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A Comment on the Bias of Probabilities Derived From Betting Odds and Their Use in Measuring Outcome Uncertainty

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  • Erik Å trumbelj

Abstract

Probabilities from bookmaker odds are often used in measures of short-run outcome uncertainty. We analyzed the most commonly used methods for deriving probability forecasts from odds and found that basic normalization (BN) produces biased probabilities. Furthermore, differences between probabilities produced with BN, regression models, or Shin probabilities are large enough to lead to contradictory conclusions when used to measure outcome uncertainty. We also provide evidence against the reported bias of bookmakers favoring better supported teams and show how past evidence of such a bias is possibly only due to a misinterpretation of the results.

Suggested Citation

  • Erik Å trumbelj, 2016. "A Comment on the Bias of Probabilities Derived From Betting Odds and Their Use in Measuring Outcome Uncertainty," Journal of Sports Economics, , vol. 17(1), pages 12-26, January.
    • Handle: RePEc:sae:jospec:v:17:y:2016:i:1:p:12-26
    DOI: 10.1177/1527002513519329
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    References listed on IDEAS

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    1. Nicholas King & P. Dorian Owen & Rick Audas, 2012. "Playoff Uncertainty, Match Uncertainty and Attendance at Australian National Rugby League Matches," The Economic Record, The Economic Society of Australia, vol. 88(281), pages 262-277, June.
    2. Jullien, Bruno & Salanie, Bernard, 1994. "Measuring the Incidence of Insider Trading: A Comment on Shin," Economic Journal, Royal Economic Society, vol. 104(427), pages 1418-1419, November.
    3. 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.
    4. Stekler, H.O. & Sendor, David & Verlander, Richard, 2010. "Issues in sports forecasting," International Journal of Forecasting, Elsevier, vol. 26(3), pages 606-621, July.
      • Herman O. Stekler & David Sendor & Richard Verlander, 2009. "Issues in Sports Forecasting," Working Papers 2009-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    5. Shin, Hyun Song, 1991. "Optimal Betting Odds against Insider Traders," Economic Journal, Royal Economic Society, vol. 101(408), pages 1179-1185, September.
    6. Shin, Hyun Song, 1993. "Measuring the Incidence of Insider Trading in a Market for State-Contingent Claims," Economic Journal, Royal Economic Society, vol. 103(420), pages 1141-1153, September.
    7. Hyun Song Shin, 2008. "Prices Of State Contingent Claims With Insider Traders, And The Favourite-Longshot Bias," World Scientific Book Chapters, in: Donald B Hausch & Victor SY Lo & William T Ziemba (ed.), Efficiency Of Racetrack Betting Markets, chapter 34, pages 343-352, World Scientific Publishing Co. Pte. Ltd..
    8. 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.
    9. Alistair Dawson & Paul Downward, 2005. "Measuring Short-Run Uncertainty of Outcome in Sporting Leagues," Journal of Sports Economics, , vol. 6(3), pages 303-313, August.
    10. Michael Cain & David Law & David Peel, 2002. "Is one price enough to value a state-contingent asset correctly? Evidence from a gambling market," Applied Financial Economics, Taylor & Francis Journals, vol. 12(1), pages 33-38.
    11. David Forrest & Robert Simmons, 2008. "Sentiment in the betting market on Spanish football," Applied Economics, Taylor & Francis Journals, vol. 40(1), pages 119-126.
    12. Dennis Coates & Brad R. Humphreys, 2012. "Game Attendance and Outcome Uncertainty in the National Hockey League," Journal of Sports Economics, , vol. 13(4), pages 364-377, August.
    13. Vaughan Williams,Leighton (ed.), 2005. "Information Efficiency in Financial and Betting Markets," Cambridge Books, Cambridge University Press, number 9780521816038, September.
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    Cited by:

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    6. Berkowitz, Jason P. & Depken II, Craig A. & Gandar, John M., 2018. "Market evidence against widespread point shaving in college basketball," Journal of Economic Behavior & Organization, Elsevier, vol. 153(C), pages 283-292.

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