Testing Market Efficiency: Evidence From The NFL Sports Betting Market




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    • Philip K. Gray is from Queensland University of Technology and the Australian Graduate School of Management. Stephen F. Gray is from the University of Queensland and Duke University. We thank Barry Oliver, Peter Whelan, an anonymous referee, and participants of the 1995 AAANZ conference for valuable comments and suggestions. Funding from Coopers and Lybrand is gratefully acknowledged.


This article examines the efficiency of the National Football League (NFL) betting market. The standard ordinary least squares (OLS) regression methodology is replaced by a probit model. This circumvents potential econometric problems, and allows us to implement more sophisticated betting strategies where bets are placed only when there is a relatively high probability of success. In-sample tests indicate that probit-based betting strategies generate statistically significant profits. Whereas the profitability of a number of these betting strategies is confirmed by out-of-sample testing, there is some inconsistency among the remaining out-of-sample predictions. Our results also suggest that widely documented inefficiencies in this market tend to dissipate over time.