量化1991-2019年国际足联女足世界杯比赛中不平衡小组的影响

IF 1.1 Q3 SOCIAL SCIENCES, MATHEMATICAL METHODS Journal of Quantitative Analysis in Sports Pub Date : 2022-09-01 DOI:10.1515/jqas-2021-0052
Michael A. Lapré, Elizabeth M. Palazzolo
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引用次数: 2

摘要

国际足联女足世界杯分为小组赛和淘汰赛两阶段。我们确定了在小组赛阶段造成竞争不平衡的几个问题。我们使用1991年至2019年所有女足世界杯的比赛数据,对每届世界杯各组之间的竞争不平衡进行实证评估。使用最小二乘法,我们确定所有球队的评分。对于每支球队,我们将该组对手的评分取平均值,计算出该组对手的评分。我们发现小组对手评分的范围在2.5到4.5球之间变化,这表明存在严重的竞争不平衡。我们使用逻辑回归来量化不平衡对女足世界杯成功概率的影响。具体来说,我们的估计表明,在小组赛对手排名中少进一个球,进入四分之一决赛的概率就会增加33%。我们讨论了一些减少女足世界杯竞争不平衡的政策建议。
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Quantifying the impact of imbalanced groups in FIFA Women’s World Cup tournaments 1991–2019
Abstract The FIFA Women’s World Cup tournament consists of a group stage and a knockout stage. We identify several issues that create competitive imbalance in the group stage. We use match data from all Women’s World Cup tournaments from 1991 through 2019 to empirically assess competitive imbalance across groups in each World Cup. Using least squares, we determine ratings for all teams. For each team, we average the ratings of the opponents in the group to calculate group opponents rating. We find that the range in group opponents rating varies between 2.5 and 4.5 goals indicating substantial competitive imbalance. We use logistic regression to quantify the impact of imbalance on the probability of success in the Women’s World Cup. Specifically, our estimates show that one goal less in group opponents rating can increase the probability of reaching the quarterfinal by 33%. We discuss several policy recommendations to reduce competitive imbalance at the Women’s World Cup.
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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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