The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Widespread Corruption in Sports Gambling: Fact or Fiction?
Abstract
We examine whether point‐shaving is widespread in National Collegiate Athletic Association basketball by comparing bet and game outcomes with those in professional sports. Results suggest that unusual patterns previously suspected to be indicators of point‐shaving are ubiquitous throughout sports and unlikely to be caused by corruption. We suggest that line shading by sports books may explain the anomalies in game and bet outcome distributions.
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Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“However, the high salaries in the NBA make point-shaving by players unlikely.”
From The Point Spread as a Reference Point: Evidence from the National Basketball Association (2022) · cites this paper as Borghesi (2008)
In the citing paper
“This result builds on Borghesi's (2008) in several ways.Perhaps most importantly, it is not only the favorites who fail to cover.”
From The Point Spread as a Reference Point: Evidence from the National Basketball Association (2022) · cites this paper as Borghesi's (2008)
In the citing paper
“Borghesi found that heavy favorites in professional basketball or football games failed to cover the point spread about as often as college teams do.”
From The Point Spread as a Reference Point: Evidence from the National Basketball Association (2022) · cites this paper as Borghesi (2008)
Citations
Cites
Why are Gambling Markets Organised so Differently from Financial Markets?
Levitt, S. D. (2004) · The Economic Journal · doi:10.1111/j.1468-0297.2004.00207.x · Cited by 377
Testing Market Efficiency: Evidence From The NFL Sports Betting Market
GRAY, P. K., & GRAY, S. F. (1997) · The Journal of Finance · doi:10.1111/j.1540-6261.1997.tb01129.x · Cited by 219
Point Shaving: Corruption in NCAA Basketball
Wolfers, J. (2006) · American Economic Review · doi:10.1257/000282806777211757 · Cited by 166
The degree of inefficiency in the football betting market Statistical tests
Golec, J. (1991) · Journal of Financial Economics · doi:10.1016/0304-405x(91)90034-h · Cited by 139
Research works printed but not linked: 7
- Gillespie Rob, 2003, Why bet basketball?, Gambling Times
- 10.1080/00036849000000056 · DOI
- Martin Jeremy, 2007, Going against Public Teams Can Be Winning Strategy., Ultimate Capper
- McCarthy Michael, 2005, Football bettors put billions on the line, USA Today
- National Collegiate Athletic Association, 2004, 2003 NCAA national study on collegiate sports wagering and associated behavior
- 10.1080/096031001752236780 · DOI
- 10.1111/j.1540-6261.1994.tb04429.x · DOI
Cited by
Grant, D., & Green, W. B. (2013) · Empirical Economics · doi:10.1007/s00181-012-0578-0 · Cited by 37
Paul, R. J., & Weinbach, A. P. (2011) · Journal of Sports Economics · doi:10.1177/1527002510385904 · Cited by 20
A test of the widespread-point-shaving theory
Borghesi, R., & Dare, W. (2009) · Finance Research Letters · doi:10.1016/j.frl.2009.04.004 · Cited by 18
Self-citationNCAA ``Point Shaving'' as an Artifact of the Regression Effect and the Lack of Tie Games
Johnson, N. (2009) · Journal of Sports Economics · doi:10.1177/1527002508327388 · Cited by 14
A case study in sports law analytics: The debate on widespread point shaving
Borghesi, R. (2015) · Journal of Sports Analytics · doi:10.3233/jsa-150011 · Cited by 9
Self-citation
Metadata
- Authors
- Borghesi, R.
- Affiliations
- Texas State University McCoy College of Business Administration Department of Finance and Economics 601 University Drive San Marcos TX 78666 USA
- Venue
- Southern Economic Journal
- Publisher
- Wiley
- Published
- 2008-04
- Volume
- 74
- Issue
- 4
- Pages
- 1063-1069
- ISSN
- 0038-4038
- 2325-8012
- Cited by
- 30
- References
- 4
- Language
- en
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- The paper
- Borghesi, R. (2008). Widespread Corruption in Sports Gambling: Fact or Fiction? Southern Economic Journal. https://doi.org/10.1002/j.2325-8012.2008.tb00881.x
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
