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An analysis of Champions League match statistics

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  • Papahristodoulou, Christos

Abstract

Official match-play statistics from the Champions League tournament between 2001-02 and 2006-07 are used to estimate the impact of various variables on the performance of the teams, measured by goal difference. We find that offensive tactics measured by simple variables, such shots on goals, for both home and away teams, as well as the ranking of the teams, or measured by transformed variables, such as such as shots on goal and corners per ball possession, have a strong positive effect. Variables with negative effects are: the punishment of the teams, measured by own yellow and red cards per fouls committed, or simply the red cards, the shots wide, the corners, the ball possession difference and how smart the defendants are playing, measured by the number of the opposite teams’ offside per own ball possession. In addition, the multinomial logistic regressions show that the differences in some match statistics and the ranking of the teams explain 9 out of 10 home victories and almost 6 out of 10 home defeats. Finally, one of the strongest explanatory variables, the positive difference in shots on goal, compared to equality in shots on goal between teams, leads to a probability of a home team victory by 66%.

Suggested Citation

  • Papahristodoulou, Christos, 2007. "An analysis of Champions League match statistics," MPRA Paper 3605, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:3605
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    File URL: https://mpra.ub.uni-muenchen.de/20467/1/MPRA_paper_20467.pdf
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    References listed on IDEAS

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    2. Aylin Seckin, "undated". "Home Advantage in Association Football: Evidence from Turkish Super League," EcoMod2006 272100080, EcoMod.
    3. Jean-Marc Falter & Christophe Perignon, 2000. "Demand for football and intramatch winning probability: an essay on the glorious uncertainty of sports," Applied Economics, Taylor & Francis Journals, vol. 32(13), pages 1757-1765.
    4. Fiona Carmichael & Dennis Thomas & Robert Ward, 2000. "Team performance: the case of English Premiership football," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 21(1), pages 31-45.
    5. Luis Garicano & Ignacio Palacios-Huerta & Canice Prendergast, 2005. "Favoritism Under Social Pressure," The Review of Economics and Statistics, MIT Press, vol. 87(2), pages 208-216, May.
    6. Fiona Carmichael & Dennis Thomas & Robert Ward, 2001. "Production and Efficiency in Association Football," Journal of Sports Economics, , vol. 2(3), pages 228-243, August.
    7. Stefan Szymanski, 2003. "The Economic Design of Sporting Contests," Journal of Economic Literature, American Economic Association, vol. 41(4), pages 1137-1187, December.
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    Cited by:

    1. Papahristodoulou, Christos, 2013. "Evaluating the performance of UEFA Champions League scorers," MPRA Paper 51288, University Library of Munich, Germany.
    2. Papahristodoulou, Christos, 2012. "Optimal football strategies: AC Milan versus FC Barcelona," MPRA Paper 35940, University Library of Munich, Germany.
    3. Papahristodoulou, Christos, 2009. "The optimal layout of football players: A case study for AC Milan," MPRA Paper 20102, University Library of Munich, Germany.
    4. Papahristodoulou, Christos, 2012. "A NLIP Model on Wage Dispersion and Team Performance," MPRA Paper 39149, University Library of Munich, Germany.

    More about this item

    Keywords

    football; victory; defeat; goals; shots on goal; Champions League;

    JEL classification:

    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism

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