Abstract: A computing system receives data for a game. The data includes at least one of tracking data or event data. Based on the data for the game, the computing system determines that an event has occurred within the game. Based on the determining, the computing system generates a graphic responsive to the event. The graphic includes insights related to the event. The computing system recommends an image relevant to the event based on metatags associated with the event. The computing system generates a visual element by merging the image and the graphic.

Abstract: A computing system receives a video stream of a game. The computing system generates tracking data corresponding to the video stream using one or more artificial intelligence models. The computing system generates interactive video data by combining the video stream of the game with the tracking data. The computing system causes a media player to render graphics corresponding to the tracking data over the video stream by sending the interactive video data to a client device executing the media player.

Abstract: A computing system generates a portal to be accessed by a plurality of users. The portal includes a representation of a game and a plurality of gamification elements. The computing system receives data related to the game represented in the portal. The computing system monitors the data to detect an event to occur within the game. Based on the monitoring, the computing system determines that the event has occurred within the game. Based on the determining, the computing system generates a graphic associated with the event. The computing system generates a non-fungible token corresponding to the event. The non-fungible token is linked to the graphic. The computing system broadcasts the non-fungible token to a blockchain.

Abstract: A computing system receives a video stream of a game. The computing system generates tracking data corresponding to the video stream using one or more artificial intelligence models. The computing system generates interactive video data by combining the video stream of the game with the tracking data. The computing system causes a media player to render graphics corresponding to the tracking data over the video stream by sending the interactive video data to a client device executing the media player.

Abstract: A computing system identifies data related to a tennis match between a first player and a second player. The data includes a current match state and a current in-match performance. The computing system generates an input data set that includes the data related to the tennis match. The generating includes modifying the current match state to assume that the first player will win a next point in the tennis match. Based on the input data set, the computing system measures an importance of the next point to the first player winning the tennis match.

Abstract: A computing system generates an interactive game space for predicting an outcome of an event during a live game. The computing system identifies a prediction event in the live game. The computing system receives event data for the live game up to the prediction event. The computing system identifies pre-game player specific data for each player involved in the prediction event. The computing system generates a probability distribution for a set of possible outcomes for the prediction event based on the event data and the pre-game player specific data. The computing system presents the probability distribution to a user participating in the interactive game space. The computing system receives a proposed outcome for the prediction event from the user participating in the interactive game space. The computing system determines that the proposed outcome was correct. The computing system grants points to the user within the interactive game space.

Abstract: A computing system receives data for a game. The data includes at least one of tracking data or event data. Based on the data for the game, the computing system determines that an event has occurred within the game. Based on the determining, the computing system generates a graphic responsive to the event. The graphic includes insights related to the event. The computing system recommends an image relevant to the event based on metatags associated with the event. The computing system generates a visual element by merging the image and the graphic.

Abstract: A computing system receives live event data corresponding to a live game. The live event data includes events occurring within the live game. The computing system analyzes the live event data to identify a potential error in the live event data. The computing system generates a ticket corresponding to the potential error flagged in the live event data. The computing system assigns the ticket to a first quality assurance agent to resolve. The computing system receives an indication that the ticket has been reviewed by the first quality assurance agent. the computing system provides the reviewed event data to an end user.

Abstract: A computing system receives a video stream of a game. The computing system generates tracking data corresponding to the video stream using one or more artificial intelligence models. The computing system generates interactive video data by combining the video stream of the game with the tracking data. The computing system causes a media player to render graphics corresponding to the tracking data over the video stream by sending the interactive video data to a client device executing the media player.

Abstract: A computing system receives a proposed bet selection for an event. The proposed bet selection includes team information and opponent information. The computing system generates a plurality of queries by analyzing the proposed bet selection. The computing system retrieves historical data related to the proposed bet selection based on the plurality of queries. The computing system analyzes the historical data to generate a plurality of insights related to the proposed bet selection. The computing system provides the historical data and the plurality of insights to a user submitting the proposed bet selection.

Abstract: A computing system receives event data for a game. The computing system generates a plurality of artificial intelligence driven metrics based on the event data. The computing system generates a plurality of insights via one or more machine learning models based on the event data and the plurality of artificial intelligence driven metrics. The computing system ranks the plurality of insights using one or more artificial intelligence techniques. The computing system generates a graphical user interface comprising the event data and at least one insight of the plurality of insights. The computing system causes a user device to display the graphical user interface.

Abstract: A computing system receives pre-match data for an upcoming match between a first player and a second player. The computing system generates, using one or more prediction models, one or more pre-match predictions based on the pre-match data. The computing system receives in-match data for the match currently in progress. The computing system generates, using the one or more prediction models, one or more live match predictions based on the in-match data.

Abstract: A computing system receives a pre-game lineup against a target opponent. The pre-game lineup includes a representation of each player starting a game against the target opponent. The computing system retrieves a first set of historical data for each player in the pre-game lineup and team-specific information. The computing system retrieves a second set of historical data for each player of the target opponent and target opponent-specific information. The computing system predicts an outcome for the game based on the first set of historical data and the second set of historical data. The computing system projects a future effect of the pre-game lineup on at least one season of play by simulating team and player performance. The computing system generates a graphical output reflecting the predicted outcome of the game and the simulation of team and player performance over the at least one season of play.

Abstract: A method is disclosed herein. A computing system receives a data feed for an event. The data feed includes real-time player and team information. The computing system generates a feature representation of the data feed. The computing system generates micro predictions for the event. The micro predictions for the event are associated with predictions at a match level. The computing system generates macro predictions for each team involved in the event. The macro predictions are associated with predictions across one or more seasons. The computing system generates an output. The output includes the micro predictions and the macro predictions.

Abstract: A method for delivering interactive video to a user is disclosed herein. A computing system identifies video contents corresponding to a sporting event. The video contents include a plurality of video frames. The computing system annotates each video frame of the plurality of video frames to uniquely identify the video frame and contents contained therein. The computing system receives, from a plurality of prediction models, a plurality of data inputs related to agents and actions captured in each video frame of the plurality of video frames. The computing system generates a plurality of data frames based on the plurality of data inputs. The computing system associates each data frame with a respective video frame using the annotations. The computing system causes a user device to present the interactive video to the user by instructing the user device to merge the plurality of data frames with the plurality of video frames.