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      Quantifying the unfairness of the 2018 FIFA World Cup qualification

      1 , 2
      International Journal of Sports Science & Coaching
      SAGE Publications

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          Abstract

          This paper investigates the fairness of the 2018 FIFA World Cup qualifying competition via Monte Carlo simulations. The qualifying probabilities are calculated for 102 nations, all teams except for African and European countries. A method is proposed to quantify the degree of unfairness. Although the qualifications within four FIFA confederations are constructed fairly, serious differences are found between the continents: for instance, a South American team could have tripled its chances by playing in Asia. Choosing a fixed matchup in the inter-continental play-offs instead of the current random draw can reduce the unfairness of the competition. The move of Australia from the Oceanian to the Asian zone is shown to increase its probability of participating in the 2018 FIFA World Cup by about 65%. Our results provide important insights for the administrators on how to reallocate the qualifying berths.

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          Using ELO ratings for match result prediction in association football

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            Psychological Pressure in Competitive Environments: Evidence from a Randomized Natural Experiment

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              Building Nations through Shared Experiences: Evidence from African Football

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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                International Journal of Sports Science & Coaching
                International Journal of Sports Science & Coaching
                SAGE Publications
                1747-9541
                2048-397X
                February 2023
                April 11 2022
                February 2023
                : 18
                : 1
                : 183-196
                Affiliations
                [1 ]Laboratory on Engineering and Management Intelligence, Research Group of Operations Research and Decision Systems, Institute for Computer Science and Control (SZTAKI), Eötvös Loránd Research Network (ELKH)
                [2 ]Department of Operations Research and Actuarial Sciences, Corvinus University of Budapest (BCE)
                Article
                10.1177/17479541211073455
                b31d2270-59a0-44ba-bd6b-97a1b08faff9
                © 2023

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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