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Time-varying ratings for international football teams

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  • Baker, Rose D.
  • McHale, Ian G.

Abstract

We present a model for rating international football teams. Using data from 1944 to 2016, we ask ‘which was the greatest team?’. To answer the question requires some sophisticated methodology. Specifically, we have used k-fold cross-validation, which allows us to optimally down-weight the results of friendly matches in explaining World Cup results. In addition to the central aim of the paper, we also discuss, from a philosophical perspective, situations in which model over-fitting is perhaps desirable. Results suggest that Hungary in 1952, is a strong candidate for the all-time greatest international football team.

Suggested Citation

  • Baker, Rose D. & McHale, Ian G., 2018. "Time-varying ratings for international football teams," European Journal of Operational Research, Elsevier, vol. 267(2), pages 659-666.
    • Handle: RePEc:eee:ejores:v:267:y:2018:i:2:p:659-666
    DOI: 10.1016/j.ejor.2017.11.042
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    References listed on IDEAS

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    1. Bastos, João A., 2010. "Forecasting bank loans loss-given-default," Journal of Banking & Finance, Elsevier, vol. 34(10), pages 2510-2517, October.
    2. Baker, Rose D. & McHale, Ian G., 2017. "An empirical Bayes model for time-varying paired comparisons ratings: Who is the greatest women’s tennis player?," European Journal of Operational Research, Elsevier, vol. 258(1), pages 328-333.
    3. Rose Baker & Dan Jackson, 2014. "Statistical application of barycentric rational interpolants: an alternative to splines," Computational Statistics, Springer, vol. 29(5), pages 1065-1081, October.
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    Cited by:

    1. László Csató, 2024. "Club coefficients in the UEFA Champions League: Time for shift to an Elo-based formula," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 24(2), pages 119-134, March.
    2. Scarf, Phil & Parma, Rishikesh & McHale, Ian, 2019. "On outcome uncertainty and scoring rates in sport: The case of international rugby union," European Journal of Operational Research, Elsevier, vol. 273(2), pages 721-730.
    3. Lapré Michael A. & Palazzolo Elizabeth M., 2022. "Quantifying the impact of imbalanced groups in FIFA Women’s World Cup tournaments 1991–2019," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 18(3), pages 187-199, September.
    4. Lapré Michael A. & Palazzolo Elizabeth M., 2023. "The evolution of seeding systems and the impact of imbalanced groups in FIFA Men’s World Cup tournaments 1954–2022," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 19(4), pages 317-332, December.
    5. L'aszl'o Csat'o, 2023. "Club coefficients in the UEFA Champions League: Time for shift to an Elo-based formula," Papers 2304.09078, arXiv.org, revised Oct 2023.
    6. Csató, László, 2022. "Quantifying incentive (in)compatibility: A case study from sports," European Journal of Operational Research, Elsevier, vol. 302(2), pages 717-726.

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