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Let's meet as usual: Do games played on non-frequent days differ? Evidence from top European soccer leagues

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  • Goller, Daniel
  • Krumer, Alex

Abstract

Balancing the allocation of games in sports competitions is an important organizational task that can have serious financial consequences. In this paper, we examine data from 10,142 soccer games played in the top German, Spanish, French, and English soccer leagues between 2007/2008 and 2016/2017. Using a machine learning technique for variable selection and applying a semi-parametric analysis of radius matching on the propensity score, we find that all four leagues have a lower attendance in games that take place on four non-frequently played days than those on three frequently played days. We also find that, in all leagues, there is a significantly lower home advantage for the underdog teams on non-frequent days. Our findings suggest that the current schedule favors underdog teams with fewer home games on non-frequent days. Therefore, to increase the fairness of the competitions, it is necessary to adjust the allocation of the home games on non-frequent days in a way that eliminates any advantage driven by the schedule. These findings have implications for the stakeholders of the leagues, referees’ and calendar committees as well as for coaches and players.

Suggested Citation

  • Goller, Daniel & Krumer, Alex, 2020. "Let's meet as usual: Do games played on non-frequent days differ? Evidence from top European soccer leagues," European Journal of Operational Research, Elsevier, vol. 286(2), pages 740-754.
  • Handle: RePEc:eee:ejores:v:286:y:2020:i:2:p:740-754
    DOI: 10.1016/j.ejor.2020.03.062
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    References listed on IDEAS

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    1. Bergantiños, Gustavo & Moreno-Ternero, Juan D., 2021. "Monotonicity in sharing the revenues from broadcasting sports leagues," MPRA Paper 105643, University Library of Munich, Germany.
    2. Goller, Daniel & Lechner, Michael & Moczall, Andreas & Wolff, Joachim, 2020. "Does the estimation of the propensity score by machine learning improve matching estimation? The case of Germany's programmes for long term unemployed," Labour Economics, Elsevier, vol. 65(C).
    3. Scoppa, Vincenzo, 2021. "Social pressure in the stadiums: Do agents change behavior without crowd support?," Journal of Economic Psychology, Elsevier, vol. 82(C).
    4. J. James Reade & Dominik Schreyer & Carl Singleton, 2020. "Echoes: what happens when football is played behind closed doors?," Economics Discussion Papers em-dp2020-14, Department of Economics, Reading University.
    5. J. James Reade & Carl Singleton, 2020. "Demand for Public Events in the COVID-19 Pandemic: A Case Study of European Football," Economics Discussion Papers em-dp2020-09, Department of Economics, Reading University.
    6. J. James Reade & Dominik Schreyer & Carl Singleton, 2020. "Eliminating supportive crowds reduces referee bias," Economics Discussion Papers em-dp2020-25, Department of Economics, Reading University.

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