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Soccer matches as experiments: how often does the 'best' team win?

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  • G. K. Skinner
  • G. H. Freeman

Abstract

Models in which the number of goals scored by a team in a soccer match follow a Poisson distribution, or a closely related one, have been widely discussed. We here consider a soccer match as an experiment to assess which of two teams is superior and examine the probability that the outcome of the experiment (match) truly represents the relative abilities of the two teams. Given a final score, it is possible by using a Bayesian approach to quantify the probability that it was or was not the case that 'the best team won'. For typical scores, the probability of a misleading result is significant. Modifying the rules of the game to increase the typical number of goals scored would improve the situation, but a level of confidence that would normally be regarded as satisfactory could not be obtained unless the character of the game was radically changed.

Suggested Citation

  • G. K. Skinner & G. H. Freeman, 2009. "Soccer matches as experiments: how often does the 'best' team win?," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(10), pages 1087-1095.
    • Handle: RePEc:taf:japsta:v:36:y:2009:i:10:p:1087-1095
    DOI: 10.1080/02664760802715922
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    References listed on IDEAS

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    1. Karlis, Dimitris & Ntzoufras, Ioannis, 2005. "Bivariate Poisson and Diagonal Inflated Bivariate Poisson Regression Models in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 14(i10).
    2. Greenhough, J & Birch, P.C & Chapman, S.C & Rowlands, G, 2002. "Football goal distributions and extremal statistics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 615-624.
    3. M. J. Maher, 1982. "Modelling association football scores," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 36(3), pages 109-118, September.
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    Cited by:

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    2. Nicos Zafiris, 2014. "When is a multiple bet better than a single ?," Journal of Gambling Business and Economics, University of Buckingham Press, vol. 8(2), pages 1-15.

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