Analysis device, analysis method, and analysis program

Abstract

Provided is an analysis technology for analyzing characteristics of a psychological state in a game in which a plurality of players participate. According to the present invention, an information providing device comprises: an estimation unit that estimates a psychological state of a target player at each time point during play in a game in which a plurality of players participate; an acquisition unit that acquires play content, at each time point during play, of a specific player other than the target player among the plurality of players; a determination unit that searches for play content of a specific scene among the acquired play content at each time point, and determines a correlation between an estimation result of the psychological state of the target player at a time point when the searched-for play content occurred and the play content of the searched-for specific scene; and an output unit that outputs the play content of the specific scene determined to have the correlation as information indicating characteristics of the psychological state of the target player.

Description

Analysis Apparatus, Analysis Method, and Analysis Program

[0001] The present disclosure relates to an analysis apparatus, an analysis method, and an analysis program.

[0002] In esports, the psychological state of a player during gameplay greatly influences the outcome of a match. For this reason, in the field of esports, efforts have been made to grasp the characteristics of each player's psychological state by estimating the player's psychological state and analyzing the estimation results.

[0003] International Publication No. 2022 / 23440, Japanese Unexamined Patent Application Publication No. 2019-54547, International Publication No. 2022 / 158160, International Publication No. 2021 / 221140

[0004] On the other hand, in the case of a game in which a plurality of players participate, it is assumed that the psychological state of a target player changes under the influence of a specific player, or the psychological state of the entire target team changes under the influence of a specific player. Accordingly, the applicant of the present application has focused on the relationship with a specific player when grasping the characteristics of the psychological state of the target player or the characteristics of the psychological state of the entire target team.

[0005] An object of the present disclosure is to provide an analysis technique for analyzing characteristics of psychological states in a game in which a plurality of players participate.

[0006] According to one aspect, the analysis apparatus comprises: an estimation unit that estimates a psychological state at each time point during gameplay of a target player in a game in which a plurality of players participate; an acquisition unit that acquires gameplay content at each time point during gameplay of a specific player other than the target player among the plurality of players; a determination unit that searches for gameplay content of a specific scene from the acquired gameplay content at each time point, and determines a correlation between an estimation result of the psychological state of the target player at the time point when the searched gameplay content occurred and the searched gameplay content of the specific scene; and an output unit that outputs the gameplay content of the specific scene determined to have a correlation as information indicating characteristics of the psychological state of the target player.

[0007] According to this disclosure, it is possible to analyze the characteristics of psychological states in games involving multiple players.

[0008] Figure 1 is a diagram showing an example of the application of the analysis device. Figure 2 is a diagram showing an example of data stored by the analysis device. Figure 3 is a diagram showing an example of the hardware configuration of the analysis device. Figure 4 is a diagram showing the details of the functional configuration of the data analysis unit of the analysis device according to the first embodiment. Figure 5 is a first diagram showing an example of a search method. Figure 6 is a second diagram showing an example of a search method. Figure 7 is an example of a first flowchart showing the flow of analysis processing by the data analysis unit. Figure 8A is a first diagram showing an example of the output of analysis results. Figure 8B is a second diagram showing an example of the output of analysis results. Figure 9 is a diagram showing the details of the functional configuration of the data analysis unit of the analysis device according to the second embodiment. Figure 10 is a third diagram showing an example of a search method. Figure 11 is an example of a second flowchart showing the flow of analysis processing by the data analysis unit. Figure 12 is a third diagram showing an example of the output of analysis results. Figure 13 is a diagram showing the details of the functional configuration of the data analysis unit of the analysis device according to the third embodiment. Figure 14 is a fourth diagram showing an example of a search method. Figure 15 is an example of a third flowchart showing the flow of analysis processing by the data analysis unit. Figure 16 is a fourth diagram showing an example of analysis result output. Figure 17 is a diagram showing the details of the functional configuration of the data analysis unit of the analysis device according to the fourth embodiment. Figure 18 is a first diagram showing an example of a search method and an example of statistical value calculation. Figure 19 is an example of a fourth flowchart showing the flow of analysis processing by the data analysis unit. Figure 20 is a fifth diagram showing an example of analysis result output. Figure 21 is a diagram showing the details of the functional configuration of the data analysis unit of the analysis device according to the fifth embodiment. Figure 22 is a second diagram showing an example of a search method and an example of statistical value calculation. Figure 23 is an example of a fifth flowchart showing the flow of analysis processing by the data analysis unit. Figure 24 is a sixth diagram showing an example of analysis result output.

[0009] Each embodiment will be described below with reference to the attached drawings. In this specification and the drawings, components having substantially the same functional configuration are denoted by the same reference numerals, and redundant descriptions will be omitted.

[0010] [First Embodiment] <Example of Application of Analysis Device> First, an example of application of the analysis device according to the first embodiment will be described. Figure 1 is a diagram showing an example of application of the analysis device. As shown in Figure 1, the analysis device 150 is applied, for example, to a game provided in an e-sports tournament in which teams consisting of multiple players compete against each other.

[0011] In Figure 1, players 110_1 to 110_3 are players of Team 1 (player names: A, B, and C), and each participates in the game using gaming PCs (including peripherals) 120_1 to 120_3, respectively.

[0012] Similarly, players 130_1 to 130_3 are players of the second team (player names: D, E, and F), and they participate in the game using gaming PCs (including peripherals) 140_1 to 140_3, respectively.

[0013] Team 1, including players 110_1 to 110_3, and Team 2, including players 130_1 to 130_3, are participating in the same game, and both teams are playing against each other. During the match, data showing the content of the game scene is transmitted to the analysis device 150. Also during the match, data showing the play content of each player (players 110_1 to 110_3, 130_1 to 130_3) is transmitted to the analysis device 150. Furthermore, during the match, time-series data used to estimate the psychological state of each player (players 110_1 to 110_3, 130_1 to 130_3) is transmitted to the analysis device 150.

[0014] In the first embodiment, the time-series data used to estimate the psychological state includes: - Face image data taken of each player (players 110_1 to 110_3, 130_1 to 130_3); and - Vital data measured for each player (players 110_1 to 110_3, 130_1 to 130_3).

[0015] The analysis device 150 has an analysis program installed, and when this analysis program is executed, the analysis device 150 functions as a scene content acquisition unit 151, a play content acquisition unit 152, a psychological state estimation unit 153, and a data analysis unit 154.

[0016] The scene content acquisition unit 151 acquires data indicating the scene content of a game scene from a server device (not shown) that provides games in an e-sports tournament, and stores it in the data storage unit 155. In the first embodiment, the data indicating the scene content of a game scene refers, for example, to tag information that labels a specific scene in the game. Specifically, the tag information may include labels indicating the battle situation, such as "advantageous" or "disadvantageous," and labels indicating events, such as "surprise attack by opponent" or "point taken first by teammate." The scene content acquisition unit 151 may store such tag information including labels in the data storage unit 155 in association with the acquisition date and time of time-series data used for estimating psychological state.

[0017] The gameplay acquisition unit 152 acquires data from each gaming PC indicating the gameplay performed by each player in each game scene and stores it in the data storage unit 155. In the first embodiment, the data indicating the gameplay performed by each player refers to tag information that labels, for example, the specific operations performed by each player during the game, the results of specific operations performed by each player during the game, and the statements, conversations, and other action information of each player outside the game system. Specifically, the tag information may include labels indicating specific operations such as "use of special move," "surprise attack," "defense," and "retreat." The tag information may also include labels indicating the results of operations or actions such as "points taken first by an ally player," "points lost due to a surprise attack," "success of a special move," and "failure of a special move." Furthermore, the tag information may include labels indicating the actions of each player outside the game system, including statements such as "encouragement," "praise," "gratitude," "taunt," "clicking tongue," and "abusive language." The play content acquisition unit 152 may store the tag information, including such labels, in the data storage unit 155, in association with the acquisition date and time of the time-series data used for estimating the psychological state.

[0018] The psychological state estimation unit 153 acquires time-series data used to estimate the psychological state of each player from each gaming PC, estimates the psychological state of each player, and stores data indicating the psychological state estimation result in the data storage unit 155.

[0019] The data analysis unit 154 receives analysis instructions from the analyst 160, searches for data in the data storage unit 155 according to the received analysis instructions, and analyzes the searched data to output analysis results to the analyst 160, such as: information indicating the characteristics of the psychological state of the target player, and information indicating the characteristics of the psychological state of the entire target team.

[0020] Thus, according to the analysis device 150 of the first embodiment, it is possible to provide an analysis technique for analyzing the characteristics of psychological states in a game in which multiple players participate.

