Opening up the court: analyzing player performance across tennis Grand Slams

IF 1.1 Q3 SOCIAL SCIENCES, MATHEMATICAL METHODS Journal of Quantitative Analysis in Sports Pub Date : 2021-07-06 DOI:10.1515/jqas-2019-0015
Shannon K. Gallagher, K. Frisoli, Amanda Luby
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引用次数: 2

Abstract

Abstract In tennis, the Australian Open, French Open, Wimbledon, and US Open are the four most prestigious events (Grand Slams). These four Grand Slams differ in the composition of the court surfaces, when they are played in the year, and which city hosts the players. Individual Grand Slams come with different expectations, and it is often thought that some players achieve better results at some Grand Slams than others. It is also thought that differences in results may be attributed, at least partially, to surface type of the courts. For example, Rafael Nadal, Roger Federer, and Serena Williams have achieved their best results on clay, grass, and hard courts, respectively. This paper explores differences among Grand Slams, while adjusting for confounders such as tour, competitor strength, and player attributes. More specifically, we examine the effect of the Grand Slam on player performance for matches from 2013 to 2019. We take two approaches to modeling these data: (1) a mixed-effects model accounting for both player and tournament features and (2) models that emphasize individual performance. We identify differences across the Grand Slams at both the tournament and individual player level.
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开放球场:分析网球大满贯选手的表现
在网球运动中,澳大利亚网球公开赛、法国网球公开赛、温布尔登网球公开赛和美国网球公开赛是四大最负盛名的赛事(大满贯)。这四项大满贯赛事的不同之处在于场地的组成、一年中的比赛时间以及选手所在的城市。个人大满贯有着不同的期望,人们通常认为有些球员在某些大满贯中取得了比其他人更好的成绩。也有人认为,结果的差异可能至少部分归因于法院的地面类型。例如,拉斐尔·纳达尔、罗杰·费德勒和塞雷娜·威廉姆斯分别在红土、草地和硬地取得了最好的成绩。本文探讨了大满贯赛事之间的差异,同时对巡回赛、竞争对手实力和球员属性等混杂因素进行了调整。更具体地说,我们研究了2013年至2019年大满贯赛事对球员表现的影响。我们采用两种方法对这些数据进行建模:(1)考虑球员和锦标赛特征的混合效应模型;(2)强调个人表现的模型。我们确定了大满贯在锦标赛和个人水平上的差异。
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来源期刊
Journal of Quantitative Analysis in Sports
Journal of Quantitative Analysis in Sports SOCIAL SCIENCES, MATHEMATICAL METHODS-
CiteScore
2.00
自引率
12.50%
发文量
15
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.
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