Fair Bets and Profitability in College Football Gambling

By Paul, Rodney J.; Weinbach, Andrew P. et al. | Journal of Economics and Finance, Summer 2003 | Go to article overview

Fair Bets and Profitability in College Football Gambling


Paul, Rodney J., Weinbach, Andrew P., Weinbach, Chris J., Journal of Economics and Finance


Abstract

Efficient markets in college football are tested over a 25-year period, 1976-2000. The market in general is found to be efficient, but betting on underdogs of more than 28 points violates a fair bet. The strategy of betting home underdogs reveals stronger results. Home underdogs of more than seven points are found to reject the null hypotheses of a fair bet over the last 10 years of the sample, 1991-2000. Home underdogs of more than 28 points are found to reject the null of no profitability during the same time frame. (JEL G1)

Introduction

The market for gambling in professional football has been examined in a variety of ways including the early work of Pankoff (1968) and the efficiency studies of Zuber et al. (1985), Gandar et al. (1988), and Sauer et al. (1988). The gambling market for college football has not been examined as frequently or as extensively. The two major studies of college football are the papers of Golec and Tomarkin (1991) and Dare and McDonald (1985). Golec and Tomarkin (1991) examined 15 years worth of data, 1973-87, for both college and professional football and found that professional football gamblers over bet favorites, particularly on the road, but the college football market does not exhibit this bias. Dare and McDonald (1985) tested the college football market over 13 years, 1981-93, and could not reject efficiency within the market.

This paper expands the study of college football gambling on a number of fronts. First, it includes 25 years worth of data to examine efficiency issues. Second, it tests for the existence of over betting on several categories of favorites. Log likelihood ratio tests for a fair bet and no profitability are examined for the entire sample and various subsamples of underdogs above a certain line in the same manner Vergin and Scriabin (1978) and Tryfos et al. (1984) studied in professional football. Finally, home underdogs are examined as a separate group and examined for market efficiency.

A fair bet cannot be rejected for the college football market as a whole. The over betting of favorites does not appear to exist for the overall sample, but in games with a line of more than 28 points, a strategy of taking the underdog rejects the null hypothesis of a fair bet, but not profitability. With respect to betting home underdogs, games with lines of greater than seven points were found to reject the null of no profitability from 1991-2000, and games with lines of more than 28, the largest underdogs, were found to reject the null of no profitability for the sample as a whole.

Market Efficiency Tests in College Football 1976-2000

The notion of the public over betting favorites is not new. The over betting of favorites, at least in violating a fair bet, if not profitability, has been found in baseball odds (Woodland and Woodland 1994), hockey odds (Woodland and Woodland 2001), and similarly in over betting of overs on NFL totals (Paul and Weinbach 2002). Although the market for college football appeared to be efficient in the studies of Golec and Tomarkin (1991) and Dare and McDonald (1995), the data in this paper include a longer time-frame for study and include the most recent years of lines, where the market for gambling has increased due to on-line betting through the Internet.

Data were gathered on college football betting lines through sports handicapper Jim Feist's workbook. The data include the years 1976 through 2000. The forecast errors of the simple regression models of Gandar et al. (1988) and Sauer et al. (1988) were found to exhibit skewness and to be non-normal. The forecast errors were found to have skewness equal to 0.279926, kurtosis equal to 3.168189, and a Jarque-Bera statistic of 177.9089 with a corresponding probability value close to zero. This invalidates the regression model and the F-statistic of the efficient markets test. Therefore, to test for market efficiency, we chose the likelihood ratio test proposed by Even and Noble (1992), which tests the result of a basic strategy against the null of a fair bet and no profitability. …

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