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Efficiency in the NFL betting market: modifying and consolidating research methods


  • William Dare
  • A. Steven Holland


Modifying and consolidating previous research methods to generate more reliable estimates, some fairly weak evidence is found of inefficiency in the NFL betting market resulting from a bias favouring home underdog (against away favourite) teams. In contrast to previous research, no evidence is found that 'momentum strategies' generate significant returns in this market.

Suggested Citation

  • William Dare & A. Steven Holland, 2004. "Efficiency in the NFL betting market: modifying and consolidating research methods," Applied Economics, Taylor & Francis Journals, vol. 36(1), pages 9-15.
  • Handle: RePEc:taf:applec:v:36:y:2004:i:1:p:9-15
    DOI: 10.1080/0003684042000177152

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    References listed on IDEAS

    1. Russo, Benjamin & Gandar, John M. & Zuber, Richard A., 1989. "Market rationality tests based on cross-equation restrictions," Journal of Monetary Economics, Elsevier, vol. 24(3), pages 455-470, November.
    2. Gray, Philip K & Gray, Stephen F, 1997. " Testing Market Efficiency: Evidence from the NFL Sports Betting Market," Journal of Finance, American Finance Association, vol. 52(4), pages 1725-1737, September.
    3. Gandar, John, et al, 1988. " Testing Rationality in the Point Spread Betting Market," Journal of Finance, American Finance Association, vol. 43(4), pages 995-1008, September.
    4. Golec, Joseph & Tamarkin, Maurry, 1991. "The degree of inefficiency in the football betting market : Statistical tests," Journal of Financial Economics, Elsevier, vol. 30(2), pages 311-323, December.
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    Cited by:

    1. 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, Research Program on Forecasting.
    2. Baker, Rose D. & McHale, Ian G., 2013. "Forecasting exact scores in National Football League games," International Journal of Forecasting, Elsevier, vol. 29(1), pages 122-130.
    3. Norton, Hugh & Gray, Steve & Faff, Robert, 2015. "Yes, one-day international cricket ‘in-play’ trading strategies can be profitable!," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 164-176.
    4. Vaughan Williams, Leighton & Stekler, Herman O., 2010. "Sports forecasting," International Journal of Forecasting, Elsevier, vol. 26(3), pages 445-447, July.
      • Herman O. Stekler, 2007. "Sports Forecasting," Working Papers 2007-001, The George Washington University, Department of Economics, Research Program on Forecasting, revised Jan 2007.
    5. Borghesi, Richard, 2007. "The home team weather advantage and biases in the NFL betting market," Journal of Economics and Business, Elsevier, vol. 59(4), pages 340-354.
    6. 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.
    7. 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.
    8. Rodney J. Paul & Andrew P. Weinbach, 2014. "Market Efficiency and Behavioral Biases in the WNBA Betting Market," International Journal of Financial Studies, MDPI, Open Access Journal, vol. 2(2), pages 1-10, April.
    9. 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.
    10. Frank Daumann & Markus Breuer, 2011. "The Role of Information in Professional Football and the German Football Betting Market," Chapters,in: Contemporary Issues in Sports Economics, chapter 6 Edward Elgar Publishing.

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