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    SYSTEMS AND METHODS FOR A COUPLED PLAY, DRIVE, AND MATCH OUTCOME PREDICTION SYSTEM FOR LIVE SPORTS
    2.
    发明公开
    SYSTEMS AND METHODS FOR A COUPLED PLAY, DRIVE, AND MATCH OUTCOME PREDICTION SYSTEM FOR LIVE SPORTS 审中-公开

    公开(公告)号：US20240296358A1

    公开(公告)日：2024-09-05

    申请号：US18593110

    申请日：2024-03-01

    申请人： STATS LLC

    发明人： Lucas Haupt ,  Evan Boyd ,  Matthew Scott ,  Patrick Joseph LUCEY

    IPC分类号： G06N7/01

    CPC分类号： G06N7/01

    摘要： A method for generating coupled play, drive, and game outcome predictions for a sporting event, the method including: inputting features for a sporting event into an initial model, the input features including historical game data and in-game data; determining a predicted outcome for at least one upcoming play with the initial model; determining, using the input features and predicted outcome, a predicted probability of each team winning the sporting event; and determining a probability of success for an action in the at least one upcoming play of the sporting event.

    SYSTEMS AND METHODS FOR COMBINING TOP-DOWN AND BOTTOM-UP TEAM AND PLAYER PREDICTION FOR SPORTS
    4.
    发明公开
    SYSTEMS AND METHODS FOR COMBINING TOP-DOWN AND BOTTOM-UP TEAM AND PLAYER PREDICTION FOR SPORTS 审中-公开

    公开(公告)号：US20240216780A1

    公开(公告)日：2024-07-04

    申请号：US18401023

    申请日：2023-12-29

    申请人： Stats LLC

    发明人： Michael John Horton ,  Nils Sebastiaan Mackaij ,  Daniel Richard Dinsdale ,  Hayley Redgate ,  Daniele Foroni ,  Patrick Joseph LUCEY

    IPC分类号： A63B71/06

    CPC分类号： A63B71/06

    摘要： 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.

    System and Method for Real-Time Minting and Enrichment of Sports Data
    9.
    发明公开
    System and Method for Real-Time Minting and Enrichment of Sports Data 审中-公开

    公开(公告)号：US20240070770A1

    公开(公告)日：2024-02-29

    申请号：US18452954

    申请日：2023-08-21

    申请人： STATS LLC

    发明人： Christian Marko ,  Matjaz Ales ,  Lukas Marek ,  Shaun McMurray ,  Vadim Torosyan ,  Markus Klausmann

    IPC分类号： G06Q30/08 ,  G06Q20/36

    CPC分类号： G06Q30/08 ,  G06Q20/36 ,  G06Q2220/00

    摘要： 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.

    System and method for multi-task learning
    10.
    发明授权
    System and method for multi-task learning 有权

    公开(公告)号：US11900254B2

    公开(公告)日：2024-02-13

    申请号：US18175262

    申请日：2023-02-27

    申请人： STATS LLC

    发明人： Matthew Holbrook ,  Jennifer Hobbs ,  Patrick Joseph Lucey

    IPC分类号： G06N3/08 ,  G06N3/04

    CPC分类号： G06N3/08 ,  G06N3/04

    摘要： A method of generating a multi-modal prediction is disclosed herein. A computing system retrieves event data from a data store. The event data includes information for a plurality of events across a plurality of seasons. Computing system generates a predictive model using a mixture density network, by generating an input vector from the event data learning, by the mixture density network, a plurality of values associated with a next play following each play in the event data. The mixture density network is trained to output the plurality of values near simultaneously. Computing system receives a set of event data directed to an event in a match. The set of event data includes information directed to at least playing surface position and current score. Computing system generates, via the predictive model, a plurality of values associated with a next event following the event based on the set of event data.