Gaming content recommendation for a video game
Systems and methods for providing game content recommendation of a video game based on player's performance are disclosed. Prior to an actual video game play, a performance metric is calculated based on a stored player data and video settings of the game. The performance metric is evaluated to further calculate a performance metric of video game play session content indicative of aspects of actual video game play. A metrics data of each player in determined from the video game play session content. The player metrics data is analyzed relative to the stored player data and the video settings of the game to determine whether to recommend the video game play session content.
1 . A computer-implemented method for automatically recommending for display video game play session content of a present video game play session, the method comprising:
calculating a plurality of pre-game performance metrics of each player of a plurality of teams associated with a video game, based at least in part on stored player data including game play input received via a user interface during a previous video game play session;
generating, using a server, a predictive average value of aggregated pre-game performance metrics of each player of the plurality of teams associated with the video game, wherein the predictive average value is generated by the server using an algorithm that weighs and combines analyzed player performance metrics according to settings and player roles associated with the video game, based at least in part on the stored player data;
determining whether the predictive average value associated with each player of the plurality of teams is greater than a pre-game threshold average value, based at least in part on the stored player data;
in response to determining that the predictive average value is greater than the pre-game threshold average value, updating the pre-game threshold average value with the predictive average value and selecting the stored player data corresponding to the plurality of pre-game performance metrics of the video game for post-game analysis using a video analysis algorithm trained on videos of previous video game play sessions;
receiving at least one game play input, via the user interface, corresponding to the present video game play session of the video game, wherein the at least one game play input is received via at least one of: a video game controller, a keyboard, or a mouse;
retrieving, by the server, in real-time, metadata corresponding to the present video game play session based at least in part on the received at least one game play input, wherein the metadata includes parameters that measure a plurality of in-game performance metrics during the present video game play session, and wherein the server further determines a quality of the present video game play session based at least in part on an average score associated with the plurality of in-game performance metrics;
analyzing, using the video analysis algorithm, the present video game play session to determine whether player data of the plurality of in-game performance metrics, calculated in real time, is substantially the same as the plurality of pre-game performance metrics based at least in part on the stored player data, wherein the plurality of in-game performance metrics are based at least in part on the at least one game play input received via the user interface for the present video game play session, and wherein the plurality of in-game performance metrics are analyzed by the server based at least in part on a game map of the present video game play session and specific in-game performance metrics; and
in response to determining that the plurality of in-game performance metrics are substantially the same as the plurality of pre-game performance metrics and that the quality of the present video game play session exceeds a predetermined threshold, using the server to:
generate for display, on a display of the user interface, a recommendation for a specific segment of the video game play session content of the present video game play session, wherein the specific segment relates to a segment where a player's performance can be most improved, based at least in part on an in-game analysis, and wherein the video game play session content represents the present video game play session.
2 . The computer-implemented method of claim 1 , further comprising determining a genre of the video game.
3 . The computer-implemented method of claim 2 , further comprising calculating the plurality of pre-game performance metrics and the plurality of in-game performance metrics based at least in part on the genre.
4 . The computer-implemented method of claim 1 , further comprising:
in response to determining that the predictive average value is not greater than the pre-game threshold average value:
discarding the video game; and
selecting a different video game for calculating pre-game performance metrics.
5 . The computer-implemented method of claim 1 , further comprising:
in response to determining that the plurality of in-game performance metrics based at least in part on the at least one received game play input are not substantially the same as the plurality of pre-game performance metrics based at least in part on the stored player data:
discarding the video game; and
selecting a different video game for calculating in-game performance metrics.
6 . The computer-implemented method of claim 1 , wherein the performance metrics are calculated based at least in part on video game play session data corresponding to at least one of attacking, defending, damage points, healing, character positioning, route followed, reaction time, crowd controlling, objective capturing and targets destroyed.
7 . The computer-implemented method of claim 1 , wherein the determining whether the player data of the plurality of in-game performance metrics based at least in part on the at least one received game play input is substantially the same as the stored player data comprises:
calculating the plurality of in-game performance metrics for each player of the plurality of teams at a plurality of time intervals.
8 . The computer-implemented method of claim 1 , wherein the user interface is a remote control, a trackball, a keypad, a touchscreen, a touchpad, a stylus input, a joystick, a voice recognition interface, or other user interfaces.
9 . The computer-implemented method of claim 1 , wherein the plurality of in-game performance metrics are based at least in part on the player data including at least one game play input received via the user interface for the present video game play session.
