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Method and system for interactive, interpretable, and improved match and player performance predictions in team sports

A team and player technique used in the field of predicting pre- and in-game results

Pending Publication Date: 2021-01-26
斯塔特斯公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, there is an ongoing race to develop systems that can more accurately predict the outcome of sporting events

Method used

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  • Method and system for interactive, interpretable, and improved match and player performance predictions in team sports
  • Method and system for interactive, interpretable, and improved match and player performance predictions in team sports
  • Method and system for interactive, interpretable, and improved match and player performance predictions in team sports

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Embodiment Construction

[0026] One or more techniques disclosed herein relate generally to systems and methods for generating predicted outcomes of sporting events (eg, "games"). For example, one or more techniques disclosed herein address predicting the outcome of a game before the game begins and while the game is in progress.

[0027] In some embodiments, one or more of the techniques disclosed herein exploits the ability of individualized predictions to generate a prediction model prior to the start of a game to capture the low-level nonlinearities that exist between player performances within a team, thereby Generate forecast results. For example, the rationale behind this approach is that players and teams may have different levels of talent, but the level of talent they can demonstrate may be intrinsically linked to other players on the field as well as their opponents. While this approach may be intuitive, it has proven to be very challenging to do in practice due to the large number of perm...

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PUM

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Abstract

A method of generating an outcome for a sporting event is disclosed herein. A computing system retrieves tracking data from a data store. The computing system generates a predictive model using a deepneural network. The one or more neural networks of the deep neural network generates one or more embeddings comprising team-specific information and agent- specific information based on the trackingdata. The computing system selects, from the tracking data, one or more features related to a current context of the sporting event. The computing system learns, by the deep neural network, one or more likely outcomes of one or more sporting events. The computing system receives a pre-match lineup for the sporting event. The computing system generates, via the predictive model, a likely outcome ofthe sporting event based on historical information of each agent for the home team, each agent for the away team, and team-specific features.

Description

[0001] Cross References to Related Applications [0002] This application claims reference to US Provisional Application Serial No. 62 / 619,894, filed January 21, 2018, which is hereby incorporated by reference in its entirety. technical field [0003] The present disclosure relates generally to systems and methods for generating predictive models, and more particularly to systems and methods for predicting pre-game and in-game outcomes. Background technique [0004] Sports fans and data analysts have increasingly become deeply entrenched in sports analytics, specifically predicting the outcome of games before and during games. For example, as a lead up to a big game, sports networks continue to host debate shows in which multiple parties argue over which team will win the upcoming game. However, this analysis does not stop until the game is over. A typical "Monday Morning Quarterback" sportscaster, for example, debates how the outcome of the game would change if the coach ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A63F13/65A63F13/812G06N3/08G06N7/00
CPCG06N20/20G06N3/084G06N5/01G06N3/048G06N7/01G06N3/045A63B71/0605G06N3/08A63B71/0622G06N3/042A63B71/0616
Inventor H·鲁伊斯S·甘古利N·弗兰克P·卢西
Owner 斯塔特斯公司
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