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Prediction of major international soccer tournaments based on team-specific regularized Poisson regression: An application to the FIFA World Cup 2014

Author

Listed:
  • Groll Andreas

    (Department of Mathematics, Ludwig-Maximilians-University, Theresienstr. 39, 80333 Munich)

  • Schauberger Gunther
  • Tutz Gerhard

    (Department of Statistics, Ludwig-Maximilians-University, Munich, Bavaria, Germany)

Abstract

In this article an approach for the analysis and prediction of international soccer match results is proposed. It is based on a regularized Poisson regression model that includes various potentially influential covariates describing the national teams’ success in previous FIFA World Cups. Additionally, within the generalized linear model (GLM) framework, also differences of team-specific effects are incorporated. In order to achieve variable selection and shrinkage, we use tailored Lasso approaches. Based on preceding FIFA World Cups, two models for the prediction of the FIFA World Cup 2014 are fitted and investigated. Based on the model estimates, the FIFA World Cup 2014 is simulated repeatedly and winning probabilities are obtained for all teams. Both models favor the actual FIFA World Champion Germany.

Suggested Citation

  • Groll Andreas & Schauberger Gunther & Tutz Gerhard, 2015. "Prediction of major international soccer tournaments based on team-specific regularized Poisson regression: An application to the FIFA World Cup 2014," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 11(2), pages 97-115, June.
    • Handle: RePEc:bpj:jqsprt:v:11:y:2015:i:2:p:97-115:n:1
    DOI: 10.1515/jqas-2014-0051
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    References listed on IDEAS

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    Cited by:

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    2. Corona Francisco & Wiper Michael Peter & Horrillo Juan de Dios Tena, 2017. "On the importance of the probabilistic model in identifying the most decisive games in a tournament," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 13(1), pages 11-23, March.
    3. Chater, Mario & Arrondel, Luc & Gayant, Jean-Pascal & Laslier, Jean-François, 2021. "Fixing match-fixing: Optimal schedules to promote competitiveness," European Journal of Operational Research, Elsevier, vol. 294(2), pages 673-683.
    4. Groll Andreas & Kneib Thomas & Mayr Andreas & Schauberger Gunther, 2018. "On the dependency of soccer scores – a sparse bivariate Poisson model for the UEFA European football championship 2016," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 14(2), pages 65-79, June.
    5. Gunther Schauberger & Andreas Groll & Gerhard Tutz, 2018. "Analysis of the importance of on-field covariates in the German Bundesliga," Journal of Applied Statistics, Taylor & Francis Journals, vol. 45(9), pages 1561-1578, July.
    6. Christian Deutscher & Marco Sahm & Sandra Schneemann & Hendrik Sonnabend, 2022. "Strategic investment decisions in multi-stage contests with heterogeneous players," Theory and Decision, Springer, vol. 93(2), pages 281-317, September.

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