[0021] <Data Stored in the Data Storage Unit> Next, a specific example of data stored in the data storage unit 155 will be described. Figure 2 shows an example of data stored by the analysis device. In the example in Figure 2, for the sake of explanation, the elapsed time from the start of the game is represented continuously for each data point. However, the data storage unit 155 may store time-series data for multiple periods, with interruptions in between, depending on the analysis. When time-series data for multiple periods is stored in an arranged manner, the data analysis unit 154 may statistically analyze the characteristics of the psychological state in a game in which multiple players participate, based on the results of each of the multiple periods.

[0022] In Figure 2, reference numeral 200 schematically represents data indicating the content of a game scene, with the horizontal axis representing the elapsed time since the start of the game and the vertical axis representing the content of the scene at each point in time. In addition to the tag information mentioned above, the data indicating the content of a game scene may also include data indicating the win or loss in each stage of the game.

[0023] In Figure 2, reference numeral 210 schematically represents data showing the content of the game played by player 110_1, whose name is Player A, and reference numeral 211 schematically represents data showing the estimated psychological state of player 110_1, whose name is Player A. In both cases, the horizontal axis represents the elapsed time since the start of the game. On the other hand, the vertical axis of reference numeral 210 represents the content of the game played, and the vertical axis of reference numeral 211 represents the estimated psychological state (for example, basic emotions).

[0024] Similarly, symbols 220, 230, 240, 250, and 260 schematically represent data showing the gameplay of players 110_2 to 110_6, whose player names are B to F. Also, symbols 221, 231, 241, 251, and 261 schematically represent data showing the estimated psychological state of players 110_2 to 110_6, whose player names are B to F. In all cases, the horizontal axis represents the elapsed time since the start of the game. On the other hand, the vertical axis of symbols 220, 230, 240, 250, and 260 represents the gameplay, while the vertical axis of symbols 221, 231, 241, 251, and 261 represents the estimated psychological state (e.g., basic emotions).

[0025] <Hardware Configuration of the Analysis Device> Next, the hardware configuration of the analysis device 150 according to the first embodiment will be described. Figure 3 is a diagram showing an example of the hardware configuration of the analysis device. As shown in Figure 3, the analysis device 150 has a processor 301, memory 302, auxiliary storage device 303, I / F (Interface) device 304, communication device 305, and drive device 306. The hardware components of the analysis device 150 are interconnected via a bus 307.

[0026] The processor 301 has various computing devices such as a CPU (Central Processing Unit) and a GPU (Graphics Processing Unit). The processor 301 reads various programs (for example, analysis programs, etc.) into the memory 302 and executes them.

[0027] Memory 302 has main memory devices such as ROM (Read Only Memory) and RAM (Random Access Memory). The processor 301 and memory 302 form a so-called computer, and the processor 301 executes various programs read from memory 302, thereby enabling the computer to perform various functions (for example, scene content acquisition unit 151 to data analysis unit 154).

[0028] The auxiliary storage device 303 stores various programs and various data used when those programs are executed by the processor 301. For example, the data storage unit 155 is implemented in the auxiliary storage device 303.

[0029] The I / F device 304 receives operations from the analyst 160 on the analysis device 150 via the operation device 311. The I / F device 304 also outputs the results of internal processing by the analysis device 150 and displays them to the analyst 160 via the display device 312.

[0030] The communication device 305 is a communication device that connects to a network (not shown) and communicates with server equipment, gaming PCs, etc.

[0031] The drive device 306 is a device for setting the recording medium 313. The recording medium 313 here includes media that record information optically, electrically, or magnetically, such as CD-ROMs, flexible disks, and magneto-optical disks. The recording medium 313 may also include semiconductor memory that records information electrically, such as ROMs and flash memory.

[0032] The various programs to be installed on the auxiliary storage device 303 are installed, for example, when the distributed recording medium 313 is set in the drive device 306 and the various programs recorded on the recording medium 313 are read by the drive device 306. Alternatively, the various programs to be installed on the auxiliary storage device 303 may be installed by downloading them from the network via the communication device 305.

[0033] <Details of the Data Analysis Unit> Next, the details of the data analysis unit 154 implemented in the analysis device 150 will be described. Figure 4 is a diagram showing the details of the functional configuration of the data analysis unit of the analysis device according to the first embodiment. The data analysis unit 154 of the analysis device 150 according to the first embodiment analyzes whether the psychological state of the target player is correlated with the gameplay of a specific player other than the target player in a specific scene. To achieve this analysis objective, the data analysis unit 154 has a player designation unit 401, a scene designation unit 402, a search method determination unit 403, a search unit 404, a correlation determination unit 405, and an output unit 406, as shown in Figure 4.

[0034] The player designation unit 401 receives the player name of the target player and the player name of a specific player from the analyst 160 and notifies the search method determination unit 403.

[0035] The scene designation unit 402 receives information indicating a specific scene from the analyst 160 and notifies the search method determination unit 403.

[0036] The search method determination unit 403 determines a search method for searching the data storage unit 155 based on the player name notified by the player designation unit 401 and information indicating a specific scene notified by the scene designation unit 402. In the first embodiment, the search method determination unit 403 determines a search method that: - searches for a specific scene content from the scene content (reference numeral 200) stored in the data storage unit 155; - ​​acquires each point in time that has been searched; - searches for the play content at each acquired point in time from the play content of a specific player (for example, reference numeral 220) stored in the data storage unit 155; and - searches for the estimation result at each acquired point in time from the estimation result of the psychological state of the target player (for example, reference numeral 211) stored in the data storage unit 155. The search method determination unit 403 notifies the search unit 404 of the determined search method.

[0037] The search unit 404 notifies the data storage unit 155 of a search request based on the search method notified by the search method determination unit 403 and obtains the search results. In the first embodiment, the search unit 404 notifies the correlation determination unit 405 of: - Search results obtained by searching for the play content at each acquired point in time from the play content of a specific player (e.g., reference numeral 220) stored in the data storage unit 155; and - Search results obtained by searching for the estimation results at each acquired point in time from the estimation results of the psychological state of the target player (e.g., reference numeral 211) stored in the data storage unit 155.

[0038] The correlation determination unit 405 determines whether or not there is a correlation between the search results notified by the search unit 404. Specifically, the correlation determination unit 405 determines whether or not there is a correlation between: - the play content of a specific player in a specific scene that was searched, and - the estimated result of the psychological state of the target player at the time the searched play content occurred. If the correlation determination unit 405 determines that there is a correlation, it notifies the output unit 406 of the determination result. Note that the method used by the correlation determination unit 405 to determine whether or not there is a correlation is arbitrary, and for example, the presence or absence of a correlation may be determined by calculating the correlation coefficient.

[0039] When the correlation determination unit 405 notifies the output unit 406 of a determination result, the output unit 406 outputs an analysis result that includes "the content of a specific player's play in a specific scene" as information indicating the characteristics of the target player's psychological state.

[0040] <Specific Examples of Search Methods> Next, specific examples of search methods determined by the search method determination unit 403 will be explained. Figure 5 is the first diagram showing an example of a search method, and it shows the search method when a player on the same team as the target player (i.e., an allied player) is specified as the specific player.

[0041] In Figure 5, reference numeral 500 indicates: the player name of the target player (=A) and the player name of a specific player (=B) notified by the player designation unit 401; and information indicating a specific scene (scene α) notified by the scene designation unit 402.

[0042] According to the search method determined by the search method determining unit 403: - From the scene content (reference numeral 200) stored in the data storage unit 155, the scene content indicated by reference numerals 501, 502, and 503 is searched as "scene α", - Each time point of reference numerals 501, 502, and 503 is acquired, - From the play content (reference numeral 220) of player 110_2 with player name = B stored in the data storage unit 155, the play content indicated by reference numerals 511, 512, and 513 is searched as the play content at each acquired time point, - From the psychological state estimation result (reference numeral 211) of player 110_1 with player name = A stored in the data storage unit 155, the estimation results indicated by reference numerals 521, 522, and 523 are searched as the estimation results at each acquired time point.

[0043] FIG. 6 is a second diagram illustrating an example of a search method, and shows the search method when a player of a team that plays against the target player's team (i.e., an enemy player) is specified as the specific player.

[0044] In FIG. 6, reference numeral 600 indicates: - the player name of the target player (= A) and the player name of the specific player (= E) notified from the player specifying unit 401, and - information (scene α) indicating the specific scene notified from the scene specifying unit 402.

[0045] According to the search method determined by the search method determining unit 403: - From the scene content (reference numeral 200) stored in the data storage unit 155, the scene content indicated by reference numerals 601, 602, and 603 is searched as "scene α", - Each time point of reference numerals 601, 602, and 603 is acquired, - From the play content (reference numeral 250) of player 130_2 with player name = E stored in the data storage unit 155, the play content indicated by reference numerals 611, 612, and 613 is searched as the play content at each acquired time point, - From the psychological state estimation result (reference numeral 211) of player 110_1 with player name = A stored in the data storage unit 155, the estimation results indicated by reference numerals 621, 622, and 623 are searched as the estimation results at each acquired time point.

