SYSTEMS AND METHODS FOR COMBINING TOP-DOWN AND BOTTOM-UP TEAM AND PLAYER PREDICTION FOR SPORTS
A method of generating predictions for teams and players for each team associated with a sporting event, the method including: receiving one or more top-down predictions for the sporting event; providing the top-down predictions as one or more top-down feature vectors to a computing system; receiving, by the computing system, a second set of feature vectors comprising data for one or more players associated with one or more respective teams and data for one or more teams associated with a sporting event; inputting the one or more top-down feature vectors and second set of feature vectors into a transformer-based neural network; and generating, using the transformer-based neural network, one or more predictions for the sporting event based on the one or more top-down feature vectors and the second set of feature vectors.
1 . A method of generating predictions for teams and players for each team associated with a sporting event, the method comprising:
receiving one or more top-down predictions related to the sporting event;
providing the top-down predictions as one or more top-down feature vectors to a computing system;
receiving, by the computing system, a second set of feature vectors comprising data for one or more players associated with one or more respective teams and data for one or more teams associated with a sporting event;
inputting the one or more top-down feature vectors and second set of feature vectors into a transformer-based neural network; and
generating, using the transformer-based neural network, one or more predictions for the sporting event based on the one or more top-down feature vectors and the second set of feature vectors.
2 . The method of claim 1 , wherein the one or more top-down predictions are one or more of a neural network output, market information, or game context information.
3 . The method of claim 1 , wherein the top-down predictions comprise a first top-down prediction based on pre-game data and a second top-down prediction based on in-play data.
4 . The method of claim 1 , further comprising:
causing the one or more predictions for the sporting event to be displayed on a display device.
5 . The method of claim 1 , wherein the transformer-based neural network further includes:
a set of embedding layers;
transformer encoder layers; and
fully connected layers.
6 . The method of claim 1 , wherein the data for one or more players comprises actions of one or more agents on a playing surface received from a tracking device.
7 . The method of claim 1 , further comprising:
receiving, from a tracking device, updated data for the one or more players or teams;
providing the updated data to the transformer-based neural network; and
generating an updated one or more predictions for the sporting event based on the updated data.
8 . The method of claim 1 , further comprising:
accessing, using a trigger processing step, a data platform at a set interval to determine when the sporting event occurs; and
creating, using a feature creator processing step, the second set of feature vectors by querying data from the data platform.
9 . A system for generating predictions for teams and players for each team associated with a sporting event, the system comprising:
a non-transitory computer readable medium configured to store processor-readable instructions; and
a processor operatively connected to the non-transitory computer readable medium, and configured to execute the instructions to perform operations comprising:
receiving one or more top-down predictions related to the sporting event;
providing the top-down predictions as one or more top-down feature vectors to a computing system;
receiving, by the computing system, a second set of feature vectors comprising data for one or more players associated with one or more respective teams and data for one or more teams associated with a sporting event;
inputting the one or more top-down feature vectors and second set of feature vectors into a transformer-based neural network; and
generating, using the transformer-based neural network, one or more predictions for the sporting event based on the one or more top-down feature vectors and the second set of feature vectors.
10 . The system of claim 9 , wherein the one or more top-down predictions are one or more of a neural network output, market information, or game context information.
11 . The system of claim 9 , wherein the top-down predictions comprise a first top-down prediction based on pre-game data and a second top-down prediction based on in-play data.
12 . The system of claim 9 , wherein the operations further comprise:
causing the one or more predictions for the sporting event to be displayed on a display device.
13 . The system of claim 9 , wherein the transformer-based neural network includes:
a set of embedding layers;
transformer encoder layers; and
fully connected layers.
14 . The system of claim 9 , wherein the data for one or more players comprises actions of one or more agents on a playing surface received from a tracking device.
15 . The system of claim 9 , wherein the operations further comprise:
receiving, from a tracking device, updated data for one or more players or teams;
providing the updated data to the transformer-based neural network; and
generating an updated one or more predictions for the sporting event based on the updated data.
16 . The system of claim 9 , further comprising:
accessing, using a trigger processing step, a data platform at a set interval to determine when the sporting event occurs; and
creating, using a feature creator processing step, the second set of feature vectors by querying data from the data platform.
17 . A non-transitory computer readable medium configured to store processor-readable instructions, wherein when executed by a processor, the instructions perform operations comprising:
receiving one or more top-down predictions related to the sporting event;
providing the top-down predictions as one or more top-down feature vectors to a computing system;
receiving, by the computing system, a second set of feature vectors comprising data for one or more players associated with one or more respective teams and data for one or more teams associated with a sporting event;
inputting the one or more top-down feature vectors and second set of feature vectors into a transformer-based neural network; and
generating, using the transformer-based neural network, one or more predictions for the sporting event based on the one or more top-down feature vectors and the second set of feature vectors.
18 . The non-transitory computer readable medium of claim 17 , wherein the one or more top-down predictions are one or more of a neural network output, market information, or game context information.
19 . The non-transitory computer readable medium of claim 17 , wherein the top-down predictions comprise a first top-down prediction based on pre-game data and a second top-down prediction based on in-play data.
20 . The non-transitory computer readable medium of claim 17 , wherein the operations further comprise:
causing the one or more predictions for the sporting event to be displayed on a display device.