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Semi-strong inefficiency in the fixed odds betting market: Underestimating the positive impact of head coach replacement in the main European soccer leagues

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  • Bernardo, Giovanni
  • Ruberti, Massimo
  • Verona, Roberto

Abstract

In this paper we analyse the efficiency of the sports betting market, seeking to ascertain whether the market is efficient in the case of fixed odds provided by bookmakers in the four major European soccer leagues under the semi-strong efficiency hypothesis. By examining the trends of odds in the event of a major change in expectations about team results, i.e. when the head coach of a team is replaced, we attempt to verify the argument that a profitable strategy for the bettor is likely to be possible. In this case, the market under consideration would be inefficient. Analysing the average effect of head coach replacement, we find a positive impact on team performance. Based on this information, we build a betting strategy to find out whether the bookmakers’ odds absorb this change in expectations about the winning probability of involved teams. Comparing our strategy result with a distribution generated in a Monte Carlo experiment, we conclude that the betting market is inefficient in its semi-strong form.

Suggested Citation

  • Bernardo, Giovanni & Ruberti, Massimo & Verona, Roberto, 2019. "Semi-strong inefficiency in the fixed odds betting market: Underestimating the positive impact of head coach replacement in the main European soccer leagues," The Quarterly Review of Economics and Finance, Elsevier, vol. 71(C), pages 239-246.
  • Handle: RePEc:eee:quaeco:v:71:y:2019:i:c:p:239-246
    DOI: 10.1016/j.qref.2018.08.007
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    1. Rick Audas & John Goddard & W. Glenn Rowe, 2006. "Modelling employment durations of NHL head coaches: turnover and post-succession performance," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 293-306.
    2. Donald B. Hausch & William T. Ziemba & Mark Rubinstein, 1981. "Efficiency of the Market for Racetrack Betting," Management Science, INFORMS, vol. 27(12), pages 1435-1452, December.
    3. Andersson, Patric & Edman, Jan & Ekman, Mattias, 2005. "Predicting the World Cup 2002 in soccer: Performance and confidence of experts and non-experts," International Journal of Forecasting, Elsevier, vol. 21(3), pages 565-576.
    4. Anthony Costa Constantinou & Norman Elliott Fenton, 2013. "Profiting From Arbitrage And Odds Biases Of The European Football Gambling Market," Journal of Gambling Business and Economics, University of Buckingham Press, vol. 7(2), pages 41-70.
    5. Ruth N. Bolton & Randall G. Chapman, 2008. "Searching For Positive Returns At The Track: A Multinomial Logit Model For Handicapping Horse Races," World Scientific Book Chapters, in: Donald B Hausch & Victor SY Lo & William T Ziemba (ed.), Efficiency Of Racetrack Betting Markets, chapter 17, pages 151-171, World Scientific Publishing Co. Pte. Ltd..
    6. 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.
    7. Maria De Paola & Vincenzo Scoppa, 2012. "The Effects of Managerial Turnover," Journal of Sports Economics, , vol. 13(2), pages 152-168, April.
    8. Marshall, Ben R., 2009. "How quickly is temporary market inefficiency removed?," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(3), pages 917-930, August.
    9. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    10. Song, ChiUng & Boulier, Bryan L. & Stekler, Herman O., 2007. "The comparative accuracy of judgmental and model forecasts of American football games," International Journal of Forecasting, Elsevier, vol. 23(3), pages 405-413.
    11. 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.
    12. Asch, Peter & Malkiel, Burton G & Quandt, Richard E, 1984. "Market Efficiency in Racetrack Betting," The Journal of Business, University of Chicago Press, vol. 57(2), pages 165-175, April.
    13. Strumbelj, E. & Sikonja, M. Robnik, 2010. "Online bookmakers' odds as forecasts: The case of European soccer leagues," International Journal of Forecasting, Elsevier, vol. 26(3), pages 482-488, July.
    14. Ioannis Asimakopoulos & John Goddard, 2004. "Forecasting football results and the efficiency of fixed-odds betting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(1), pages 51-66.
    15. Mukhtar Ali, 1998. "Probability models on horse-race outcomes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 25(2), pages 221-229.
    16. Swidler, Steve & Shaw, Ron, 1995. "Racetrack wagering and the "uninformed" bettor: A study of market efficiency," The Quarterly Review of Economics and Finance, Elsevier, vol. 35(3), pages 305-314.
    17. I. Graham & H. Stott, 2008. "Predicting bookmaker odds and efficiency for UK football," Applied Economics, Taylor & Francis Journals, vol. 40(1), pages 99-109.
    18. Dixon, Mark J. & Pope, Peter F., 2004. "The value of statistical forecasts in the UK association football betting market," International Journal of Forecasting, Elsevier, vol. 20(4), pages 697-711.
    19. Vaughan Williams,Leighton (ed.), 2005. "Information Efficiency in Financial and Betting Markets," Cambridge Books, Cambridge University Press, number 9780521816038.
    20. Michael Cain & David Law & David Peel, 2000. "The Favourite‐Longshot Bias and Market Efficiency in UK Football betting," Scottish Journal of Political Economy, Scottish Economic Society, vol. 47(1), pages 25-36, February.
    21. Forrest, David & Simmons, Robert, 2000. "Forecasting sport: the behaviour and performance of football tipsters," International Journal of Forecasting, Elsevier, vol. 16(3), pages 317-331.
    22. Berkowitz, Jason P. & Depken, Craig A. & Gandar, John M., 2017. "A favorite-longshot bias in fixed-odds betting markets: Evidence from college basketball and college football," The Quarterly Review of Economics and Finance, Elsevier, vol. 63(C), pages 233-239.
    23. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    24. Hausch, Donald B & Ziemba, William T, 1990. "Arbitrage Strategies for Cross-Track Betting on Major Horse Races," The Journal of Business, University of Chicago Press, vol. 63(1), pages 61-78, January.
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    Cited by:

    1. 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.
    2. 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.
    3. Pascal Flurin Meier & Raphael Flepp & Egon Franck, 2021. "Are sports betting markets semistrong efficient? Evidence from the COVID-19 pandemic," Working Papers 387, University of Zurich, Department of Business Administration (IBW).

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    More about this item

    Keywords

    Sports betting market; Fixed-odds bets; Semi-strong efficiency hypothesis; Monte Carlo experiment;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism

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