[0046] <Flow of Analysis Processing by Data Analysis Unit> Next, the flow of analysis processing by the data analysis unit 154 will be described. Fig. 7 is an example of a first flowchart showing the flow of analysis processing by the data analysis unit.

[0047] In step S701, a player specifying unit 401 of the data analysis unit 154 accepts specification of a player name of a target player.

[0048] In step S702, the player specifying unit 401 of the data analysis unit 154 accepts specification of a player name of a specific player.

[0049] In step S703, a scene specifying unit 402 of the data analysis unit 154 accepts information indicating a specific scene.

[0050] In step S704, a search unit 404 of the data analysis unit 154 searches for specific scene content from the scene content (reference numeral 200) stored in a data storage unit 155, and acquires each searched time point.

[0051] In step S705, the search unit 404 of the data analysis unit 154 searches for play content at each acquired time point from the play content (for example, reference numeral 220) of the specific player stored in the data storage unit 155.

[0052] In step S706, the search unit 404 of the data analysis unit 154 searches for an estimation result at each acquired time point from an estimation result of the psychological state of the target player (for example, reference numeral 211) stored in the data storage unit 155.

[0053] In step S707, a correlation determination unit 405 of the data analysis unit 154 determines whether there is a correlation between the play content of the specific player searched in step S705 and the estimation result of the psychological state of the target player searched in step S706.

[0054] In step S708, the correlation determination unit 405 of the data analysis unit 154 branches the processing according to the result of the determination of whether or not there is a correlation. If it is determined that there is no correlation (NO in step S708), the correlation determination unit 405 of the data analysis unit 154 proceeds to step S710. On the other hand, if it is determined that there is a correlation (YES in step S708), the correlation determination unit 405 of the data analysis unit 154 proceeds to step S709.

[0055] In step S709, the output unit 406 of the data analysis unit 154 outputs an analysis result that includes "the content of a specific player's play in a specific scene" as information indicating the characteristics of the target player's psychological state.

[0056] In step S710, the data analysis unit 154 determines whether to continue the analysis process. If it determines to continue (if the answer is YES in step S710), it returns to step S701. On the other hand, if it determines not to continue (if the answer is NO in step S710), it terminates the analysis process.

[0057] <Example of Analysis Result Output> Next, an example of the analysis result output by the output unit 406 of the data analysis unit 154 will be described.

[0058] (1) Output example when a specific player is an ally player First, we will explain an example of the output of the analysis result when the name of an ally player is specified as a specific player. Figure 8A is the first figure showing an example of the output of the analysis result.

[0059] As shown in Figure 8A, the analysis results 800 include the following information items: "game genre," "specific player attributes," "correlation judgment result," "countermeasures," and "necessary functions."

[0060] The “Game Genre” field stores the genre of the game the player in question played. FPS stands for First-Person Shooter, a type of shooting game. The “Specific Player Attributes” field stores the attributes of the specified player; in this case, it stores "ally player."

[0061] The "Correlation Judgment Results" section stores the gameplay of allied players that were determined to be correlated, along with the estimated psychological state of the target player. Example 800 of analysis results shows a correlation between an allied player killing the first opponent and a decrease in the target player's level of tension. Also, example 800 of analysis results shows a correlation between an allied player trolling in a random match and an increase in the target player's level of frustration.

[0062] The “countermeasures” section stores information on measures to improve the target player’s psychological state during gameplay, based on the “correlation assessment results.” Example 800 of the analysis results shows that, in order to alleviate the target player’s tension, it was suggested that the team should adopt a strategy that places a high value on securing the first kill. Also, example 800 of the analysis results shows that, in order to eliminate the target player’s frustration, it was suggested that the team should adopt a strategy of blocking random players.

[0063] The “Required Functions” section stores the functions that should be added to the gaming PCs of each player in the team that includes the target player, based on the “Countermeasures.” Example 800 of the analysis results shows that, in order to implement a strategy that highly values ​​the importance of getting the first kill as a team, it was proposed to add a function to visualize the level of tension of each player during gameplay, and a function to record the player who gets the first kill. Another example of the analysis results 800 shows that, in order to implement a strategy that blocks random players as a team, it was proposed to add a function to visualize the emotional state of each player during gameplay, and a function to record the gameplay of teammates.

[0064] (2) Output example when a specific player is an enemy player Next, we will explain an example of the output of the analysis result when the player name of an enemy player is specified as the specific player. Figure 8B is the second figure showing an example of the output of the analysis result.

[0065] As shown in Figure 8B, the analysis result 810 includes the same information items as the analysis result 820: "game genre," "specific player attributes," "correlation judgment result," "countermeasures," and "necessary functions."

[0066] The “Game Genre” field stores the genre of the game the target player participated in. The “Specific Player Attributes” field stores the attributes of the specified player, in this case, the enemy player. The “Correlation Judgment Result” field stores the enemy player's gameplay and the estimated psychological state of the target player, which were determined to be correlated. The “Countermeasures” field stores countermeasures to improve the target player's psychological state during gameplay, based on the “Correlation Judgment Result.” The “Required Functions” field stores functions that should be added to the gaming PCs of each player in the team that the target player is on, based on the “Countermeasures.”

[0067] <Summary> As is clear from the above explanation, the analysis device 150 according to the first embodiment: - Estimates the psychological state of a target player at each point in time during gameplay in a game in which multiple players participate. - Acquires the gameplay content of a specific player other than the target player at each point in time during gameplay among the multiple players. - Searches for the gameplay content of a specific scene from the acquired gameplay content at each point in time, and determines the correlation between the estimated result of the target player's psychological state at the time of the search and the gameplay content of the searched specific scene. - If a correlation is determined to exist, outputs the gameplay content of the specific scene as information indicating the characteristics of the target player's psychological state.

[0068] Thus, according to the analysis device 150 of the first embodiment, in a game in which multiple players participate, it is possible to analyze the influence of a specific player's gameplay in a specific scene as a characteristic of the psychological state of the target player.

[0069] [Second Embodiment] In the first embodiment described above, the case in which analysis is performed focusing on the relationship between the play content of a specific player in a specific scene and the actual play content. In contrast, the second embodiment describes a case in which analysis is performed focusing on the relationship between the estimation result of a specific psychological state of a specific player and the actual play content. The second embodiment will be described below, focusing on the differences from the first embodiment.

[0070] <Details of the Data Analysis Unit> First, the details of the data analysis unit 154 implemented in the analysis device 150 will be explained. Figure 9 is a diagram showing the details of the functional configuration of the data analysis unit of the analysis device according to the second embodiment. The data analysis unit 154 of the analysis device 150 according to the second embodiment analyzes whether the psychological state of a target player is correlated with a specific psychological state of a specific player other than the target player. To achieve this analysis objective, the data analysis unit 154 in the second embodiment has a player designation unit 901, a psychological state designation unit 902, a search method determination unit 903, a search unit 904, a correlation determination unit 905, and an output unit 906, as shown in Figure 9.

[0071] The player designation unit 901 receives the player name of the target player and the player name of a specific player (ally player) from the analyst 160, and notifies the search method determination unit 903.

[0072] The psychological state designation unit 902 receives information from the analyst 160 indicating a specific psychological state of a specific player and notifies the search method determination unit 903.

[0073] The search method determination unit 903 determines a search method for searching the data storage unit 155 based on the player name notified by the player designation unit 901 and information indicating a specific psychological state notified by the psychological state designation unit 902. In the second embodiment, the search method determination unit 903 determines a search method that: - searches for the estimation result of a specific psychological state from the estimation result of the psychological state of a specific player stored in the data storage unit 155 (for example, reference numeral 221); - acquires each point in time during the search; and - searches for the estimation result at each acquired point in time from the estimation result of the psychological state of the target player stored in the data storage unit 155 (for example, reference numeral 211). The search method determination unit 903 notifies the search unit 904 of the determined search method.

[0074] The search unit 904 notifies the data storage unit 155 of a search request based on the search method notified by the search method determination unit 903 and obtains the search results. In the second embodiment, the search unit 904 notifies the correlation determination unit 905 of: - the search results obtained by searching for the estimation result of a specific psychological state from the estimation result of the psychological state of a specific player (e.g., reference numeral 221) stored in the data storage unit 155; and - the search results obtained by searching for the estimation result at each point in time obtained from the estimation result of the psychological state of the target player (e.g., reference numeral 211) stored in the data storage unit 155.

[0075] The correlation determination unit 905 determines whether or not there is a correlation between the search results notified by the search unit 904. Specifically, the correlation determination unit 905 determines whether or not there is a correlation between: the estimation result of a specific psychological state of a specific player, and the estimation result of the psychological state of the target player at the time the specific psychological state was estimated. If the correlation determination unit 905 determines that there is a correlation, it notifies the output unit 906 of the determination result.

