Cited by 15Sports Analytics and PerformanceDecision-Making and Behavioral EconomicsFinancial Markets and Investment Strategies

Are Sports Bettors Biased toward Longshots, Favorites, or Both? A Literature Review

Open access
Newall, Philip W. S., Cortis, Dominic·2021·Risks

Abstract

A large body of literature on the favorite–longshot bias finds that sports bettors in a variety of markets appear to have irrational biases toward either longshots (which offer a small chance of winning a large amount of money) or favorites (which offer a high chance of winning a small amount of money). While early studies in horse racing led to an impression that longshot bias is dominant, favorite bias has also now been found in a variety of sports betting markets. This review proposes that the evidence is consistent with both biases being present in the average sports bettor. Sports betting markets with only two potential outcomes, where the favorite therefore has a probability >0.5 of happening, often produce favorite bias. Sports betting markets with multiple outcomes, where the favorite’s probability is usually <0.5, appear more consistent with longshot bias. The presence of restricted odds ranges within any given betting market provides an explanation for why single studies support, at most, one bias. This literature review highlights how individual sports bettors might possess biases toward both highly likely, and highly unlikely, events, a contradictory view that has not been summarized in detail before.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3390/risks9010022

Cites

75 of 75 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 24

  1. Asch, Peter, Burton G. Malkiel, and Richard E. Quandt. 1982. Racetrack betting and informed behavior. Journal of Financial Economics 10: 187-94.
  2. Brailsford, Timothy J., Philip K. Gray, Stephen A. Easton, and Stephen F. Gray. 1995. The efficiency of australian football betting markets. Australian Journal of Management 20: 167-95.
  3. Braun, Sebastian, and Michael Kvasnicka. 2013. National sentiment and economic behavior evidence from online betting on european football. Journal of Sports Economics 14: 45-64.
  4. Bruce, Alistair C., and Johnnie E. V. Johnson. 2000. Investigating the roots of the favourite-longshot bias: An analysis of decision making by supply-and demand-side agents in parallel betting markets. Journal of Behavioral Decision Making 13: 413-30.
  5. Buhagiar, Ranier, Dominic Cortis, and Philip WS Newall. 2018. Why do some soccer bettors lose more money than others? Journal of Behavioral and Experimental Finance 18: 85-93.
  6. Cain, Michael, David Law, and David Peel. 2000. The favourite-longshot bias and market efficiency in UK football betting. Scottish Journal of Political Economy 47: 25-36.
  7. Cain, Michael, David Law, and David Peel. 2003. The Favourite-Longshot bias, bookmaker margins and insider trading in a variety of betting markets. Bulletin of Economic Research 55: 263-73.
  8. Constantinou, Anthony, and Norman Fenton. 2013. Profiting from arbitrage and odds biases of the european football gambling market. The Journal of Gambling Business and Economics 7: 41-70.
  9. Coval, Joshua D., and Tobias J. Moskowitz. 1999. Home bias at home: Local equity preference in domestic portfolios. The Journal of Finance 54: 2045-73.
  10. Deschamps, Bruno, and Olivier Gergaud. 2012. Efficiency in betting markets: Evidence from english football. The Journal of Prediction Markets 1: 61-73.
  11. Golec, Joseph, and Maurry Tamarkin. 1991. The degree of inefficiency in the football betting market: Statistical tests. Journal of Financial Economics 30: 311-23.
  12. Gray, Philip K., and Stephen F. Gray. 1997. Testing market efficiency: Evidence from the NFL sports betting market. The Journal of Finance 52: 1725-37.
  13. Kanto, Antti J., Gunnar Rosenqvist, and Arto Suvas. 1992. On utility function estimation of racetrack bettors. Journal of Economic Psychology 13: 491-98.
  14. Paul, Rodney J., and Andrew P. Weinbach. 2012. Wagering preferences of nfl bettors: Determinants of betting volume. Journal of Prediction Markets 6: 42-55.
  15. Pleskac, Timothy J., and Ralph Hertwig. 2014. Ecologically rational choice and the structure of the environment. Journal of Experimental Psychology: General 143: 2000-19.
  16. Shin, Hyun Song. 1992. Prices of state contingent claims with insider traders, and the favourite-longshot bias. The Economic Journal 102: 426-35.
  17. Snowberg, Erik, and Justin Wolfers. 2010. Explaining the Favorite-Long shot bias: Is it risk-love or misperceptions? Journal of Political Economy 118: 723-46.
  18. Stark, Dudley, and Dominic Cortis. 2017. Balancing the book: Is it necessary and sufficient? The Journal of Gambling Business and Economics 11: 1-6.
  19. Sung, Ming-Chien, Johnnie Eric Victor Johnson, and Itiel E. Dror. 2009. Complexity as a guide to understanding decision bias: A contribution to the favorite-longshot bias debate. Journal of Behavioral Decision Making 22: 318-37.
  20. Terrell, Dek, and Amy Farmer. 1996. Optimal betting and efficiency in parimutuel betting markets with information costs. The Economic Journal 106: 846-68.
  21. Vaughan Williams, Leighton, and David Paton. 1997. Why is there a favourite-longshot bias in british racetrack betting markets? The Economic Journal 107: 150-58.
  22. Winter, Stefan, and Martin Kukuk. 2006. Risk love and the favorite-longshot bias: Evidence from german harness horse racing. Schmalenbach Business Review (Sbr) 58: 349-64.
  23. Woodland, Linda M., and Bill M. Woodland. 1994. Market efficiency and the favorite-longshot bias: The baseball betting market. The Journal of Finance 49: 269-79.
  24. CrossRef · DOI

Cited by

Sorted by citations

Authors
Newall, P. W. S., & Cortis, D.
Affiliations
  • Central Queensland University (AU)
  • University of Malta (MT)
Corresponding author
Newall, Philip W. S.
Venue
Risks
Publisher
MDPI AG
Published
2021-01-12
Volume
9
Issue
1
Pages
22
ISSN
2227-9091 (ISSN-L)
OpenAlex
W3120981661
Cited by
14
References
75
Citations by year
2026: 1 · 2025: 2 · 2024: 3 · 2023: 4 · 2022: 1 · 2021: 3
FWCI
0.54
Type
journal article
Language
en
Open access
Locations
  • Risks (publishedVersion, cc-by)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Econstor (Econstor) (submittedVersion, cc-by)
  • Figshare (submittedVersion, cc-by)
Topics
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Sports Analytics and Performance
  • Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
  • Social Sciences › Economics, Econometrics and Finance › Finance › Financial Markets and Investment Strategies
Keywords
favorite-longshot bias, sports betting, horse racing betting, betting odds

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review