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The Impact of Visiting Team Travel on Game Outcome and Biases in NFL Betting Markets

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  • Mark W. Nichols

Abstract

Using data on regular season National Football League games from 1981-2004, this study examines the impact that travel has on game outcome and whether betting markets fully incorporate this information. A visiting team travelling west to east and crossing at least one time zone is shown to significantly increase the probability of the home team winning. This impact increases with distance, but at a decreasing rate. Evidence on whether betting markets fully account for this travel effect is mixed. While there is evidence that markets do not fully account for the impact of travel and that bettors underestimate the home team’s score whenever the visitor crosses a time zone, the model does not provide a profitable betting strategy out of sample. Thus, any bias is likely too small to profitably exploit.

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  • Mark W. Nichols, 2014. "The Impact of Visiting Team Travel on Game Outcome and Biases in NFL Betting Markets," Journal of Sports Economics, , vol. 15(1), pages 78-96, February.
    • Handle: RePEc:sae:jospec:v:15:y:2014:i:1:p:78-96
    DOI: 10.1177/1527002512440580
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    References listed on IDEAS

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    Cited by:

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    5. Lopez Michael J. & Matthews Gregory J., 2015. "Building an NCAA men’s basketball predictive model and quantifying its success," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 11(1), pages 5-12, March.
    6. Seungwhan Chun & Sang Soo Park, 2021. "Home Advantage in Skeleton: Familiarity versus Crowd Support," Journal of Sports Economics, , vol. 22(1), pages 3-26, January.
    7. 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.
    8. Andy Fodor & Kevin Krieger & David Kirch & Andrew Kreutzer, 2012. "Informational Differences In Nfl Point Spread And Moneyline Markets," Journal of Prediction Markets, University of Buckingham Press, vol. 6(2), pages 1-11.
    9. Scoppa, Vincenzo, 2013. "Fatigue and Team Performance in Soccer: Evidence from the FIFA World Cup and the UEFA European Championship," IZA Discussion Papers 7519, Institute of Labor Economics (IZA).
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    13. Corey A. Shank, 2018. "Is the NFL betting market still inefficient?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 42(4), pages 818-827, October.
    14. Carlos Alberto Belchior, 2020. "Fans and Match Results: Evidence From a Natural Experiment in Brazil," Journal of Sports Economics, , vol. 21(7), pages 663-687, October.
    15. Starke, Stephan & Vischer, Lars & Dilger, Alexander, 2022. "Change in home bias due to ghost games in the NFL," Discussion Papers of the Institute for Organisational Economics 6/2022, University of Münster, Institute for Organisational Economics.
    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(4), pages 567-580, September.
    17. Rodney Fort & Young H. Lee, 2020. "Transition to an unbalanced Sports League schedule: adding the analysis of outcome uncertainty," Applied Economics, Taylor & Francis Journals, vol. 52(51), pages 5629-5638, November.
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    20. B. Jay Coleman, 2017. "Team Travel Effects and the College Football Betting Market," Journal of Sports Economics, , vol. 18(4), pages 388-425, May.

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