在滑雪冲刺淘汰赛中选择对手

IF 1.1 Q3 SOCIAL SCIENCES, MATHEMATICAL METHODS Journal of Quantitative Analysis in Sports Pub Date : 2023-07-11 DOI:10.1515/jqas-2021-0027
Anders Lunander, N. Karlsson
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引用次数: 1

摘要

在这项研究中,我们分析了2015-2020年世界杯男女越野滑雪冲刺淘汰赛的数据。通过预审的运动员不再按照种子计划被分配到四分之一决赛,而是按照先后顺序选择参加五个四分之一决赛中的哪一个。由于比赛当天的时间限制,淘汰赛之间的恢复时间有所不同。这意味着运动员在四分之一决赛的早期比赛比在四分之一决赛的后期比赛有明显的优势,以最大限度地提高登上领奖台的可能性。本文的目的是分析运动员在选择参加四分之一决赛时面对恢复时间和预期竞争程度之间的权衡的选择。我们发现,尽管面临预期的更激烈的竞争,但预选赛中排名较高的运动员更愿意参加四分之一决赛。然而,我们的研究结果也表明,运动员低估了选择提前进入四分之一决赛的价值。此外,我们提出了一个种子方案,利用逻辑回归模型的估计来捕捉四分之一决赛之间的基本差异。
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Choosing opponents in skiing sprint elimination tournaments
Abstract In this study we analyse data from world cup cross-country skiing sprint elimination tournaments for men and women in 2015–2020. Instead of being assigned a quarterfinal according to a seeding scheme, prequalified athletes choose themselves in sequential order in which of the five quarterfinals to compete. Due to a time constraint on the day the competition is held, the recovery time between the elimination heats varies. This implies a clear advantage for the athlete to race in an early rather than in a late quarterfinal to maximize the probability of reaching the podium. The purpose of the paper is to analyse the athletes’ choices facing the trade-off between recovery time and expected degree of competition when choosing in which quarterfinal to compete. We find empirical support for the prediction that higher ranked athletes from the qualification round prefer to compete in early quarterfinals, despite facing expected harder competition. Nevertheless, our results also suggest that athletes underestimate the value of choosing an early quarterfinal. In addition, we propose a seeding scheme capturing the fundamental disparity across quarterfinals using the estimates from alogistic regression model.
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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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