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Optimizing the Prediction Process: From Statistical Concepts to the Case Study of Soccer

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  • Andreas Heuer
  • Oliver Rubner

Abstract

We present a systematic approach for prediction purposes based on panel data, involving information about different interacting subjects and different times (here: two). The corresponding bivariate regression problem can be solved analytically for the final statistical estimation error. Furthermore, this expression is simplified for the special case that the subjects do not change their properties between the last measurement and the prediction period. This statistical framework is applied to the prediction of soccer matches, based on information from the previous and the present season. It is determined how well the outcome of soccer matches can be predicted theoretically. This optimum limit is compared with the actual quality of the prediction, taking the German premier league as an example. As a key step for the actual prediction process one has to identify appropriate observables which reflect the strength of the individual teams as close as possible. A criterion to distinguish different observables is presented. Surprisingly, chances for goals turn out to be much better suited than the goals themselves to characterize the strength of a team. Routes towards further improvement of the prediction are indicated. Finally, two specific applications are discussed.

Suggested Citation

  • 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.
  • Handle: RePEc:plo:pone00:0104647
    DOI: 10.1371/journal.pone.0104647
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    References listed on IDEAS

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    1. Andersson, Patric & Edman, Jan & Ekman, Mattias, 2005. "Predicting the World Cup 2002 in soccer: Performance and confidence of experts and non-experts," International Journal of Forecasting, Elsevier, vol. 21(3), pages 565-576.
    2. Schnitzlein, Daniel D., 2014. "How Important Is the Family? Evidence from Sibling Correlations in Permanent Earnings in the USA, Germany, and Denmark," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 27(1), pages 69-89.
    3. Song, ChiUng & Boulier, Bryan L. & Stekler, Herman O., 2007. "The comparative accuracy of judgmental and model forecasts of American football games," International Journal of Forecasting, Elsevier, vol. 23(3), pages 405-413.
    4. Hvattum, Lars Magnus & Arntzen, Halvard, 2010. "Using ELO ratings for match result prediction in association football," International Journal of Forecasting, Elsevier, vol. 26(3), pages 460-470, July.
    5. Ioannis Asimakopoulos & John Goddard, 2004. "Forecasting football results and the efficiency of fixed-odds betting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(1), pages 51-66.
    6. 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.
    7. C. Sire & S. Redner, 2009. "Understanding baseball team standings and streaks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 67(3), pages 473-481, February.
    8. E. Bittner & A. Nußbaumer & W. Janke & M. Weigel, 2009. "Football fever: goal distributions and non-Gaussian statistics," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 67(3), pages 459-471, February.
    9. Forrest, David & Simmons, Robert, 2000. "Forecasting sport: the behaviour and performance of football tipsters," International Journal of Forecasting, Elsevier, vol. 16(3), pages 317-331.
    10. A. Heuer & O. Rubner, 2009. "Fitness, chance, and myths: an objective view on soccer results," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 67(3), pages 445-458, February.
    11. M. J. Maher, 1982. "Modelling association football scores," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 36(3), pages 109-118, September.
    12. Ambrey, Christopher L. & Fleming, Christopher M., 2014. "The causal effect of income on life satisfaction and the implications for valuing non-market goods," Economics Letters, Elsevier, vol. 123(2), pages 131-134.
    13. Goddard, John, 2005. "Regression models for forecasting goals and match results in association football," International Journal of Forecasting, Elsevier, vol. 21(2), pages 331-340.
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    Cited by:

    1. Li, Yuesen & Ma, Runqing & Gonçalves, Bruno & Gong, Bingnan & Cui, Yixiong & Shen, Yanfei, 2020. "Data-driven team ranking and match performance analysis in Chinese Football Super League," Chaos, Solitons & Fractals, Elsevier, vol. 141(C).
    2. Luca Pappalardo & Paolo Cintia, 2018. "Quantifying The Relation Between Performance And Success In Soccer," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 21(03n04), pages 1-30, May.

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