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Are betting markets efficient? Evidence from European Football Championships

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  • Alexis Direr

Abstract

This article investigates the degree of efficiency of the European Football online betting market by using odds quoted by 12 bookmakers on 21 European championships over 11 years. We show that systematically picking out odds inferior to a threshold delivers a rate of return of 4.45% if best odds are selected across bookmakers and 2.78% if mean odds are used. This amounts to backing overwhelmingly favourites whose probability of winning exceeds 90%. Our results only exploit information contained in odds, are robust to the use of real-time data and different sample periods and hold under risk neutrality and expected utility preferences for realistic degrees of risk aversion. Transaction costs reduce profitability but only for small stake bets.

Suggested Citation

  • Alexis Direr, 2013. "Are betting markets efficient? Evidence from European Football Championships," Applied Economics, Taylor & Francis Journals, vol. 45(3), pages 343-356, January.
    • Handle: RePEc:taf:applec:v:45:y:2013:i:3:p:343-356
    DOI: 10.1080/00036846.2011.602010
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    Cited by:

    1. Goto, Shingo & Yamada, Toru, 2023. "What drives biased odds in sports betting markets: Bettors’ irrationality and the role of bookmakers," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 252-270.
    2. David Winkelmann & Marius Ötting & Christian Deutscher & Tomasz Makarewicz, 2024. "Are Betting Markets Inefficient? Evidence From Simulations and Real Data," Journal of Sports Economics, , vol. 25(1), pages 54-97, January.
    3. Dominic Cortis, 2015. "Expected Values And Variances In Bookmaker Payouts: A Theoretical Approach Towards Setting Limits On Odds," Journal of Prediction Markets, University of Buckingham Press, vol. 9(1), pages 1-14.
    4. Feess, Eberhard & Müller, Helge & Schumacher, Christoph, 2016. "Estimating risk preferences of bettors with different bet sizes," European Journal of Operational Research, Elsevier, vol. 249(3), pages 1102-1112.
    5. Franke, Maximilian, 2020. "Do market participants misprice lottery-type assets? Evidence from the European soccer betting market," The Quarterly Review of Economics and Finance, Elsevier, vol. 75(C), pages 1-18.
    6. Jonas Vandenbruaene & Jan Annaert & Marc De Ceuster, 2025. "How digitalization can shape markets: the case of sports betting," Economica, London School of Economics and Political Science, vol. 92(366), pages 644-673, April.
    7. Angelini, Giovanni & De Angelis, Luca & Singleton, Carl, 2022. "Informational efficiency and behaviour within in-play prediction markets," International Journal of Forecasting, Elsevier, vol. 38(1), pages 282-299.
    8. Kai Fischer & Justus Haucap, 2020. "Betting Market Efficiency in the Presence of Unfamiliar Shocks: The Case of Ghost Games during the Covid-19 Pandemic," CESifo Working Paper Series 8526, CESifo.
    9. Jinook Jeong & Jee Young Kim & Yoon Jae Ro, 2019. "On the efficiency of racetrack betting market: a new test for the favourite-longshot bias," Applied Economics, Taylor & Francis Journals, vol. 51(54), pages 5817-5828, November.
    10. Kai Fischer & Justus Haucap, 2022. "Home advantage in professional soccer and betting market efficiency: The role of spectator crowds," Kyklos, Wiley Blackwell, vol. 75(2), pages 294-316, May.
    11. Angelini, Giovanni & De Angelis, Luca, 2019. "Efficiency of online football betting markets," International Journal of Forecasting, Elsevier, vol. 35(2), pages 712-721.
    12. Montone, Maurizio, 2021. "Optimal pricing in the online betting market," Journal of Economic Behavior & Organization, Elsevier, vol. 186(C), pages 344-363.

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