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Testing the efficiency of the National Football League betting market

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  • Bryan Boulier
  • H. O. Stekler
  • Sarah Amundson

Abstract

This study presents three tests of efficiency of the NFL betting market for the years 1994-2000. First, it tests for weak-form informational efficiency of the betting market. Then it examines whether the market incorporates objective information such as power scores and stadium characteristics that might be useful for predicting game outcomes. Finally, it determines whether alternative betting strategies would have yielded a profit. Although there is some indication that differences in the playing surfaces of home and visiting teams were not fully reflected in the betting lines, it is found that there is no conclusive evidence to suggest that the market was inefficient over the period examined.

Suggested Citation

  • Bryan Boulier & H. O. Stekler & Sarah Amundson, 2006. "Testing the efficiency of the National Football League betting market," Applied Economics, Taylor & Francis Journals, vol. 38(3), pages 279-284.
    • Handle: RePEc:taf:applec:v:38:y:2006:i:3:p:279-284
    DOI: 10.1080/00036840500368904
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    References listed on IDEAS

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    1. Roger C. Vergin & Michael Scriabin, 1978. "Winning Strategies for Wagering on National Football League Games," Management Science, INFORMS, vol. 24(8), pages 809-818, April.
    2. Boulier, Bryan L. & Stekler, H. O., 2003. "Predicting the outcomes of National Football League games," International Journal of Forecasting, Elsevier, vol. 19(2), pages 257-270.
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    4. Zuber, Richard A & Gandar, John M & Bowers, Benny D, 1985. "Beating the Spread: Testing the Efficiency of the Gambling Market for National Football League Games," Journal of Political Economy, University of Chicago Press, vol. 93(4), pages 800-806, August.
    5. Sauer, Raymond D & Brajer, Vic & Ferris, Stephen P & Marr, M Wayne, 1988. "Hold Your Bets: Another Look at the Efficiency of the Gambling Market for National Football League Games: Comment," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 206-213, February.
    6. Evan Osborne, 2001. "Efficient Markets? Don’t Bet on It," Journal of Sports Economics, , vol. 2(1), pages 50-61, February.
    7. repec:bla:jfinan:v:43:y:1988:i:4:p:995-1008 is not listed on IDEAS
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    Cited by:

    1. Johnnie Johnson & Alistair Bruce & Jiejun Yu, 2010. "The ordinal efficiency of betting markets: an exploded logit approach," Applied Economics, Taylor & Francis Journals, vol. 42(29), pages 3703-3709.
    2. Justin L. Davis & Kevin Krieger, 2017. "Preseason bias in the NFL and NBA betting markets," Applied Economics, Taylor & Francis Journals, vol. 49(12), pages 1204-1212, March.
    3. Justin Cox & Adam L. Schwartz & Bonnie F. Van Ness & Robert A. Van Ness, 2021. "The Predictive Power of College Football Spreads: Regular Season Versus Bowl Games," Journal of Sports Economics, , vol. 22(3), pages 251-273, April.
    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. Martin Spann & Bernd Skiera, 2009. "Sports forecasting: a comparison of the forecast accuracy of prediction markets, betting odds and tipsters," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(1), pages 55-72.
    6. Justin Davis & Andy Fodor & Luke McElfresh & Kevin Kreiger, 2015. "Exploiting Week 2 Bias in the NFL Betting Markets," Journal of Prediction Markets, University of Buckingham Press, vol. 9(1), pages 53-67.
    7. N. Winchester & R. T. Stefani, 2013. "An innovative approach to National Football League standings using bonus points," Applied Economics, Taylor & Francis Journals, vol. 45(1), pages 123-134, January.
    8. Richard Borghesi, 2008. "Weather biases in the NFL totals market," Applied Financial Economics, Taylor & Francis Journals, vol. 18(12), pages 947-953.
    9. Steven Caudill, 2009. "OSU and LSU: easy to spell but did they belong? Using the method of paired comparisons to evaluate the BCS rankings and the NCAA football championship game 2007-08," Applied Economics, Taylor & Francis Journals, vol. 41(25), pages 3225-3230.
    10. Michael A. Roach, 2018. "Testing Labor Market Efficiency Across Position Groups in the NFL," Journal of Sports Economics, , vol. 19(8), pages 1093-1121, December.
    11. Miller, Thomas W. & Rapach, David E., 2013. "An intra-week efficiency analysis of bookie-quoted NFL betting lines in NYC," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 10-23.
    12. Hvattum, Lars Magnus & Arntzen, Halvard, 2010. "Using ELO ratings for match result prediction in association football," International Journal of Forecasting, Elsevier, vol. 26(3), pages 460-470, July.

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