背景中没有欢呼声?COVID-19 期间职业飞镖的个人表现

IF 1.1 Q3 SOCIAL SCIENCES, MATHEMATICAL METHODS
Finn Spilker, Marius Ötting
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引用次数: 0

摘要

COVID-19 大流行导致全球体育活动停摆。虽然职业体育比赛在 2020 年中期重新开始,但通常不允许观众入场。本文研究了球迷缺席和社会压力减小对职业飞镖比赛成绩的影响--在这种情况下,可以很好地观察选手的个人表现。考虑到近五年的比赛数据,我们使用贝叶斯多层次模型来研究不同选手在社会压力减少方面的潜在异质性。在分析中,我们考虑了飞镖运动中的两个主要成绩衡量标准:三镖平均成绩和结账成绩。我们的结果表明,社会压力的减少对不同选手成绩的影响存在很大差异。我们还发现,与相对缺乏经验的选手相比,经验丰富的选手受社会压力的影响较小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
No cheering in the background? Individual performance in professional darts during COVID-19
The COVID-19 pandemic has led to a global shutdown of sporting activities. While professional sports competitions restarted in mid-2020, spectators were usually not allowed. This paper investigates the effect of absent fans and reduced social pressure on performance in professional darts – a setting where individual player performances can be well observed. Considering almost five years of tournament data, we use Bayesian multilevel models to investigate potential heterogeneity across players concerning reduced social pressure. For our analysis, we consider the two main performance measures in darts: the three-dart average and the checkout performance. Our results indicate that the effect of reduced social pressure on performance varies substantially across players. We further find experienced players to be less affected by social pressure compared to relatively inexperienced players.
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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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