Exploiting the “Win But Does Not Cover” Phenomenon in College Basketball

Published date01 February 2018
Date01 February 2018
The Financial Review 53 (2018) 185–204
Exploiting the “Win But Does Not Cover”
Phenomenon in College Basketball
Jason P. Berkowitz
St. John’s University
Craig A. Depken II
University of North Carolina-Charlotte
John M. Gandar
University of North Carolina-Charlotte
Wolfers (2006) was the first to document that heavy favorites in college basketball win
but fail to cover the pre-game point spread at a statistically higher rate than expected. We
generate a hedged strategy to exploit the “win but does not cover” phenomenon using two
wagers: a bet on the underdog sides line and a bet on the favorite money line. While one bet
is guaranteed to win regardless of the outcome, both bets win if the favorite wins but does not
cover. We show that the minimum-variance portfolio best exploits this anomaly, yielding an
average return of 0.34% per game and a positive return in fiveof the seven seasons of college
basketball analyzed.
Keywords: portfolio selection, minimum-variance portfolio, betting markets
JEL Classifications: G11, Z23, L83
Corresponding author: Department of Economics & Finance, Tobin College of Business, St. John’s
University,101 Astor Place, New York,NY 10003; Phone: (212) 284-7022; E-mail: berkowij@stjohns.edu.
We are grateful for valuable comments from an anonymous referee, Mikael Bergbrant, Anna Martin,
and participants at the 2016 Eastern Finance Association annual meeting and 2015 Southern Finance
Association annual meeting.
C2018 The Eastern Finance Association 185
186 J. P. Berkowitz et al./The Financial Review 53 (2018) 185–204
1. Introduction
Wolfers (2006) shows that heavy favorites in National Collegiate Athletic As-
sociation (NCAA) men’s basketball, defined as teams favored to win by 12 or more
points, tend to win but not cover the pre-game betting line (the “point spread” or
“sides” line) more frequently than expected. While the reason for this disparity is not
clear, no evidence disputes the finding that heavyfavorites win but do not cover more
frequently than expected.1In this paper, we create a profitable betting strategy that
exploits the “win but does not cover” (WDNC) phenomenon.
Several authors have pointed out similarities between betting markets and tradi-
tional financial markets as well as some unique benefits of utilizing betting markets
(see Gandar, Zuber, O’Brien and Russo, 1988; Camerer, 1989; Brown and Sauer,
1993a,b; Dare and Scott MacDonald, 1996; Averyand Chevalier, 1999; Levitt, 2004).
Both markets have a wide dissemination of information, professionals who are ready
to exploit mispricing, an initial offering, and both offer market participants the abil-
ity to diversify across various assets. In addition, betting markets are like financial
derivatives in that they are both zero-sum games, with one side winning and the
other side losing.2Furthermore, betting markets have characteristics beyond those of
traditional financial markets in that they yield terminal values that allow researchers
to compare the true price of an asset to the market or trading price.
In this paper, we investigate three possible strategies to exploit the WDNC
phenomenon in the context of a portfolio of bets on select college basketball games
with heavy favorites. In each case, we diversifyacross two different betting markets:
betting on the underdog in the sides line market and betting on the favorite in the
money line market. Wedesign a na¨
ıve portfolio, in which half of the money is placed
on each bet, a minimum-variance portfolio, and an optimal portfolio, as defined by
modern portfolio theory. We show that the minimum-variance portfolio exploits the
WDNC anomaly better than either the na¨
ıve portfolio or the optimal portfolio.
While the optimal portfolio does well in some seasons, it struggles in seasons
when one of the bets has a historical negative return. In such seasons, the optimal
portfolio calls for investingin only the wager with the positive return that dramatically
lowers the portfolio’s expected returns and increases the portfolio’s risk exposure.
The minimum-variance portfolio has many characteristics that make it attractive in
betting markets, specifically its lack of reliance on historical returns and its ability to
exploit risk-based pricing anomalies, as documented by Scherer (2011). The na¨
strategy yielded an average return of 0.02% per game over the seven seasons, the
minimum-variance portfolio yields an average return of 0.34% per game over the
seven seasons while yielding a profit in five of the seven seasons analyzed, and
1Wolfers (2006) suggests point shaving whereas others suggest game management (see e.g., Borghesi,
2008; Bernhardt and Heston, 2010).
2Sports betting can result in a push, when neither side wins nor loses, resulting in all wagers being returned
to the bettors.

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