Does confirmation bias exist in judged events at the Olympic Games?

IF 1.1 Q3 SOCIAL SCIENCES, MATHEMATICAL METHODS

Journal of Quantitative Analysis in Sports Pub Date : 2020-11-02 DOI:10.1515/jqas-2019-0043

Christiana E. Hilmer, Michael J. Hilmer

引用次数: 1

Abstract

Abstract Examining data for the 10 Olympic Games contested this century, we ask whether confirmation bias exists in judged events. We theorize that if such bias is present, then competitors in judged events should perform closer to predicted than competitors in non-judged events. Among a sample of over 5100 predicted medalists from the 10 Games, we find that, all else equal, the differences between ex-ante conventional wisdom and ex-post observed outcome are larger for competitors in timed events than for competitors in judged events. These results suggest that confirmation bias does potentially exist for judged events at the Olympic Games.

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确认偏见是否存在于奥运会的裁判项目中?

摘要通过对本世纪10届奥运会的数据分析，我们想知道在被评判的项目中是否存在确认偏见。我们的理论是，如果存在这样的偏见，那么在评判项目中的选手应该比在非评判项目中的选手表现得更接近于预测。在来自10届奥运会的5100多名预测奖牌获得者的样本中，我们发现，在其他条件相同的情况下，计时项目选手的事前传统智慧和事后观察结果之间的差异大于裁判项目选手的差异。这些结果表明，确认偏误确实可能存在于奥运会的裁判项目中。

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.