Modelling Australian Rules Football as spatial systems with pairwise comparisons

IF 1.1 Q3 SOCIAL SCIENCES, MATHEMATICAL METHODS Journal of Quantitative Analysis in Sports Pub Date : 2022-12-01 DOI:10.1515/jqas-2021-0035
Anton Andreacchio, N. Bean, Lewis Mitchell
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Abstract

Abstract Statistical analysis in competitive sport is an important tool for developing strategy and seeking competitive advantages. However, for complex team sports such as Australian Rules Football, major limitations occur when using possession event data for game analysis. First, focusing on counting possession events does not capture the impact of off-the-ball actions such as ground positioning of other players. Second, it is difficult to determine the extent that an event is due to either team’s relative proficiency or skill. Third, there is limited possession event data available from each match and modelling efforts often have low statistical power. Here we reinterpret event data into positional systems and utilise pairwise performance metrics to understand the relative team proficiency in each of these states. These metrics can then be used to construct transition probabilities between states for future games, and ultimately, absorbing probabilities of goal states. Our approach effectively predicts match outcomes using team ratings for forward, midfield and defensive systems and is sufficiently interpretable to support strategic decision-making by coaching departments in the Australian Football League (AFL).
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模拟澳式足球规则的空间系统与两两比较
竞技体育统计分析是制定竞技体育战略、谋求竞技优势的重要工具。然而,对于复杂的团队运动,如澳式足球,在使用控球事件数据进行比赛分析时存在主要限制。首先,专注于计算控球事件并没有捕捉到无球动作的影响,比如其他球员的地面定位。其次,很难确定某项比赛在多大程度上是由于两队的相对熟练程度或技术所致。第三,每场比赛的控球事件数据有限,建模工作通常具有较低的统计能力。在这里,我们将事件数据重新解释为位置系统,并利用成对的绩效指标来了解每个状态下的相对团队熟练程度。这些参数可以用于构建未来游戏状态之间的转换概率,并最终吸收目标状态的概率。我们的方法利用球队对前锋、中场和防守系统的评分有效地预测比赛结果,并充分解释澳大利亚足球联盟(AFL)教练部门的战略决策。
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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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