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NFL bettor biases and price setting: further tests of the Levitt hypothesis of sportsbook behaviour

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  • Rodney Paul
  • Andrew Weinbach

Abstract

Empirical support for the Levitt hypothesis of sportsbook behaviour, where sportsbooks set prices to maximize profits, not to clear the market, is shown using data from actual sportsbooks. Betting percentages on favourites and underdogs (pointspread market) and overs and unders (totals market) were obtained using actual dollars bet (www.sportsbook.com) and percentage of bets made (www.sportsinsights.com). Both data sets reinforce the idea that sportsbooks are not setting prices to attract even betting dollars on both sides of the proposition. Big favourites, road favourites and overs on high totals are all shown to attract a significantly higher percentage of bets in both samples. Betting against public sentiment is shown to be statistically profitable for the National Football League pointspread market, but not in the market for totals.

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  • Rodney Paul & Andrew Weinbach, 2011. "NFL bettor biases and price setting: further tests of the Levitt hypothesis of sportsbook behaviour," Applied Economics Letters, Taylor & Francis Journals, vol. 18(2), pages 193-197.
    • Handle: RePEc:taf:apeclt:v:18:y:2011:i:2:p:193-197
    DOI: 10.1080/13504850903508242
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    References listed on IDEAS

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    1. Rodney J. Paul & Andrew P. Weinbach, 2007. "Does Sportsbook.com Set Pointspreads to Maximize Profits? Tests of the Levitt Model of Sportsbook Behavior," Journal of Prediction Markets, University of Buckingham Press, vol. 1(3), pages 209-218, December.
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    Cited by:

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    2. Evan Moore & James Francisco, 2019. "Efficiency, Profitability, and College Football: do Bettors Overrate the Major Conferences in Interconference Play?," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 47(2), pages 159-167, June.
    3. Durand, Robert B. & Patterson, Fernando M. & Shank, Corey A., 2021. "Behavioral biases in the NFL gambling market: Overreaction to news and the recency bias," Journal of Behavioral and Experimental Finance, Elsevier, vol. 31(C).
    4. Linda M. Woodland & Bill M. Woodland, 2015. "The National Football League season wins total betting market: The impact of heuristics on behavior," Southern Economic Journal, John Wiley & Sons, vol. 82(1), pages 38-54, July.
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    6. Rodney Paul & Andrew P. Weinbach & Kenneth Small, 2014. "The Relationship between Sportsbook Volume, Forecast Accuracy, and Market Efficiency: The NFL and NCAA Football," Journal of Prediction Markets, University of Buckingham Press, vol. 8(2), pages 29-42.
    7. James Francisco & Evan Moore, 2019. "Betting with house money: reverse line movement based strategies in college football totals markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(4), pages 813-827, October.
    8. Jeremy Sandford & Paul Shea, 2013. "Optimal Setting of Point Spreads," Economica, London School of Economics and Political Science, vol. 80(317), pages 149-170, January.
    9. Andy Fodor, 2014. "Does Jet Lag Create A Profitable Opportunity For Nfl Bettors?," Journal of Gambling Business and Economics, University of Buckingham Press, vol. 8(1), pages 41-52.
    10. Andy Fodor & Michael DiFilippo & Kevin Krieger & Justin Davis, 2013. "Inefficient pricing from holdover bias in NFL point spread markets," Applied Financial Economics, Taylor & Francis Journals, vol. 23(17), pages 1407-1418, September.
    11. Igan, Deniz & Pinheiro, Marcelo & Smith, John, 2012. "Racial biases and market outcomes: "White men can't jump," but would you bet on it?," MPRA Paper 36069, University Library of Munich, Germany.
    12. Scott Tainsky & Jie Xu & Yilun Zhou, 2014. "Qualifying the Game Uncertainty Effect," Journal of Sports Economics, , vol. 15(3), pages 219-236, June.
    13. Kevin Krieger & Justin L. Davis & James Strode, 2021. "Patience is a virtue: exploiting behavior bias in gambling markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 45(4), pages 735-750, October.
    14. Shank, Corey A., 2022. "Information asymmetry in the NFL gambling market: Inside information versus informed bettors," Journal of Behavioral and Experimental Finance, Elsevier, vol. 36(C).
    15. Igan, Deniz & Pinheiro, Marcelo & Smith, John, 2015. "A study of a market anomaly: “White Men Can’t Jump”, but would you bet on it?," Journal of Economic Behavior & Organization, Elsevier, vol. 113(C), pages 13-25.
    16. Corey A. Shank, 2019. "NFL betting market efficiency, divisional rivals, and profitable strategies," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 36(3), pages 567-580, September.
    17. Kevin Krieger & Andy Fodor & Greg Stevenson, 2013. "The Sensitivity of Findings of Expected Bookmaker Profitability," Journal of Sports Economics, , vol. 14(2), pages 186-202, April.
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    20. Salaga, Steven & Tainsky, Scott, 2015. "Betting lines and college football television ratings," Economics Letters, Elsevier, vol. 132(C), pages 112-116.

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