[0076] When the correlation determination unit 905 notifies the output unit 906 of a determination result, the output unit 906 outputs an analysis result that includes "an estimated result of a specific psychological state of a specific player" as information indicating the characteristics of the psychological state of the target player.

[0077] <Specific Examples of Search Methods> Next, specific examples of search methods determined by the search method determination unit 903 will be described. Figure 10 is a second diagram showing an example of a search method.

[0078] In Figure 10, reference numeral 1000 indicates: the player name of the target player (=A) and the player name of a specific player (=B), which are notified by the player designation unit 901; and information indicating a specific psychological state (anger), which is notified by the psychological state designation unit 902.

[0079] According to the search method determined by the search method determination unit 903, - From the estimated result of the psychological state of player 110_2 with player name = B stored in the data storage unit 155 (code 221), codes 1001 to 1003 are searched for as "anger", - Each time point of codes 1001 to 1003 is obtained, - From the estimated result of the psychological state of player 110_1 with player name = A stored in the data storage unit 155 (code 211), the estimated results shown in codes 1011 to 1013 are searched as the estimated results at each time point of codes 1001 to 1003 obtained.

[0080] The example in Figure 10 shows that the win / loss record for each stage, which includes each acquired point in time, was read from the scene content (reference numeral 200) stored in the data storage unit 155 (reference numerals 1021, 1022, and 1023).

[0081] <Analysis Processing Flow by Data Analysis Unit> Next, the analysis processing flow by the data analysis unit 154 in the second embodiment will be described. Figure 11 is an example of a second flowchart showing the analysis processing flow by the data analysis unit.

[0082] In step S1101, the player designation unit 901 of the data analysis unit 154 accepts the designation of the player name of the target player.

[0083] In step S1102, the player designation unit 901 of the data analysis unit 154 accepts the designation of a player name for a specific player.

[0084] In step S1103, the psychological state designation unit 902 of the data analysis unit 154 receives information indicating a specific psychological state.

[0085] In step S1104, the search unit 904 of the data analysis unit 154 searches for the estimation result of a specific psychological state (for example, reference numeral 221) of a specific player stored in the data storage unit 155, and obtains each point in time that was searched.

[0086] In step S1105, the search unit 904 of the data analysis unit 154 searches for the estimated psychological state of the target player (for example, reference numeral 211) stored in the data storage unit 155 to find the estimated results at each acquired point in time.

[0087] In step S1106, the correlation determination unit 905 of the data analysis unit 154 determines whether or not there is a correlation between the estimation result of a specific psychological state of a specific player that was searched in step S1104 and the estimation result of the psychological state of the target player that was searched in step S1105.

[0088] In step S1107, the correlation determination unit 905 of the data analysis unit 154 branches the processing according to the result of the determination of whether or not there is a correlation. If it is determined that there is no correlation (NO in step S1107), the correlation determination unit 905 of the data analysis unit 154 proceeds to step S1109. On the other hand, if it is determined that there is a correlation (YES in step S1107), the correlation determination unit 905 of the data analysis unit 154 proceeds to step S1108.

[0089] In step S1108, the output unit 906 of the data analysis unit 154 outputs an analysis result that includes "an estimated result of a specific psychological state of a specific player" as information indicating the characteristics of the psychological state of the target player.

[0090] In step S1109, the data analysis unit 154 determines whether to continue the analysis process. If it determines to continue (if the answer is YES in step S1109), it returns to step S1101. On the other hand, if it determines not to continue (if the answer is NO in step S1109), it terminates the analysis process.

[0091] <Example of Analysis Result Output> Next, an example of the analysis result output by the output unit 906 of the data analysis unit 154 will be described. Figure 12 is a third figure showing an example of the analysis result output.

[0092] As shown in Figure 12, the analysis results 1200 include the following information items: "game genre," "specific player attributes," "correlation judgment result," "countermeasures," and "necessary functions."

[0093] The “Game Genre” field stores the genre of the game the player in question participated in. The “Specific Player Attributes” field stores the attributes of the specified player, in this case, an ally player.

[0094] The "Correlation Judgment Results" section stores the estimated psychological state of specific allied players that were determined to be correlated, as well as the estimated psychological state of the target player. In addition, the example in Figure 12 also mentions the win rate based on the results of each stage.

[0095] The “Countermeasures” section stores countermeasures to improve the target player's psychological state during gameplay, based on the “correlation assessment results.” The “Required Functions” section stores functions that should be added to the gaming PCs of each player in the team that includes the target player, based on the “Countermeasures.”

[0096] <Summary> As is clear from the above explanation, the analysis device 150 according to the second embodiment: - Estimates the psychological state of the target player at each point in time during gameplay in a game in which multiple players participate, and the psychological state of a specific player on the same team as the target player at each point in time during gameplay. - Determines the correlation between the estimation result of a specific psychological state among the estimation results of the specific player's psychological state at each point in time during gameplay, and the estimation result of the target player's psychological state at the time the specific psychological state was estimated. - If a correlation is determined to exist, outputs the estimation result of the specific psychological state of the specific player as information indicating the characteristics of the target player's psychological state.

[0097] Thus, according to the analysis device 150 of the second embodiment, in a game in which multiple players participate, it is possible to analyze the influence of a specific psychological state of a specific player as a characteristic of the psychological state of the target player.

[0098] [Third Embodiment] In the second embodiment described above, the case in which analysis is performed focusing on the relationship with the estimated result of a specific psychological state of a specific player. In contrast, the third embodiment describes a case in which analysis is performed focusing on the relationship with the estimated result of a synchronized psychological state of multiple specific players. The third embodiment will be described below, focusing on the differences from the second embodiment described above.

[0099] <Details of the Data Analysis Unit> First, we will explain the details of the data analysis unit 154 implemented in the analysis device 150. Figure 13 is a diagram showing the details of the functional configuration of the data analysis unit of the analysis device according to the third embodiment. The data analysis unit 154 of the analysis device 150 according to the third embodiment analyzes whether the psychological state of a target player is correlated with the synchronized psychological states of several specific players other than the target player. To achieve this analysis objective, the data analysis unit 154 in the third embodiment has a player designation unit 1301, a synchronization designation unit 1302, a search method determination unit 1303, a search unit 1304, a correlation determination unit 1305, and an output unit 1306, as shown in Figure 13.

[0100] The player designation unit 1301 receives the player name of the target player and the player names of several specific players (ally players) from the analyst 160, and notifies the search method determination unit 1303.

[0101] The synchronization designation unit 1302 receives information from the analyst 160 indicating the synchronized psychological state among the various psychological states of multiple specific players, and notifies the search method determination unit 1303.

[0102] The search method determination unit 903 determines a search method for searching the data storage unit 155 based on the player name notified by the player designation unit 1301 and the information indicating the synchronized psychological state notified by the synchronization designation unit 1302. In the third embodiment, the search method determination unit 1303 determines a search method that: - searches for information indicating the synchronized psychological state from the estimation results of the psychological states of a plurality of specific players stored in the data storage unit 155 (for example, reference numeral 221, 231); - acquires each point in time that has been searched; and - searches for the estimation result at each acquired point in time from the estimation result of the psychological state of the target player stored in the data storage unit 155 (for example, reference numeral 211). The search method determination unit 1303 notifies the search unit 1304 of the determined search method.

[0103] The search unit 1304 notifies the data storage unit 155 of a search request based on the search method notified by the search method determination unit 1303 and obtains the search results. In the third embodiment, the search unit 1304 notifies the correlation determination unit 1305 of: - Search results obtained by searching for the estimated psychological state of a synchronized state from the estimated psychological state of a plurality of specific players stored in the data storage unit 155; and - Search results obtained by searching for the estimated psychological state of a target player at each point in time obtained from the estimated psychological state of the target player stored in the data storage unit 155.

[0104] The correlation determination unit 1305 determines whether or not there is a correlation between the search results notified by the search unit 1304. Specifically, the correlation determination unit 1305 determines the correlation between: the estimated results of the synchronized psychological states of multiple specific players, and the estimated results of the psychological states of the target player at each synchronized point in time. If the correlation determination unit 1305 determines that there is a correlation, it notifies the output unit 1306 of the determination result.

[0105] When the correlation determination unit 1305 notifies the output unit 1306 of a determination result, it outputs an analysis result that includes "estimated results of the synchronized psychological states of multiple specific players" as information indicating the characteristics of the target player's psychological state.

[0106] <Specific Examples of Search Methods> Next, specific examples of search methods determined by the search method determination unit 1303 will be described. Figure 14 is a third diagram showing an example of a search method.

[0107] In Figure 14, reference numeral 1400 indicates: the player name of the target player (=A) and the player names of multiple specific players (=B, C) notified by the player designation unit 1301; and information indicating the synchronized psychological state (concentration) notified by the synchronization designation unit 1302.

