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Modeling and prediction of ice hockey match results

Author

Listed:
  • Marek Patrice

    (University of West Bohemia-European Centre of Excellence NTIS – New Technologies for Information Society, Plzen, Czech Republic)

  • Šedivá Blanka

    (University of West Bohemia-Department of Mathematics, Plzen, Czech Republic)

  • Ťoupal Tomáš

    (University of West Bohemia-European Centre of Excellence NTIS – New Technologies for Information Society, Plzen, Czech Republic)

Abstract

Modeling and prediction of ice hockey match results are not as widely examined areas as modeling and prediction of association football match results. It is assumed that match results in football and ice hockey can be modeled by the bivariate Poisson distribution or by some modification of this distribution. The aim of this paper is to explore the possibility of using models derived for football match results also for ice hockey match results and to propose some modifications of these models. A new model based on alternative definition of the bivariate Poisson distribution is presented. The models are tested on historical data from the highest-level ice hockey league in the Czech Republic between the years 1999 and 2012.

Suggested Citation

  • Marek Patrice & Šedivá Blanka & Ťoupal Tomáš, 2014. "Modeling and prediction of ice hockey match results," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 10(3), pages 357-365, September.
    • Handle: RePEc:bpj:jqsprt:v:10:y:2014:i:3:p:9:n:4
    DOI: 10.1515/jqas-2013-0129
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    References listed on IDEAS

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    1. Felix Famoye, 2010. "A new bivariate generalized Poisson distribution," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 64(1), pages 112-124, February.
    2. Franck Egon & Theiler Philipp, 2012. "One for Sure or Maybe Three: Empirical Evidence for Overtime Play from a Comparison of Swiss Ice Hockey and the NHL," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 232(3), pages 210-223, June.
    3. Siem Jan Koopman & Rutger Lit, 2015. "A dynamic bivariate Poisson model for analysing and forecasting match results in the English Premier League," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(1), pages 167-186, January.
    4. Dobson,Stephen & Goddard,John, 2011. "The Economics of Football," Cambridge Books, Cambridge University Press, number 9780521517140, October.
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    Cited by:

    1. Patrice Marek & František Vávra, 2020. "Comparison of Home Advantage in European Football Leagues," Risks, MDPI, vol. 8(3), pages 1-13, August.

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