The Determinants of Betting Volume for Sports in North America: Evidence of Sports Betting as Consumption in the NBA and NHL

Abstract

The National Basketball Association (NBA) and National Hockey League (NHL) are studied to ascertain the determinants of betting volume on an individual game-togame basis. Actual betting volume was obtained and aggregated across three on-line sportsbooks for the 2008-09 season. Independent variables such as the quality of teams, television coverage by network, day of the week, time of day, month of the season, etc. are included in a regression model to determine the factors that influence betting volume. The results reveal betting behavior is much like fan behavior as key fan-attributes, such as the quality of teams and the availability of television coverage, are shown to have a positive and significant effect on betting volume. The results imply that consumption plays a major role in the decision to gamble on sports. Pure investment-based gambling appears to be the exception, rather than the norm. The implication of this result as it relates to models of sportsbook behavior is explored.

Keywords

sports betting efficient markets consumption television

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References

Buraimo

, & Simmons

(2008). Competitive balance and attendance in Major League Baseball: An empirical test of the uncertainty of outcome hypothesis. International Journal of Sport Finance,3(3), 146–155.

Conlisk

(1993). The utility of gambling. Journal of Risk and Uncertainty, 6, 255–275.

Forrest

, & Simmons

(2008). Sentiment in the betting market on Spanish football. Applied Economics,40(1), 119–126.

Golec

, & Tamarkin

(1991). The degree of inefficiency in the football betting market: Statistical tests. Journal of Financial Economics, 30, 311–323.

Gray

, & Gray

(1997). Testing market efficiency: Evidence from the NFL sports betting market. Journal of Finance, 52, 1725–1737.

Levitt

(2004). Why are gambling markets organized so differently from financial markets? The Economic Journal, 114, 223–246.

Osborne

(2001). Efficient markets? Don't bet on it. Journal of Sports Economics, 2(1), 50–61.

Pankoff

(1968). Market efficiency and football betting. Journal of Business, 41, 203–214.

Paul

, & Weinbach

(2002). Market inefficiency and a profitable betting rule: Evidence from totals on professional football. Journal of Sports Economics, 3, 256–263.

10.

Paul

, Weinbach

, & Weinbach

(2003). Fair bets and profitability in college football gambling. Journal of Economics and Finance, 27(2), 236–242.

11.

Paul

, & Weinbach

(2007). The uncertainty of outcome and scoring effects on Nielsen ratings for Monday Night Football. Journal of Economics and Business, 59(3), 199–211.

12.

Paul

, & Weinbach

(2008a). Does Sportsbook.com set pointspreads to maximize profits? Tests of the Levitt Model of Sportsbook Behavior.Journal of Prediction Markets, 1(3), 209–218.

13.

Paul

, & Weinbach

(2008b). Price setting in the NBA gambling market: Tests of the Levitt Model of Sportsbook Behavior.International Journal of Sports Finance,3(3), 2–18.

14.

Rascher

, & Solmes

(2007). Do fans want close contests? A test of the uncertainty of outcome hypothesis in the National Basketball Association. International Journal of Sport Finance, 2(3), 130–141.

15.

Samuelson

(1952). Probability, utility, and the independence axiom. Econometrica, 20, 670–678.

16.

Sauer

, Brajer

, Ferris

, & Marr

(1988). Hold your bets: Another look at the efficiency of the gambling market for National Football League games. Journal of Political Economy, 96,206–213.

17.

Sauer

(1998). The economics of wagering markets. Journal of Economic Literature, 36, 2021–2064.

18.

Strumpf

K. S.

(2003). Illegal sports bookmakers. Unpublished manuscript.

19.

Zuber

, Gandar

, & Bowers

(1985). Beating the spread: Testing the efficiency of the gambling market for National Football League games. Journal of Political Economy, 93, 800–806.