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Betting Markets Efficiency: Evidence From European Football

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  • Bruno Deschamps

Abstract

This paper uses data from up to 79 bookmakers in any one match to analyze the efficiency of European football betting markets during the 2005/2006 season. We first examine the empirical derivatives of the longshot bias, and find that the bias is much more pronounced for high-grade matches. This arguably supports the information-based explanation of the longshot bias. We also show that internet betting, by giving access to a large number of bookmakers, improves significantly bettors' potential return. Finally, we find that average odds do not provide the best estimate of the likelihood of a result. Indeed, the best available odds are informative as well, even after controlling for the average odds.

Suggested Citation

  • Bruno Deschamps, 2008. "Betting Markets Efficiency: Evidence From European Football," Journal of Gambling Business and Economics, University of Buckingham Press, vol. 2(1), pages 66-76, May.
    • Handle: RePEc:buc:jgbeco:v:2:y:2008:i:1:p:66-76
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    References listed on IDEAS

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    1. Russell Sobel & S. Travis Raines, 2003. "An examination of the empirical derivatives of the favourite-longshot bias in racetrack betting," Applied Economics, Taylor & Francis Journals, vol. 35(4), pages 371-385.
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    5. Vaughan Williams,Leighton (ed.), 2005. "Information Efficiency in Financial and Betting Markets," Cambridge Books, Cambridge University Press, number 9780521816038, October.
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    7. Forrest, David & Goddard, John & Simmons, Robert, 2005. "Odds-setters as forecasters: The case of English football," International Journal of Forecasting, Elsevier, vol. 21(3), pages 551-564.
    8. Michael A. Smith & David Paton & Leighton Vaughan Williams, 2006. "Market Efficiency in Person‐to‐Person Betting," Economica, London School of Economics and Political Science, vol. 73(292), pages 673-689, November.
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    10. David Paton & Leighton Vaughan Williams, 2005. "Forecasting outcomes in spread betting markets: can bettors use 'quarbs' to beat the book?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(2), pages 139-154.
    11. Bruno Deschamps & Olivier Gergaud, 2007. "Efficiency in Betting Markets: Evidence from English Football," Journal of Prediction Markets, University of Buckingham Press, vol. 1(1), pages 61-73, February.
    12. Tim Kuypers, 2000. "Information and efficiency: an empirical study of a fixed odds betting market," Applied Economics, Taylor & Francis Journals, vol. 32(11), pages 1353-1363.
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    Cited by:

    1. Carlos Gomez-Gonzalez & Julio del Corral, 2018. "The betting market over time: overround and surebets in European football," Economics and Business Letters, Oviedo University Press, vol. 7(4), pages 129-136.
    2. Andrew Grant & Anastasios Oikonomidis & Alistair C. Bruce & Johnnie E. V. Johnson, 2018. "New entry, strategic diversity and efficiency in soccer betting markets: the creation and suppression of arbitrage opportunities," The European Journal of Finance, Taylor & Francis Journals, vol. 24(18), pages 1799-1816, December.

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    JEL classification:

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

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