[0108] According to the search method determined by the search method determination unit 1303, - From the estimated psychological state results (symbols 221, 231) of players 110_2 and 110_3 with player names B and C stored in the data storage unit 155, symbols 1401 to 1403 and 1411 to 1413 are searched as synchronized states of "concentration". - Each time point of symbols 1401 to 1403 and 1411 to 1413 is acquired. - From the estimated psychological state result (symbol 211) of player 110_1 with player name A stored in the data storage unit 155, the estimated results shown by symbols 1421 to 1423 are searched as the estimated results at each time point of symbols 1401 to 1403 and 1411 to 1413 that were acquired.

[0109] <Analysis Process Flow by Data Analysis Unit> Next, the analysis process flow by the data analysis unit 154 in the third embodiment will be described. Figure 15 is an example of a third flowchart showing the analysis process flow by the data analysis unit.

[0110] In step S1501, the player designation unit 1301 of the data analysis unit 154 accepts the designation of the player name of the target player.

[0111] In step S1502, the player designation unit 1301 of the data analysis unit 154 accepts the designation of player names for multiple specific players.

[0112] In step S1503, the synchronization designation unit 1302 of the data analysis unit 154 receives information indicating the psychological state in a synchronized state.

[0113] In step S1504, the search unit 1304 of the data analysis unit 154 searches for the estimated psychological state of a synchronized state from the estimated psychological state of a plurality of specific players (for example, reference numerals 221 and 231) stored in the data storage unit 155. As a result, the search unit 1304 of the data analysis unit 154 acquires each point in time that it has searched.

[0114] In step S1505, the search unit 1304 of the data analysis unit 154 searches for the estimated psychological state of the target player (for example, reference numeral 211) stored in the data storage unit 155 to find the estimated results at each acquired point in time.

[0115] In step S1506, the correlation determination unit 1305 of the data analysis unit 154 determines whether or not there is a correlation between the estimation result explored in step S1504 and the estimation result explored in step S1505.

[0116] In step S1507, the correlation determination unit 1305 of the data analysis unit 154 branches the processing according to the result of the determination of whether or not there is a correlation. If it is determined that there is no correlation (NO in step S1507), the correlation determination unit 1305 of the data analysis unit 154 proceeds to step S1509. On the other hand, if it is determined that there is a correlation (YES in step S1507), the correlation determination unit 1305 of the data analysis unit 154 proceeds to step S1508.

[0117] In step S1508, the output unit 1306 of the data analysis unit 154 outputs an analysis result that includes "estimated results of the synchronized psychological states of multiple specific players" as information indicating the characteristics of the psychological state of the target player.

[0118] In step S1509, the data analysis unit 154 determines whether to continue the analysis process. If it determines to continue (if the answer is YES in step S1509), it returns to step S1501. On the other hand, if it determines not to continue (if the answer is NO in step S1509), it terminates the analysis process.

[0119] <Example of Analysis Result Output> Next, an example of the analysis result output by the output unit 1306 of the data analysis unit 154 will be described. Figure 16 is the fourth figure showing an example of the analysis result output.

[0120] As shown in Figure 16, the analysis results 1600 include the following information items: "game genre," "attributes of multiple specific players," "correlation determination results," "countermeasures," and "necessary functions."

[0121] The “Game Genre” field stores the genre of the game the target player participated in. The “Attributes of Multiple Specific Players” field stores the attributes of the specified multiple specific players, namely the allied players.

[0122] The "correlation determination results" store the estimated results of the synchronized psychological states of multiple specific players that were determined to be correlated, as well as the estimated results of the psychological state of the target player. In addition, in the example in Figure 16, the win rate is also mentioned based on the win / loss results in each stage.

[0123] The “Countermeasures” section stores countermeasures to improve the target player's psychological state during gameplay, based on the “correlation assessment results.” The “Required Functions” section stores functions that should be added to the gaming PCs of each player in the team that includes the target player, based on the “Countermeasures.”

[0124] <Summary> As is clear from the above explanation, the analysis device 150 according to the third embodiment: - Estimates the psychological state of the target player at each point in time during gameplay in a game in which multiple players participate, and the psychological state of multiple specific players on the same team as the target player at each point in time during gameplay. - Determines the correlation between the estimated psychological state of the synchronized state among the estimated psychological state of the multiple specific players at each point in time during gameplay, and the estimated psychological state of the target player at each synchronized point in time. - If a correlation is determined to exist, outputs the estimated psychological state of the synchronized state as information indicating the characteristics of the target player's psychological state.

[0125] Thus, according to the analysis device 150 of the third embodiment, in a game in which multiple players participate, it is possible to analyze the influence of the synchronized psychological states of multiple specific players as a characteristic of the psychological state of the target player.

[0126] [Fourth Embodiment] The first to third embodiments described above describe the case in which the characteristics of the psychological state of the target player are analyzed. In contrast, the fourth embodiment describes the case in which the characteristics of the psychological state of the entire target team are analyzed. The fourth embodiment will be described below, focusing on the differences from the first to third embodiments.

[0127] <Details of the Data Analysis Unit> First, the details of the data analysis unit 154 implemented in the analysis device 150 will be explained. Figure 17 is a diagram showing the details of the functional configuration of the data analysis unit of the analysis device according to the fourth embodiment. The data analysis unit 154 of the analysis device 150 according to the fourth embodiment analyzes whether the participation or non-participation of a specific player correlates with the psychological state of the entire target team. To achieve this analysis objective, the data analysis unit 154 in the fourth embodiment has a first player designation unit 1701 and a second player designation unit 1702, as shown in Figure 17. In addition, the data analysis unit 154 in the fourth embodiment has a search method determination unit 1703, a search unit 1704, a calculation unit 1705, a correlation determination unit 1706, and an output unit 1707.

[0128] In this embodiment, the data storage unit 155 is assumed to store multiple datasets designated by reference numerals 200 to 261, as shown in Figure 2 in the first embodiment. The multiple datasets include at least: - A dataset of the same player combination as shown in Figure 2 (player names: A, B, C), played against the same opposing team on different days; - A dataset of the same player combination as shown in Figure 2 (player names: A, B, C), played against a different opposing team; - A dataset of a different player combination (for example, player names: A, G, C) than the player combination shown in Figure 2 (player names: A, B, C), played against the same opposing team; - A dataset of a different player combination (for example, player names: A, G, C) than the player combination shown in Figure 2 (player names: A, B, C), played against a different opposing team; and so on. Note that "different opposing teams" here includes cases where the teams themselves are different, and cases where the teams themselves are the same, but the combination of players on those teams is different.

[0129] The first player designation unit 1701 receives the player names of the players in the 1-1 team from the analyst 160 and notifies the search method determination unit 1703.

[0130] The second player designation unit 1702 receives the player names of the players in the first and second teams from the analyst 160 and notifies the search method determination unit 1703. Note that the first and second teams have different specific players.

[0131] The search method determination unit 1703 determines a search method for searching the data storage unit 155 based on the player name notified by the first player designation unit 1701 and the player name notified by the second player designation unit 1702. In the fourth embodiment, the search method determination unit 1703 determines a search method that: - searches for a dataset containing a team (1st-1st team) consisting of the player name notified by the first player designation unit 1701 from among a plurality of datasets stored in the data storage unit 155; and - searches for a dataset containing a team (1st-2nd team) consisting of the player name notified by the second player designation unit 1702 from among a plurality of datasets stored in the data storage unit 155.

[0132] The search unit 1704 notifies the data storage unit 155 of a search request based on the search method notified by the search method determination unit 1703 and obtains the search results. In the fourth embodiment, the search unit 1704 notifies the calculation unit 1705 of the following: - Search results obtained by searching for a dataset containing a team consisting of player names notified by the first player designation unit 1701 (Team 1-1) from a plurality of datasets stored in the data storage unit 155; and - Search results obtained by searching for a dataset containing a team consisting of player names notified by the second player designation unit 1702 (Team 1-2) from a plurality of datasets stored in the data storage unit 155.

[0133] The calculation unit 1705 classifies the search results notified by the search unit 1704 into: a first group consisting of datasets for team 1-1 that include a specific player, and a second group consisting of datasets for team 1-2 that do not include a specific player.

[0134] Furthermore, the calculation unit 1705 statistically processes the estimation results of specific psychological states (concentration) for players whose player names are notified by the first player designation unit 1701, from among the estimation results of psychological states included in the dataset classified into the first group. As a result, the calculation unit 1705 calculates a statistical value (mean value).

[0135] Similarly, the calculation unit 1705 statistically processes the estimation results of specific psychological states (concentration) for players whose player names are notified by the second player designation unit 1702, from among the estimation results of psychological states included in the dataset classified into the second group. Based on this, the calculation unit 1705 calculates a statistical value (mean value).

[0136] Furthermore, the calculation unit 1705 calculates the difference between: • the statistical value of the estimated result of a specific psychological state (e.g., average concentration level) calculated for each player in the first group, and • the statistical value of the estimated result of a specific psychological state (e.g., average concentration level) calculated for each player in the second group.

