加拿大足球游戏中的获胜概率模型

IF 1.7 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

Journal of Business Analytics Pub Date : 2021-12-18 DOI:10.1080/2573234X.2021.2015252

S. Hill

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引用次数: 1

摘要

本文介绍了加拿大足球比赛中的获胜概率模型。使用2015年至2019年加拿大足球联盟比赛的详细比赛和投注数据来创建逻辑回归和梯度增强模型。提出并讨论了具有和不具有博弈前扩散和总(超过/低于)数据影响的模型。由此产生的获胜概率模型经过精心校准，可用于支持游戏内决策、评估教练决策、估计团队“卷土重来”的程度，并潜在地识别游戏内下注机会。提供了一个R Shiny应用程序，允许估计用户提供的游戏状态输入的游戏内获胜概率。确定和描述未来工作的机会。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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In-game win probability models for Canadian football

ABSTRACT This article presents in-game win probability models for Canadian football. Play-by-play and wagering data for games from the Canadian Football League for the 2015 to 2019 seasons is used to create logistic regression and gradient boosting models. Models with and without the effect of pregame spread and total (over/under) data are presented and discussed. The resulting win probability models are well-calibrated and can be used to support in-game decision-making, review coaching decisions, estimate the magnitude of team “comebacks”, and potentially identify in-game wagering opportunities. An R Shiny application is provided to allow for estimation of in-game win probability for user-provided game state inputs. Opportunities for future work are identified and described.

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来源期刊

Journal of Business Analytics Business, Management and Accounting-Management Information Systems

CiteScore

2.50

自引率

0.00%

发文量