公开(公告)号：US20220207366A1

公开(公告)日：2022-06-30

申请号：US17645539

申请日：2021-12-22

申请人： STATS LLC

发明人： Daniel Edison Marley ,  Youssef Nashed ,  Long Sha

IPC分类号： G06N3/08

摘要： A computing system retrieves tracking data from a data store. The tracking data includes a plurality of frames of data for a plurality of events across a plurality of seasons. The computing system converts the tracking data into a plurality of graph-based representations. A graph neural network learns to generate an action prediction for each player in each frame of the tracking data. The computing system generates a trained graph neural network based on the learning. The computing system receives target tracking data for a target event. The target tracking data includes a plurality of target frames. The computing system converts the target tracking data to a plurality of target graph-based representations. Each graph-based representation corresponds to a target frame of the plurality of target frames. The computing system generates, via the trained graph neural network, an action prediction for each player in each target frame.

公开(公告)号：US20210322825A1

公开(公告)日：2021-10-21

申请号：US17226211

申请日：2021-04-09

申请人： STATS LLC

发明人： Daniel Edison Marley ,  Matthew Thomas O'Connor ,  Alexander Nicholas Ottenwess ,  Aiman Sherani ,  Matthew Holbrook

IPC分类号： A63B24/00 ,  G06N3/08 ,  G06N3/04

摘要： A system and method for predicting next pitch are disclosed herein. A computing system retrieves pitch-by-pitch information for a plurality of events and game context information associated with each pitch in the pitch-by-pitch information. The computing system converts the pitch-by-pitch information and the game context information into a plurality of graph-based representation. A graph neural network learns to generate a pitch type prediction for each pitch based on the plurality of graph-based representations. The computing system generates a trained graph neural network based on the learning. The computing system receives a current graph-based representation of current pitch-by-pitch information for a current pitcher and current game context information. The computing system predicts, via the trained graph neural network, a pitch type for the next pitch to be delivered from the current pitcher.

公开(公告)号：US20220253679A1

公开(公告)日：2022-08-11

申请号：US17649970

申请日：2022-02-04

申请人： STATS LLC

发明人： Paul David Power ,  Thomas Seidl ,  Michael Stöckl ,  Daniel Edison Marley

IPC分类号： G06N3/04 ,  G06N3/08

摘要： A computing system retrieves tracking data from a data store. The computing system converts the tracking data into a plurality of graph-based representations. The prediction engine learns to model defensive behavior based on the plurality of graph-based representations. The computing system generates a trained prediction engine based on the learnings. The computing system receives target tracking data for a target event. The target tracking data includes a plurality of target frames. The computing system converts the target tracking data to a plurality of target graph-based representations. The computing system models, via the trained graph neural network, defensive behavior of a team in the target event based on plurality of graph-based representations.