Gaming content recommendation for a video game

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.