10 . The computer-implemented method of claim 1 , wherein the recommending the specific segment of the video game play session content of the present video game play session via the display of the user interface is performed by the server, and wherein the server is communicatively coupled to a video gaming device.
11 . A system for automatically recommending for display video game play session content of a present video game play session, the system comprising:
a memory; and
a control circuitry configured to:
calculate a plurality of pre-game performance metrics of each player of a plurality of teams associated with a video game, based at least in part on stored player data including game play input received via a user interface during a previous video game play session, wherein the stored player data is stored in the memory;
generate, using a server, a predictive average value of aggregated pre-game performance metrics of each player of the plurality of teams associated with the video game, wherein the predictive average value is generated by the server using an algorithm that weighs and combines analyzed player performance metrics according to settings and player roles associated with the video game, based at least in part on the stored player data;
determine whether the predictive average value associated with each player of the plurality of teams is greater than a pre-game threshold average value, based at least in part on the stored player data;
in response to determining that the predictive average value is greater than the pre-game threshold average value, update the pre-game threshold average value with the predictive average value and selecting the stored player data corresponding to the plurality of pre-game performance metrics of the video game for post-game analysis using a video analysis algorithm trained on videos of previous video game play sessions;
receive at least one game play input, via the user interface, corresponding to the present video game play session of the video game, wherein the at least one game play input is received via at least one of: a video game controller, a keyboard, or a mouse;
retrieve, by the server, in real-time, metadata corresponding to the present video game play session based at least in part on the received at least one game play input, wherein the metadata includes parameters that measure a plurality of in-game performance metrics during the present video game play session, and wherein the server further determines a quality of the present video game play session based at least in part on an average score associated with the plurality of in-game performance metrics;
analyze, using the video analysis algorithm, the present video game play session to determine whether player data of the plurality of in-game performance metrics, calculated in real time, is substantially the same as the plurality of pre-game performance metrics based at least in part on the stored player data, wherein the plurality of in-game performance metrics are based at least in part on the at least one game play input received via the user interface for the present video game play session, and wherein the plurality of in-game performance metrics are analyzed by the server based at least in part on a game map of the present video game play session and specific in-game performance metrics; and
in response to determining that the plurality of in-game performance metrics are substantially the same as the plurality of pre-game performance metrics and that the quality of the present video game play session exceeds a predetermined threshold, using the server to:
generate for display, on a display of the user interface, a recommendation for a specific segment of the video game play session content of the present video game play session, wherein the specific segment relates to a segment where a player's performance can be most improved, based at least in part on an in-game analysis, and wherein the video game play session content represents the present video game play session.
12 . The system of claim 11 , wherein the control circuitry is further configured to determine a genre of the video game.
13 . The system of claim 12 , wherein the control circuitry is further configured to calculate the plurality of pre-game performance metrics and the plurality of in-game performance metrics based at least in part on the genre.
14 . The system of claim 11 , wherein the control circuitry is further configured to:
in response to determining that the predictive average value is not greater than the pre-game threshold average value:
discard the video game; and
select a different video game for calculating pre-game performance metrics.
15 . The system of claim 11 , wherein the control circuitry is further configured to:
in response to determining that the plurality of in-game performance metrics based at least in part on the at least one received game play input are not substantially the same as the plurality of pre-game performance metrics based at least in part on the stored player data:
discard the video game; and
select a different video game for calculating in-game performance metrics.
16 . The system of claim 11 , wherein the control circuitry is configured to calculate the performance metrics based at least in part on video game play session data corresponding to at least one of attacking, defending, damage points, healing, character positioning, route followed, reaction time, crowd controlling, objective capturing and targets destroyed.
17 . The system of claim 11 , wherein the control circuitry is configured to determine whether the player data of the plurality of in-game performance metrics based at least in part on the at least one received game play input is substantially the same as the stored player data by:
calculating the plurality of in-game performance metrics for each player of the plurality of teams at a plurality of time intervals.
18 . The system of claim 11 , wherein the user interface is a remote control, a trackball, a keypad, a touchscreen, a touchpad, a stylus input, a joystick, a voice recognition interface, or other user interfaces.
19 . The system of claim 11 , wherein the plurality of in-game performance metrics are based at least in part on the player data including the at least one game play input received via the user interface for the present video game play session.
20 . The system of claim 11 , wherein the control circuitry is configured to recommend the specific segment of the video game play session content of the present video game play session via the display of the user interface by utilizing a server that is communicatively coupled to a video gaming device.