战略性跳跃--在跳远比赛中赢得 "最后三名 "的顺序效应

IF 1.1 Q3 SOCIAL SCIENCES, MATHEMATICAL METHODS
Niklas Karlsson, Anders Lunander
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引用次数: 0

摘要

近年来,跳远比赛的比赛规则发生了变化。如今,只有在五次初试中跳得最好的三名运动员才有资格再跳第六次--这种形式被称为 "最后三跳"。在首次实施的 "最后三跳 "中,排名靠前的运动员依次进行最后一跳,从最初试跳中排名第三的运动员开始。在第六次尝试中跳得最远的运动员将赢得比赛,与之前尝试的成绩无关。在本研究中,我们分析了在首次实施的 "决赛三人组 "中,运动员的跳跃顺序对比赛获胜概率的影响。根据 2021 年东京奥运会跳远决赛的估计分布参数,我们推导出决赛的对称子博弈完美均衡,并计算出相应的均衡获胜概率。在建立博弈模型之前,我们还建立了跳远比赛结果的随机模型。我们的研究结果表明,尽管后发优势很小,但仍存在。我们的模型还揭示了在这种比赛形式中,接近跑长度变化小和战略思维的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The strategic jump-the order effect on winning “The Final Three” in long jump competitions
The tournament rules for long jump competitions have changed in recent years. Today, only the three athletes with the best jumps from the five initial attempts are qualified to make an additional sixth jump – a format called The Final Three. In the first implemented version of The Final Three, the top athletes sequentially make one final jump, starting with the athlete ranked third place from the initial attempts. The athlete with the longest jump in this sixth attempt wins the competition, irrespective of achieved results in previous attempts. In this study, we analyze the effect of the athletes’ jump order on the probability of winning the competition within this first implemented version of The Final Three. We derive the final’s symmetric subgame perfect equilibrium and compute the corresponding equilibrium winning probabilities, given estimated distributional parameters from the Olympic long jumping final in Tokyo 2021. The modeling of the game is preceded by a development of a stochastic model for the outcome in long jumping. Our results indicate a last mover advantage, albeit small. Our model also reveals the importance of having a low variation in the approach run length and thinking strategically in this tournament format.
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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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