A structural model is derived describing the relationship between the probability that the favored team is victorious and the point spread through the use of a "no-arbitrage'' condition. A series of probit models are developed that show that NFL wagering markets were efficient within season during the period 1988-2006 and that the point spread is a statistically significant indicator of probability of victory. A team-level excess performance metric is estimated, termed an NFL Alpha, that indicates the extent to which a team's on-the-field performance exceeded betting market expectations. Finally, it is shown that there exists a market overreaction effect for NFL Alphas across seasons.
Ben-Akiva, M., & S. Lerman.1985. Discrete choice analysis. London: MIT Press.
2.
Bowers, B., Gandar, J., and Zuber, R.1985. Beating the spread: Testing the efficiency of the gambling market for the National Football League games. Journal of Political Economy, 93, 800-806.
3.
Brailsford, T., Easton, S., Gray, P., & Gray, S. (1995). The efficiency of Australian football betting markets. Australian Journal of Management, 20(2), 167-196.
4.
Cain, M., Law, D., & Peel, D.2000. Testing for statistical and market efficiency when forecast errors are non-normal: The NFL betting market revisited. Journal of Forecasting, 19, 575-586.
5.
Daniel, K., Hirshleifer, D., & Subrahmanyam, A.1998. Investor psychology and security market under-and over-reactions. Journal of Finance , 3(6), 1839-1885.
6.
Dare W., & MacDonald, S. (1996). A generalized model for testing the home and favorite team advantage in point spread markets. Journal of Financial Economics, 40, 295-318.
7.
Dare, W., & Holland, S. (2004). Efficiency in the NFL betting market: Modifying and consolidating research methods. Applied Economics, 36, 9-15.
8.
Dowie, J., 1976. On the efficiency and equity of betting markets . Economica, 43(170), 139-150.
9.
Fair, R., & Oster, J.2007. College football rankings and market efficiency . Journal of Sports Economics, 8(1), 3-18.
10.
Fama, E., & French, K.1992. The cross-section of expected stock returns. Journal of Finance, 47, 427-465.
11.
Gandar, J., Zuber, R., O'Brien, T., & Russo, B.1988. Testing rationality in the point spread betting market . Journal of Finance, 43, 995-1008.
12.
Gray, P., & Gray, S. (1997). Testing market efficiency: Evidence from the NFL sports betting market. Journal of Finance, 52(4), 1725-1737.
13.
Green, W., 2000, Econometric analysis. Upper Saddle River, NJ: Prentice Hall.
14.
Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. Journal of Finance , 48(1), 699-720.
15.
Kahneman, D., & Tversky, A.1973. On the psychology of prediction. Psychological Review, 80(4), 237-251.
16.
Paul, R., & Weinbach, A.2005. Bettor misperceptions in the NBA: The overbetting of large favorites and the ``hot hand.'' Journal of Sports Economics , 6(4), 390-400.
17.
Schnytzer, A., & Shilony, Y.1995. Inside information in a betting market. Economic Journal, 105(431), 963-971.
18.
Weinbach, A., & Weinbach, C., 2003. Fair bets and profitability in college football gambling . Journal of Economics and Finance, 27(2), 236-242.
19.
Williams, L.1999. Information efficiency in betting markets: A survey . Bulletin of Economic Research, 51(1), 269-279.
20.
Woodland, B., & Woodland, L.1994. Market efficiency and the favorite-longshot bias: The baseball betting market. Journal of Finance, 49(1), 269-280.
21.
Woodland, B., & Woodland, L.2000. Testing contrarian strategies in the National Football League. Journal of Sports Economics, 1(2), 187-193.
