{"title":"The evolution of seeding systems and the impact of imbalanced groups in FIFA Men’s World Cup tournaments 1954–2022","authors":"Michael A. Lapré, Elizabeth M. Palazzolo","doi":"10.1515/jqas-2022-0087","DOIUrl":null,"url":null,"abstract":"Abstract The FIFA Men’s World Cup tournament is the most popular sporting event in the world. Scholars have identified several flaws in the organization of the World Cup causing competitive imbalance. We empirically assess competitive imbalance between groups for the World Cup tournaments from 1954 through 2022. We average the Elo ratings of a team’s opponents in the group stage to calculate their group opponents rating. In every World Cup, the range in group opponents rating exceeds 118 Elo rating points – the difference between an average participant and an average semifinalist. Using logistic regression, we find that for an average participant in a 32-team World Cup, an increase in group opponents rating of only 88 Elo rating points can reduce the probability of reaching the quarterfinal from 0.174 to 0.081, which is a decrease of more than 50 %. None of the five seeding systems used by FIFA during 1954–2022 lessened the negative impact of group opponents rating on the probability of reaching the quarterfinal. We close with seven policy recommendations to restore competitive balance at the World Cup.","PeriodicalId":16925,"journal":{"name":"Journal of Quantitative Analysis in Sports","volume":"36 1","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Quantitative Analysis in Sports","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/jqas-2022-0087","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"SOCIAL SCIENCES, MATHEMATICAL METHODS","Score":null,"Total":0}
引用次数: 2
Abstract
Abstract The FIFA Men’s World Cup tournament is the most popular sporting event in the world. Scholars have identified several flaws in the organization of the World Cup causing competitive imbalance. We empirically assess competitive imbalance between groups for the World Cup tournaments from 1954 through 2022. We average the Elo ratings of a team’s opponents in the group stage to calculate their group opponents rating. In every World Cup, the range in group opponents rating exceeds 118 Elo rating points – the difference between an average participant and an average semifinalist. Using logistic regression, we find that for an average participant in a 32-team World Cup, an increase in group opponents rating of only 88 Elo rating points can reduce the probability of reaching the quarterfinal from 0.174 to 0.081, which is a decrease of more than 50 %. None of the five seeding systems used by FIFA during 1954–2022 lessened the negative impact of group opponents rating on the probability of reaching the quarterfinal. We close with seven policy recommendations to restore competitive balance at the World Cup.
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.