to claim 2, characterized in that the muscle measurement data acquisition unit measures the muscles of the same location of the athlete multiple times, and the risk evaluation engine outputs the injury risk index of the athlete based on the muscle history obtained from the multiple measurements.

5. An athlete evaluation system according to claim 1, wherein the evaluation data generation unit has an asset value estimation module that outputs the asset value of the athlete based on both athlete profile data which includes at least one selected from the group consisting of the athlete's physical information, trainer intervention information, training information, performance information, and economic information, and market information of the athlete market, and the athlete's injury risk index, and generates evaluation data which includes at least the asset value as an element.

6. An athlete evaluation system according to claim 1, wherein the evaluation data generation unit generates evaluation data including the trainer's contribution based on both the athlete profile data, which includes at least the athlete's past injury risk indicators and the treatment history the athlete has received from a trainer, and the athlete's injury risk indicators.

7. An athlete evaluation system according to claim 1, wherein the evaluation data presentation unit is equipped with a user interface that customizes the evaluation data presented according to the authority granted to the evaluator.

8. An athlete evaluation system according to claim 7, wherein the evaluation data generation unit generates evaluation data including recommended measures to reduce the injury risk index of the athlete, and the evaluation data presentation unit is customized to present the recommended measures to at least one of the athlete and the trainer.

9. An athlete evaluation system according to claim 7, characterized in that the evaluation data generation unit generates the evaluation data including the athlete's condition, and the evaluation data presentation unit is customized to present the athlete's condition to the coach.

10. An athlete evaluation system according to claim 9, characterized in that the evaluation data generation unit generates evaluation data including a list of the conditions of each athlete belonging to the team, and the evaluation data presentation unit is customized to present the list of conditions to the coach.

11. An athlete evaluation system according to claim 7, wherein the evaluation data generation unit generates evaluation data including the economic value of the athlete based on the asset value of the athlete, and the evaluation data presentation unit is customized to present the economic value of the athlete to at least one of the manager and a third party.

12. An athlete evaluation system according to claim 11, wherein the evaluation data generation unit generates evaluation data including the sum of the economic values ​​of each athlete belonging to the team, and the evaluation data presentation unit is customized to present the sum of the economic values ​​to at least one of the manager and a third party.

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