SYSTEMS AND METHODS FOR GENERATING SPORTS MEDIA CONTENT FOR AN INTERACTIVE DISPLAY
A method may include receiving data for a game, the data comprising at least one of tracking data or event data. The method may include determining an occurrence of a trigger event within the game based on the data for the game. The method may include providing the data for the game and the occurrence of the trigger event to a first machine learning (ML) model, where the first ML model is trained to generate a graphic based on the data for the game and the occurrence of the trigger event. The method may include receiving, from the first ML model, the graphic, and generating a visual element including the graphic for presentation within a user interface. The visual element may be configured to include an interactive element or be positioned adjacent to the interactive element within the user interface.
1 . A method comprising:
receiving, by a computing system, data for a game, the data comprising at least one of tracking data or event data;
determining, by the computing system, an occurrence of a trigger event within the game based on the data for the game;
providing the data for the game and the occurrence of the trigger event to a first machine learning model, wherein the first machine learning model is trained to generate a graphic based on the data for the game and the occurrence of the trigger event;
receiving, from the first machine learning model, the graphic based on the data for the game and the occurrence of the trigger event within the game; and
generating, by the computing system, a visual element including the graphic for presentation within a user interface, the visual element being configured to include an interactive element or be positioned adjacent to the interactive element within the user interface.
2 . The method of claim 1 , wherein the trigger event is a pre-determined trigger event type.
3 . The method of claim 1 , further comprising:
dynamically determining, by the computing system and using a second machine learning model, the trigger event.
4 . The method of claim 1 , wherein the graphic is generated further based on one or more of user data, a statistic, or broadcast video data.
5 . The method of claim 4 , wherein the user data represents one or more of user preference data or user behavioral data.
6 . The method of claim 1 , further comprising:
receiving, using the computing system, broadcast video data for the game; and
determining, using a second machine learning model, a segment of the broadcast video data associated with the graphic, wherein the visual element includes the segment of the broadcast video data or a link to the segment of the broadcast video data.
7 . The method of claim 1 , further comprising:
receiving the interactive element, wherein the interactive element represents at least one of a market-based prediction offer, an advertisement, a questionnaire, or a poll, wherein the interactive element was selected based on one or more of the visual element, the graphic, or user data.
8 . The method of claim 1 , further comprising:
outputting, using a second machine learning model, the event data.
9 . The method of claim 1 , wherein the visual element is generated in less than 30 seconds.
10 . A non-transitory computer readable medium comprising one or more sequences of instructions, which, when executed by one or more processors, causes a computing system to perform operations comprising:
receiving, by the computing system, data for a game, the data comprising at least one of tracking data or event data;
determining, by the computing system, an occurrence of a trigger event within the game based on the data for the game;
providing the data for the game and the occurrence of the trigger event to a first machine learning model, wherein the first machine learning model is trained to generate a graphic based on the data for the game and the occurrence of the trigger event;
receiving, from the first machine learning model, the graphic based on the data for the game and the occurrence of the trigger event within the game; and
generating, by the computing system, a visual element including the graphic for presentation within a user interface, the visual element being configured to include an interactive element or be positioned adjacent to the interactive element within the user interface.
11 . The non-transitory computer readable medium of claim 10 , wherein the trigger event is a pre-determined trigger event type.
12 . The non-transitory computer readable medium of claim 10 , wherein the operations further comprise:
dynamically determining, by the computing system and using a second machine learning model, the trigger event.
13 . The non-transitory computer readable medium of claim 10 , wherein the graphic is generated further based on one or more of user data, a statistic, or broadcast video data.
14 . The non-transitory computer readable medium of claim 13 , wherein the user data represents one or more of user preference data or user behavioral data.
15 . The non-transitory computer readable medium of claim 10 , wherein the operations further comprise:
receiving, using the computing system, broadcast video data for the game; and
determining, using a second machine learning model, a segment of the broadcast video data associated with the graphic; and wherein the visual element includes the segment of the broadcast video data or a link to the segment of the broadcast video data.
16 . The non-transitory computer readable medium of claim 10 , wherein the operations further comprise:
receiving the interactive element, wherein the interactive element represents at least one of a market-based prediction offer, an advertisement, a questionnaire, or a poll, and wherein the interactive element was selected based on one or more of the visual element, the graphic, or user data.
17 . The non-transitory computer readable medium of claim 10 , wherein the operations further comprise:
outputting, using a second machine learning model, the event data.
18 . The non-transitory computer readable medium of claim 10 , wherein the visual element is generated in less than 30 seconds.
19 . A computing system, comprising:
a processor; and
a memory having programming instructions stored thereon, which, when executed by the processor, causes the computing system to perform operations comprising:
receiving, by the computing system, data for a game, the data comprising at least one of tracking data or event data;
determining, by the computing system, an occurrence of a trigger event within the game based on the data for the game;
providing the data for the game and the occurrence of the trigger event to a first machine learning model, wherein the first machine learning model is trained to generate a graphic based on the data for the game and the occurrence of the trigger event;
receiving, from the first machine learning model, the graphic based on the data for the game and the occurrence of the trigger event within the game; and
generating, by the computing system, a visual element including the graphic for presentation within a user interface, the visual element being configured to include an interactive element or be positioned adjacent to the interactive element within the user interface.
20 . The computing system of claim 19 , wherein the operations further comprise:
dynamically determining, by the computing system and using a second machine learning model, the trigger event.