使用三合一人口普查分布测试游戏风格:在男子足球中的应用

IF 1.1 Q3 SOCIAL SCIENCES, MATHEMATICAL METHODS
Lucio Palazzo, Riccardo Ievoli, G. Ragozini
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引用次数: 0

摘要

足球比赛的总结性统计数据,如最终比分、控球率和传球完成率,并不能很好地反映场上的比赛风格。从这个意义上说,网络和图表能够量化团队之间的不同之处。我们研究了三合一人口普查的分布,即网络中局部结构的分布,并展示了如何描述足球队的传递网络。我们描述了三元结构,并在一些特定的概率假设下分析了它的分布,在这种情况下,引入了一些测试来验证足球数据中特定三元模式的存在。我们首先对随机结构进行综合检验,以评估观察到的三元分布是否偏离随机性。然后,我们重新设计了Dirichlet-Multinomial检验,以识别不同的三元行为。所提出的测试应用于连续三个赛季欧冠小组赛288场比赛的真实数据集。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Testing styles of play using triad census distribution: an application to men’s football
Abstract Summary statistics of football matches such as final score, possession and percentage of completed passes are not satisfyingly informative about style of play seen on the pitch. In this sense, networks and graphs are able to quantify how teams play differently from each others. We study the distribution of triad census, i.e., the distribution of local structures in networks and we show how it is possible to characterize passing networks of football teams. We describe the triadic structure and analyse its distribution under some specific probabilistic assumptions, introducing, in this context, some tests to verify the presence of specific triadic patterns in football data. We firstly run an omnibus test against random structure to asses whether observed triadic distribution deviates from randomness. Then, we redesign the Dirichlet-Multinomial test to recognize different triadic behaviours after choosing some reference patterns. The proposed tests are applied to a real dataset regarding 288 matches in the Group Stage of UEFA Champions League among three consecutive seasons.
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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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