[0137] The correlation determination unit 1706 determines whether there is a correlation between the presence or absence of a specific player and the estimated psychological state of the entire target team by determining whether the difference calculated by the calculation unit 1705 is above a predetermined threshold. If the difference is above the predetermined threshold, the correlation determination unit 1706 determines that there is a correlation between the presence or absence of a specific player and the estimated psychological state of the entire target team, and notifies the output unit 1707 of the determination result.

[0138] When the correlation determination unit 1706 notifies the output unit 1707 of the determination result, the output unit 1707 outputs an analysis result that includes "whether or not a specific player is participating" as information indicating the characteristics of the psychological state of the entire target team.

[0139] <Specific Examples of Search Methods and Examples of Statistical Value Calculation> Next, specific examples of search methods determined by the search method determination unit 1703 and examples of statistical value calculations calculated by the calculation unit 1705 will be explained. Figure 18 is the first figure showing an example of a search method and an example of statistical value calculation.

[0140] In Figure 18, reference numeral 1800 indicates: - The player names (= A, B, C) of the players of Team 1-1, notified by the First Player Designation Unit 1701; and - The player names (= A, G, C) of the players of Team 1-2, notified by the Second Player Designation Unit 1702.

[0141] According to the search method determined by the search method determination unit 1703, - From the multiple datasets stored in the data storage unit 155, code 1820 is searched for as a dataset containing the 1st-1 team consisting of player names A, B, and C. - From the multiple datasets stored in the data storage unit 155, code 1840 is searched for as a dataset containing the 1st-2 team consisting of player names A, G, and C.

[0142] The example in Figure 18 shows that the win / loss record for each stage, which includes each point in time that was explored, was read from the scene contents (reference numerals 1810, 1830) stored in the data storage unit 155 (reference numerals 1811-1813, 1831-1833).

[0143] Furthermore, according to the calculation unit 1705, the average concentration level is calculated as a statistical value obtained by statistically processing the estimated results of specific psychological states (concentration) for each player named A, B, and C, based on the dataset shown in reference numeral 1820 (reference numeral 1821), and the average concentration level is calculated as a statistical value obtained by statistically processing the estimated results of specific psychological states (concentration) for each player named A, G, and C, based on the dataset shown in reference numeral 1840 (reference numeral 1841).

[0144] <Analysis Process Flow by Data Analysis Unit> Next, the analysis process flow by the data analysis unit 154 in the fourth embodiment will be described. Figure 19 is an example of the fourth flowchart showing the analysis process flow by the data analysis unit.

[0145] In step S1901, the first player designation unit 1701 of the data analysis unit 154 receives the player names of each player in the 1st-1 team.

[0146] In step S1902, the second player designation unit 1702 of the data analysis unit 154 receives the player names of each player in the first and second teams.

[0147] In step S1903, the search unit 1704 of the data analysis unit 154 searches for a dataset containing Team 1-1 from among multiple datasets stored in the data storage unit 155.

[0148] In step S1904, the search unit 1704 of the data analysis unit 154 searches for a dataset containing the 1st and 2nd teams from among the multiple datasets stored in the data storage unit 155.

[0149] In step S1905, the calculation unit 1705 of the data analysis unit 154 statistically processes the estimation results of the specific psychological state of each player for the first group, which is a group of datasets including the 1st-1 team. As a result, the calculation unit 1705 of the data analysis unit 154 calculates statistical values ​​of the estimation results of the specific psychological state for the first group.

[0150] In step S1906, the calculation unit 1705 of the data analysis unit 154 statistically processes the estimation results of the specific psychological state of each player for the second group, which is a dataset group including the first and second teams. As a result, the calculation unit 1705 of the data analysis unit 154 calculates statistical values ​​of the estimation results of the specific psychological state for the second group.

[0151] In step S1907, the calculation unit 1705 of the data analysis unit 154 calculates the difference between the statistical value calculated for the first group and the statistical value calculated for the second group.

[0152] In step S1908, the correlation determination unit 1706 of the data analysis unit 154 determines whether there is a correlation between the presence or absence of a specific player's participation and the estimated result of the overall psychological state of the target team. If the difference calculated in step S1907 is greater than or equal to a predetermined threshold, in step S1908 it is determined that there is a correlation between the presence or absence of a specific player's participation and the estimated result of the overall psychological state of the target team (determined as YES in step S1908). In this case, the correlation determination unit 1706 of the data analysis unit 154 proceeds to step S1909.

[0153] On the other hand, if the difference calculated in step S1907 is less than a predetermined threshold, step S1908 determines that there is no correlation between the participation of a specific player and the estimated psychological state of the entire target team (determined as NO in step S1908). In this case, the correlation determination unit 1706 of the data analysis unit 154 proceeds to step S1910.

[0154] In step S1909, the output unit 1707 of the data analysis unit 154 outputs an analysis result that includes "whether or not a specific player is participating" as information indicating the characteristics of the psychological state of the entire target team.

[0155] In step S1910, the data analysis unit 154 determines whether to continue the analysis process. If it determines to continue (if the answer is YES in step S1910), it returns to step S1901. On the other hand, if it determines not to continue (if the answer is NO in step S1910), it terminates the analysis process.

[0156] <Example of Analysis Result Output> Next, an example of the analysis result output by the output unit 1707 of the data analysis unit 154 will be described. Figure 20 is the fifth figure showing an example of the analysis result output.

[0157] As shown in Figure 20, the analysis results 2000 include the following information items: "game genre," "specific player attributes," "correlation judgment result," "countermeasures," and "necessary functions."

[0158] The “Game Genre” field stores the genre of the game in which Team 1-1 and Team 1-2 participated. The “Specific Player Attributes” field stores the attributes of specific players that differ between Team 1-1 and Team 1-2, indicating which players are allied.

[0159] The "correlation determination results" store whether or not a specific player who was determined to be correlated participated, and the estimated psychological state of the entire target team. In addition, the example in Figure 20 also mentions the win rate based on the results of each stage.

[0160] The “Countermeasures” section stores the countermeasures to improve team composition based on the “Correlation Judgment Results.” The “Required Functions” section stores the functions that should be added to the gaming PCs of each player in Team 1-1 and Team 1-2, based on the “Countermeasures.”

[0161] <Summary> As is clear from the above explanation, the analysis device 150 according to the fourth embodiment: - In a game in which multiple players participate, it estimates the psychological state of each player on each team at each point in time during gameplay and stores a dataset of the estimation results for each team. - It classifies the multiple datasets into a first group consisting of datasets of teams that include a specific player and a second group consisting of datasets of teams that do not include a specific player. - It calculates the difference between the statistical value of the estimated result of a specific psychological state calculated for each player in the first group and the statistical value of the estimated result of a specific psychological state calculated for each player in the second group. - Based on the difference in statistical values, it determines whether or not the participation of a specific player is correlated with the psychological state of the entire target team. - If it is determined that there is a correlation, it outputs the analysis results, including whether or not the participation of a specific player is included, as information indicating the characteristics of the psychological state of the entire target team.

[0162] Thus, according to the analysis device 150 of the fourth embodiment, in a game in which multiple players participate, it is possible to analyze the influence of whether or not a particular player participates as a characteristic of the psychological state of the entire target team.

[0163] [Fifth Embodiment] The fourth embodiment described above focused on the relationship between the presence or absence of a specific player and the estimated psychological state of the entire target team. In contrast, the fifth embodiment describes the case in which the analysis focuses on the relationship between the role assigned to a specific player (teammate) within the target team (e.g., leader, sub-leader, etc.) and the estimated psychological state of the entire target team. The fifth embodiment will be described below, focusing on the differences from the fourth embodiment.

[0164] <Details of the Data Analysis Unit> First, the details of the data analysis unit 154 implemented in the analysis device 150 will be explained. Figure 21 is a diagram showing the details of the functional configuration of the data analysis unit of the analysis device according to the fifth embodiment. The data analysis unit 154 of the analysis device 150 according to the fifth embodiment analyzes whether the role assigned to a specific player within a target team correlates with the overall psychological state of the target team. To achieve this analysis objective, the data analysis unit 154 in the fifth embodiment has a team designation unit 2101, a player designation unit 2102, and a role designation unit 2103, as shown in Figure 21. In addition, the data analysis unit 154 in the fifth embodiment has a search method determination unit 2104, a search unit 2105, a calculation unit 2106, a correlation determination unit 2107, and an output unit 2108.

