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Journal of Economics and Finance
Published in: Journal of Economics and Finance 4/2019

29-05-2019

Betting with house money: reverse line movement based strategies in college football totals markets

Authors: James Francisco, Evan Moore

Published in: Journal of Economics and Finance | Issue 4/2019

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Abstract

This article tests the efficient market hypothesis and the profitability of a simple betting strategies in NCAA college football. We examine all games that have a total, or over/under, from September 2005 through January 2016. We investigate whether betting based on “reverse line movement” in an effort to follow the actions of “sharps,” or professional bettors, is profitable over the time period. We find that, in general, following reverse line movement is not a profitable strategy with regard to the totals markets in college football.
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Appendix
Available only for authorised users
Footnotes
1
Some sites report only the percentage of bets placed, or are ambiguous. Sports Insights, LLC, the source of our data, makes it very clear that they provide the percentage of money wagered, which is what we use in this paper. See, e.g. “. . . Our Sportsbook Insider software now offers both betting ticket percentages and the percentage of actual dollars being waged on the spread, moneyline and over/under for each game.” https://​www.​sportsinsights.​com/​company/​frequently-asked-questions-faq/​#bettingpercentag​esource
 
2
All opening and closing totals on offer reported in this paper are the values bettors could get at the standard “natural” odds (−110). Other values may be available for better or worse odds, but the norm in college football (as opposed to other sports, including professional football) is to adjust to market activity via changes in the line, as opposed to “juicing” (i.e. changing the payout from −110 to another figure).
 
3
A cursory look at these results suggests it may be profitable to bet against RLM for the 16–20% on under. The fair bet and nonrandom test statistics have the same absolute values, as expected, and the log-likelihood no profit test statistic is 1.109 and the Z-test profitability statistic is 1.012 in this case. Neither test statistic indicates rejection of the null of no profits at a statistical significance of 10%.
 
4
We tested whether it would be profitable to bet against RLM for the month of January; the log-likelihood no profit test statistic is 2.363 and the Z-test profitability statistic is 1.580 in this case. Neither test statistic indicates statistical significance at the 10% level; we cannot reject the null hypothesis of no profits.
 
5
Table 9, in the appendix, provides summary statistics including the mean, standard deviation, median, and interquartile for the over percentage at each line change provided in Table 8.
 
6
We also tested whether it would be profitable to bet against RLM for line changes of 2, 0.5, −2.5, −5.5, and − 6; only the line change of −6 indicated statistical significance with a log-likelihood no profit test statistic of 3.184 (10% level) and a Z-test profitability statistic of 2.143 (5% level). As an interesting aside, similar testing of betting against RLM conducted on pooling the 11 games with a line decrease of 8.5 points or more finds statistical significance with a log-likelihood no profit test statistic of 4.176 (5% level) and a Z-test profitability statistic of 2.531 (5% level).
 
Literature
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Metadata
Title
Betting with house money: reverse line movement based strategies in college football totals markets
Authors
James Francisco
Evan Moore
Publication date
29-05-2019
Publisher
Springer US
Published in
Journal of Economics and Finance / Issue 4/2019
Print ISSN: 1055-0925
Electronic ISSN: 1938-9744
DOI
https://doi.org/10.1007/s12197-019-09479-3

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