估算成对比较竞赛中与年龄有关的成绩:斯诺克的应用

IF 1.1 Q3 SOCIAL SCIENCES, MATHEMATICAL METHODS
Rose D. Baker, Ian G. McHale
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引用次数: 0

摘要

我们首先提出了一个斯诺克比赛结果模型,在该模型中,选手实力随时间变化而确定。其结果使我们能够确定有史以来最伟大的球员,并研究年龄与表现之间的关系。其次,我们提出了一个随机效应模型,利用第一个模型估算出的实力来预测球员的表现,并评估早期承诺的保持程度。罗尼-奥沙利文(Ronnie O'Sullivan)和斯蒂芬-亨德利(Stephen Hendry)是史上最伟大选手的两位候选人。我们发现,他们的巅峰表现出现在 25 岁到 30 岁之间,与其他运动项目的研究结果相比,他们的年龄比预期的要小。除体育运动外,这些研究结果还为有关随年龄变化的表现的一般文献做出了贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimating age-dependent performance in paired comparisons competitions: application to snooker
We first present a model for the outcome of snooker matches in which player strengths are allowed to vary deterministically with time. The results allow us to identify the greatest players of all time, and to examine the relationship between age and performance. Second, we present a random effects model which uses the estimated strengths from our first model, to forecast player performance, and to assess the extent to which early promise has been maintained. Ronnie O’Sullivan and Stephen Hendry are the two candidates for the title of the greatest of all time. We find that peak performance occurs between the ages of 25 and 30, younger than would be expected when compared to findings in other sports. Outside sport, these findings contribute to the general literature on variation of performance with age.
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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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