[0165] Furthermore, as in the fourth embodiment, in this embodiment as well, the data storage unit 155 stores multiple datasets designated by reference numerals 200 to 261, as shown in Figure 2 in the first embodiment. The multiple datasets include at least: - A dataset of the same player combination (player names: A, B, C) as shown in Figure 2, when playing against the same opposing team on different days; - A dataset of the same player combination (player names: A, B, C) as shown in Figure 2, when playing against a different opposing team; - A dataset of a different player combination (for example, player names: A, G, C) than the player combination (player names: A, B, C) shown in Figure 2, when playing against the same opposing team; - A dataset of a different player combination (for example, player names: A, G, C) than the player combination (player names: A, B, C) shown in Figure 2, when playing against a different opposing team; and so on. Note that "different opposing teams" here includes cases where the teams themselves are different, and cases where the teams themselves are the same, but the combination of players on those teams is different.

[0166] The team designation unit 2101 receives the player names of players from a specific team from the analyst 160 and notifies the search method determination unit 2104.

[0167] The player designation unit 2102 receives a designation of the player name of a specific player on a specific team from the analyst 160 and notifies the search method determination unit 2104.

[0168] The role assignment unit 2103 accepts a designation for a role assigned to a specific player within a team. If a specific player has previously been assigned multiple different roles within a team, the role assignment unit 2103 accepts a designation for two roles to be compared. The role assignment unit 2103 notifies the search method determination unit 2104 of the information indicating the two accepted roles (information indicating the first role, information indicating the second role).

[0169] The search method determination unit 2104 determines a search method for searching the data storage unit 155 based on: - the player names of players of a specific team notified by the team designation unit 2101; - the player names of specific players notified by the player designation unit 2102; and - information indicating two types of roles (information indicating a first role, information indicating a second role) notified by the role designation unit 2103. In the fifth embodiment, the search method determination unit 2104 determines a search method that: - searches for a dataset containing a specific team from a plurality of datasets stored in the data storage unit 155; - ​​searches for a dataset from the searched dataset where a specific player was assigned a first role within the team; and - searches for a dataset from the searched dataset where a specific player was assigned a second role within the team.

[0170] The search unit 2105 notifies the data storage unit 155 of a search request and obtains the search results based on the search method notified by the search method determination unit 2104. In the fifth embodiment, the search unit 2105 notifies the calculation unit 2106 of the following: - Search results obtained by searching for a dataset containing a specific team from among a plurality of datasets stored in the data storage unit 155, where a specific player was assigned a first role within the team; and - Search results obtained by searching for a dataset containing a specific team from among a plurality of datasets stored in the data storage unit 155, where a specific player was assigned a second role within the team.

[0171] The calculation unit 2106 classifies the search results notified by the search unit 2105 into: a first group, which is a group of datasets where a specific player was assigned a first role within the team; and a second group, which is a group of datasets where a specific player was assigned a second role within the team.

[0172] Furthermore, the calculation unit 2106 statistically processes the estimation results of specific psychological states (concentration) for players whose player names are notified by the team designation unit 2101, from among the estimation results of psychological states included in the dataset classified into the first group. As a result, the calculation unit 2106 calculates a statistical value (mean value).

[0173] Similarly, the calculation unit 2106 statistically processes the estimation results of specific psychological states (concentration) for players whose player names are notified by the team designation unit 2101, from among the estimation results of psychological states included in the dataset classified into the second group. Based on this, the calculation unit 2106 calculates a statistical value (mean).

[0174] Furthermore, the calculation unit 2106 calculates the difference between: • the statistical value of the estimated result of a specific psychological state (e.g., average concentration level) calculated for each player in the first group, and • the statistical value of the estimated result of a specific psychological state (e.g., average concentration level) calculated for each player in the second group.

[0175] The correlation determination unit 2107 determines whether there is a correlation between the role assigned to a specific player within the target team and the estimated psychological state of the entire target team by determining whether the difference calculated by the calculation unit 2106 is above a predetermined threshold. If the correlation determination unit 2107 determines that there is a correlation, it notifies the output unit 2108 of the determination result.

[0176] When the correlation determination unit 2107 notifies the output unit 2108 of the determination result, it outputs an analysis result that includes "the role assigned to a specific player within the target team" as information indicating the characteristics of the psychological state of the entire target team.

[0177] <Specific Examples of Search Methods and Examples of Statistical Value Calculation> Next, specific examples of search methods determined by the search method determination unit 2104 and examples of statistical value calculations calculated by the calculation unit 2106 will be described. Figure 22 is a second figure showing an example of a search method and an example of statistical value calculation.

[0178] In Figure 22, reference numeral 2200 indicates: - The player names (= A, B, C) of players on a specific team, notified by the team designation unit 2101; - The player name (= A) of a specific player, notified by the player designation unit 2102; and - The two types of roles (first role = role I, second role = role II) assigned to a specific player within the team, notified by the role designation unit 2103.

[0179] According to the search method determined by the search method determination unit 2104, - A dataset containing a specific team consisting of player names A, B, and C is searched from among multiple datasets stored in the data storage unit 155. - From the dataset containing a specific team consisting of player names A, B, and C, code 2220 is searched as the dataset where player A was given a first role = role I within the team. - A dataset containing a specific team consisting of player names A, B, and C is searched from among multiple datasets stored in the data storage unit 155. - From the dataset containing a specific team consisting of player names A, B, and C, code 2240 is searched as the dataset where player A was given a second role = role II within the team.

[0180] The example in Figure 22 shows that the win / loss record for each stage, which includes each point in time that was explored, was read from the scene contents (reference numerals 2210, 2230) stored in the data storage unit 155 (reference numerals 2211-2213, 2231-2233).

[0181] Furthermore, according to the calculation unit 2106, the average concentration level is calculated as a statistical value obtained by statistically processing the estimated results of specific psychological states (concentration) for each player named A, B, and C, based on the dataset shown in reference numeral 2220 (reference numeral 2221), and the average concentration level is calculated as a statistical value obtained by statistically processing the estimated results of specific psychological states (concentration) for each player named A, B, and C, based on the dataset shown in reference numeral 2240 (reference numeral 2241).

[0182] <Analysis Processing Flow by Data Analysis Unit> Next, the analysis processing flow by the data analysis unit 154 in the fifth embodiment will be described. Figure 23 is an example of the fifth flowchart showing the analysis processing flow by the data analysis unit.

[0183] In step S2301, the team designation unit 2101 of the data analysis unit 154 accepts the designation of the player name of a player from a specific team.

[0184] In step S2302, the player designation unit 2102 of the data analysis unit 154 accepts the designation of a specific player from a specific team.

[0185] In step S2303, the role assignment unit 2103 of the data analysis unit 154 accepts assignments for two types of roles assigned to a specific player within the team.

[0186] In step S2304, the search unit 2105 of the data analysis unit 154 searches for a dataset containing a specific team from among multiple datasets stored in the data storage unit 155. Furthermore, the search unit 2105 of the data analysis unit 154 searches for a dataset from among the datasets containing the specific team that represents the case where a specific player was assigned a first role within the team.

[0187] In step S2305, the search unit 2105 of the data analysis unit 154 searches for a dataset containing a specific team from among multiple datasets stored in the data storage unit 155. Furthermore, the search unit 2105 of the data analysis unit 154 searches for a dataset from among the datasets containing the specific team that represents the case where a specific player was given a second role within the team.

[0188] In step S2306, the calculation unit 2106 of the data analysis unit 154 statistically processes the estimation results of the specific psychological state of each player for the first group, which is a group of datasets when a first role was assigned. As a result, the calculation unit 2106 of the data analysis unit 154 calculates statistical values ​​of the estimation results of the specific psychological state.

[0189] In step S2307, the calculation unit 2106 of the data analysis unit 154 statistically processes the estimation results of the specific psychological state of each player for the second group, which is the group of datasets when a second role was assigned. As a result, the calculation unit 2106 of the data analysis unit 154 calculates statistical values ​​of the estimation results of the specific psychological state.

[0190] In step S2308, the calculation unit 2106 of the data analysis unit 154 calculates the difference between the statistical value calculated for the first group and the statistical value calculated for the second group.

[0191] In step S2309, the correlation determination unit 2107 of the data analysis unit 154 determines whether there is a correlation between the role assigned to a specific player within the target team and the estimated psychological state of the entire target team. If the difference calculated in step S2108 is greater than or equal to a predetermined threshold, it is determined that there is a correlation between the role assigned to a specific player within the target team and the estimated psychological state of the entire target team. In other words, the correlation determination unit 2107 of the data analysis unit 154 determines YES in step S2309 and proceeds to step S2310.

[0192] On the other hand, if the difference calculated in step S2308 is less than a predetermined threshold, the correlation determination unit 2107 of the data analysis unit 154 determines that there is no correlation between the role assigned to a specific player within the target team and the estimated result of the overall psychological state of the target team. In other words, the correlation determination unit 2107 of the data analysis unit 154 determines NO in step S2309 and proceeds to step S2311.

[0193] In step S2310, the output unit 2108 of the data analysis unit 154 outputs the role assigned to a specific player within the target team as information indicating the characteristics of the overall psychological state of the target team.

