A parametric family of Massey-type methods: inference, prediction, and sensitivity

IF 1.1 Q3 SOCIAL SCIENCES, MATHEMATICAL METHODS

Journal of Quantitative Analysis in Sports Pub Date : 2020-07-27 DOI:10.1515/jqas-2019-0071

E. Bozzo, P. Vidoni, Massimo Franceschet

引用次数: 0

Abstract

Abstract We study the stability of a time-aware version of the popular Massey method, previously introduced by Franceschet, M., E. Bozzo, and P. Vidoni. 2017. “The Temporalized Massey’s Method.” Journal of Quantitative Analysis in Sports 13: 37–48, for rating teams in sport competitions. To this end, we embed the temporal Massey method in the theory of time-varying averaging algorithms, which are dynamic systems mainly used in control theory for multi-agent coordination. We also introduce a parametric family of Massey-type methods and show that the original and time-aware Massey versions are, in some sense, particular instances of it. Finally, we discuss the key features of this general family of rating procedures, focusing on inferential and predictive issues and on sensitivity to upsets and modifications of the schedule.

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梅西型方法的参数族:推理、预测和灵敏度

我们研究了流行的Massey方法的时间感知版本的稳定性，该方法之前由Franceschet, M.， E. Bozzo和P. Vidoni于2017年引入。"时间化的梅西方法"《体育定量分析杂志》13:37-48，用于对体育比赛中的球队进行评级。为此，我们将时间Massey方法嵌入到时变平均算法理论中，时变平均算法是多智能体协调控制理论中主要使用的动态系统。我们还介绍了Massey型方法的参数族，并表明原始的和有时间意识的Massey版本在某种意义上是它的特殊实例。最后，我们讨论了这类评定程序的主要特征，重点讨论了推理和预测问题，以及对进度中断和修改的敏感性。

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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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.