橄榄球联盟比赛的方差伽玛模型

IF 1.1 Q3 SOCIAL SCIENCES, MATHEMATICAL METHODS

Journal of Quantitative Analysis in Sports Pub Date : 2020-03-24 DOI:10.1515/jqas-2019-0088

J. Fry, Oliver Smart, Jean-Philippe Serbera, B. Klar

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引用次数: 2

摘要

在最近的兴趣中，我们讨论了橄榄球联盟比赛的方差伽玛模型(应用于其他运动是可能的)。我们的模型是最近引入的伽玛差分布的一个特例，尽管使用方差伽玛分布的应用工作有着丰富的历史——特别是在金融领域。对这种特殊情况的限制增加了分析的可追溯性和计算的便利性。我们的三维模型扩展了经典的二维足球泊松模型。获得比赛结果、总分和奖励积分的分析结果。模型校准演示使用历史结果，博彩公司的数据和锦标赛模拟。

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A Variance Gamma model for Rugby Union matches

Abstract Amid much recent interest we discuss a Variance Gamma model for Rugby Union matches (applications to other sports are possible). Our model emerges as a special case of the recently introduced Gamma Difference distribution though there is a rich history of applied work using the Variance Gamma distribution – particularly in finance. Restricting to this special case adds analytical tractability and computational ease. Our three-dimensional model extends classical two-dimensional Poisson models for soccer. Analytical results are obtained for match outcomes, total score and the awarding of bonus points. Model calibration is demonstrated using historical results, bookmakers’ data and tournament simulations.

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来源期刊

Journal of Quantitative Analysis in Sports SOCIAL SCIENCES, MATHEMATICAL METHODS-

CiteScore

2.00

自引率

12.50%

发文量

期刊介绍： The Journal of Quantitative Analysis in Sports (JQAS), an official journal of the American Statistical Association, publishes timely, high-quality peer-reviewed research on the quantitative aspects of professional and amateur sports, including collegiate and Olympic competition. The scope of application reflects the increasing demand for novel methods to analyze and understand data in the growing field of sports analytics. Articles come from a wide variety of sports and diverse perspectives, and address topics such as game outcome models, measurement and evaluation of player performance, tournament structure, analysis of rules and adjudication, within-game strategy, analysis of sporting technologies, and player and team ranking methods. JQAS seeks to publish manuscripts that demonstrate original ways of approaching problems, develop cutting edge methods, and apply innovative thinking to solve difficult challenges in sports contexts. JQAS brings together researchers from various disciplines, including statistics, operations research, machine learning, scientific computing, econometrics, and sports management.