[0194] In step S2311, the data analysis unit 154 determines whether to continue the analysis process. If it determines to continue (if the answer is YES in step S2311), it returns to step S2301. On the other hand, if it determines not to continue (if the answer is NO in step S2311), it terminates the analysis process.

[0195] <Example of Analysis Result Output> Next, an example of the analysis result output by the output unit 1707 of the data analysis unit 154 will be described. Figure 24 is the sixth figure showing an example of the analysis result output.

[0196] As shown in Figure 24, the analysis results 2400 include the following information items: "game genre," "specific player attributes," "correlation judgment result," "countermeasures," and "necessary functions."

[0197] The “Game Genre” field stores the genre of the game in which a particular team participated. The “Specific Player Attributes” field stores the attributes of a specific player on a specific team, indicating the allied player.

[0198] The "correlation determination results" store the roles assigned to specific players within the target team that were determined to be correlated, as well as the estimated psychological state of the entire target team.

[0199] The "Countermeasures" section stores the countermeasures taken to improve team composition based on the "Correlation Judgment Results." The "Required Functions" section stores the functions that should be added to each player's gaming PC within a specific team, based on the "Countermeasures."

[0200] <Summary> As is clear from the above explanation, the analysis device 150 according to the fifth embodiment: - In a game in which multiple players participate, it estimates the psychological state of each player on each team at each point in time during gameplay and stores a dataset of the estimation results for each team. - From among the multiple datasets, it searches for a dataset of a specific team in which a specific player is given a first role within the team and classifies it into the first group. - From among the multiple datasets, it searches for a dataset of a specific team in which a specific player is given a second role within the team and classifies it into the second group. - It calculates the difference between the statistical value of the estimation result of a specific psychological state calculated for each player in the first group and the statistical value of the estimation result of a specific psychological state calculated for each player in the second group. - Based on the difference in statistical values, it determines whether the role that a specific player was given within the team is correlated with the psychological state of the entire team. - If it is determined that there is a correlation, it outputs the analysis results including the role that the specific player was given within the team as information indicating the characteristics of the psychological state of the entire team.

[0201] Thus, according to the analysis device 150 of the fifth embodiment, in a game in which multiple players participate, it is possible to analyze the influence of the role assigned to a specific player within the target team as a characteristic of the psychological state of the entire target team.

[0202] [Other Embodiments] The second to fifth embodiments described above describe cases in which the characteristics of the psychological state of a target player or the characteristics of the psychological state of the entire target team are analyzed without limiting the scene content or play content. However, even in the second to fifth embodiments described above, the configuration may be limited to a specific scene or specific play content in order to analyze the characteristics of the psychological state of a target player or the characteristics of the psychological state of the entire target team.

[0203] Furthermore, the fourth and fifth embodiments described above explained the case where the average value is calculated for each group for a specific psychological state. However, the system may be configured to analyze the characteristics of all psychological states, rather than being limited to specific psychological states. Also, the system may be configured to calculate other statistical values, rather than being limited to calculating the average value.

[0204] It should be noted that the present invention is not limited to the configurations shown in the above embodiments, including combinations with other elements. These aspects can be modified without departing from the spirit of the present invention and can be appropriately determined according to their application.

[0205] This application claims priority based on Japanese Patent Application No. 2025-054920, filed on 28 March 2025, which is incorporated herein by reference to the entire contents of the said Japanese Patent Application.

[0206] 110_1 to 110_3: Player 120_1 to 120_3: Gaming PC 130_1 to 130_3: Player 140_1 to 140_3: Gaming PC 150: Analysis device 151: Scene content acquisition unit 152: Play content acquisition unit 153: Psychological state estimation unit 154: Data analysis unit 401, 901, 1301: Player specification unit 402: Scene specification unit 403, 903, 1303, 1703, 2104: Search method determination unit 404, 904, 1304, 1704, 2105: Search unit 405, 905, 1305, 1706, 2107: Correlation determination unit 406, 906, 1306, 1707, 2108: Output Unit 902: Psychological State Specification Unit 1302: Synchronization Specification Unit 1701: First Player Specification Unit 1702: Second Player Specification Unit 1705, 2106: Calculation Unit 2101: Team Specification Unit 2102: Player Specification Unit 2103: Role Specification Unit

Claims

1. An analysis device comprising: an estimation unit that estimates the psychological state of a target player at each point in time during gameplay in a game involving multiple players; an acquisition unit that acquires the gameplay content at each point in time of a specific player other than the target player among the multiple players; a determination unit that searches for gameplay content of a specific scene among the acquired gameplay content at each point in time, determines the correlation between the estimated result of the target player's psychological state at the time the searched gameplay content occurred and the gameplay content of the searched specific scene; and an output unit that outputs the gameplay content of the specific scene that has been determined to have a correlation as information indicating the characteristics of the target player's psychological state.

2. The analysis device according to claim 1, wherein the gameplay of the specific scene is the gameplay of the specific scene by an opposing player among the plurality of players who is playing against the target player in the game.

3. The analysis device according to claim 1, wherein the gameplay of the specific scene is the gameplay of the specific scene by a player who is an ally of the target player among the plurality of players in the game.

4. The analysis device according to claim 1, further comprising a designation unit that specifies information indicating a specific scene, wherein the determination unit searches for the content of play of the specific scene based on the information indicating the content of play of the specific scene specified by the designation unit.

5. An analysis device comprising: an estimation unit that estimates the psychological state of a target player at each point in time during gameplay and the psychological state of a specific player on the same team as the target player at each point in time during gameplay; a determination unit that determines the correlation between the estimation result of a specific psychological state among the estimation results of the specific player's psychological state at each point in time during gameplay and the estimation result of the target player's psychological state at the time the specific psychological state was estimated; and an output unit that outputs the estimation result of the specific psychological state that has been determined to have a correlation as information indicating the characteristics of the target player's psychological state.

6. An analysis device comprising: an estimation unit that estimates the psychological state of a target player at each point in time during gameplay and the psychological state of multiple specific players on the same team as the target player at each point in time during gameplay; a determination unit that determines the correlation between the estimated result of the synchronized psychological state among the estimated results of the multiple specific players' psychological states at each point in time during gameplay and the estimated result of the target player's psychological state at the time when their psychological states are synchronized; and an output unit that outputs the estimated result of the synchronized psychological state, which has been determined to have a correlation, as information indicating the characteristics of the target player's psychological state.

7. An analysis device comprising: an estimation unit that estimates the psychological state of a player on a specific team at each point in time during a game in which multiple players participate; a calculation unit that classifies a dataset of estimation results for the specific team into a first group consisting of datasets in which the specific player is included and a second group consisting of datasets in which the specific player is not included, and calculates the difference between the statistical value of the estimated psychological state of the specific player calculated for each player in the first group and the statistical value of the estimated psychological state of the specific player calculated for each player in the second group; a determination unit that determines the correlation between the presence or absence of the specific player's participation and the overall psychological state of the team based on the difference in statistical values; and an output unit that, if a correlation is determined to exist, outputs the presence or absence of the specific player's participation as information indicating the characteristics of the overall psychological state of the team.

8. An analysis device comprising: an estimation unit that estimates the psychological state of a player on a specific team at each point in time during a game in which multiple players participate; a calculation unit that classifies the dataset of estimation results for the specific team into a first group consisting of datasets where the specific player on the specific team is given a first role, and a second group consisting of datasets where the specific player on the specific team is given a second role, and calculates the difference between the statistical value of the estimated psychological state calculated for each player in the first group and the statistical value of the estimated psychological state calculated for each player in the second group; a determination unit that determines the correlation between the role given to the specific player within the specific team and the overall psychological state of the team based on the difference in statistical values; and an output unit that, if a correlation is determined to exist, outputs the role given to the specific player within the specific team as information indicating the characteristics of the overall psychological state of the team.

9. An analysis method in which a computer performs the following steps: estimates the psychological state of a target player at each point in time during gameplay in a game in which multiple players participate; acquires the gameplay content at each point in time of a specific player other than the target player among the multiple players; searches for gameplay content of a specific scene among the acquired gameplay content at each point in time; determines the correlation between the estimated result of the target player's psychological state at the time the searched gameplay content occurred and the gameplay content of the searched specific scene; and outputs the gameplay content of the specific scene that is determined to have a correlation as information indicating the characteristics of the target player's psychological state.

10. An analysis program for a computer to perform the following steps: estimate the psychological state of a target player at each point in time during gameplay in a game in which multiple players participate; acquire the gameplay content at each point in time of a specific player other than the target player among the multiple players; search for gameplay content of a specific scene among the acquired gameplay content at each point in time; determine the correlation between the estimated psychological state of the target player at the time the searched gameplay content occurred and the gameplay content of the searched specific scene; and output the gameplay content of the specific scene that is determined to have a correlation as information indicating the characteristics of the psychological state of the target player.

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