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How Does the Past of a Soccer Match Influence Its Future? Concepts and Statistical Analysis

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  • Andreas Heuer
  • Oliver Rubner

Abstract

Scoring goals in a soccer match can be interpreted as a stochastic process. In the most simple description of a soccer match one assumes that scoring goals follows from independent rate processes of both teams. This would imply simple Poissonian and Markovian behavior. Deviations from this behavior would imply that the previous course of the match has an impact on the present match behavior. Here a general framework for the identification of deviations from this behavior is presented. For this endeavor it is essential to formulate an a priori estimate of the expected number of goals per team in a specific match. This can be done based on our previous work on the estimation of team strengths. Furthermore, the well-known general increase of the number of the goals in the course of a soccer match has to be removed by appropriate normalization. In general, three different types of deviations from a simple rate process can exist. First, the goal rate may depend on the exact time of the previous goals. Second, it may be influenced by the time passed since the previous goal and, third, it may reflect the present score. We show that the Poissonian scenario is fulfilled quite well for the German Bundesliga. However, a detailed analysis reveals significant deviations for the second and third aspect. Dramatic effects are observed if the away team leads by one or two goals in the final part of the match. This analysis allows one to identify generic features about soccer matches and to learn about the hidden complexities behind scoring goals. Among others the reason for the fact that the number of draws is larger than statistically expected can be identified.

Suggested Citation

  • Andreas Heuer & Oliver Rubner, 2012. "How Does the Past of a Soccer Match Influence Its Future? Concepts and Statistical Analysis," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-7, November.
  • Handle: RePEc:plo:pone00:0047678
    DOI: 10.1371/journal.pone.0047678
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    References listed on IDEAS

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    Cited by:

    1. J Reade & C Singleton & L Vaughan Williams, 2020. "Betting Markets for English Premier League Results and Scorelines: Evaluating a Simple Forecasting Model," Economic Issues Journal Articles, Economic Issues, vol. 25(1), pages 87-106, March.
    2. Bolle Friedel & Otto Philipp E., 2016. "Matching as a Stochastic Process," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 236(3), pages 323-348, May.
    3. J. James Reade & Carl Singleton & Alasdair Brown, 2021. "Evaluating strange forecasts: The curious case of football match scorelines," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(2), pages 261-285, May.
    4. Stijn Baert & Simon Amez, 2018. "No better moment to score a goal than just before half time? A soccer myth statistically tested," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-17, March.
    5. Henrich R Greve & Jo Nesbø & Nils Rudi & Marat Salikhov, 2020. "Are goals scored just before halftime worth more? An old soccer wisdom statistically tested," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-11, October.
    6. Marius Ötting & Christian Deutscher & Carl Singleton & Luca De Angelis, 2023. "Gambling on Momentum in Contests," Economics Discussion Papers em-dp2023-08, Department of Economics, University of Reading.
    7. Clive B Beggs & Alexander J Bond & Stacey Emmonds & Ben Jones, 2019. "Hidden dynamics of soccer leagues: The predictive ‘power’ of partial standings," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-28, December.
    8. Andreas Heuer & Oliver Rubner, 2014. "Optimizing the Prediction Process: From Statistical Concepts to the Case Study of Soccer," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-9, September.

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