Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 14Sports Analytics and PerformanceDoping in SportsBenford’s Law and Fraud Detection

The DOI matches its Crossref record; 4 of the 5 references it cites were found in a registry or an index.

NCAA ``Point Shaving'' as an Artifact of the Regression Effect and the Lack of Tie Games

Johnson, Neal·2009·Journal of Sports Economics
DOI 10.1177/1527002508327388
Open this paper in CoChat — free account

Abstract

Wolfers concluded that point shaving may occur in 6% of NCAA Division I basketball games involving a team favored by more than 12 points. His analysis is flawed on two counts. First, a regression effect is introduced when the definition of a strong favorite is based on the betting market's estimate of the winning margin. Second, the effect that a lack of tie games has on the resulting distribution of game outcomes relative to the Vegas spread is mistaken as a shift in the distribution because of point shaving. When combined, the regression effect and the lack of ties generate the observed data patterns. Numerical analysis indicates that even if the betting market makes unbiased estimates of the winning margin, an error with a standard deviation of 1.35 points is sufficient to generate the observed data pattern.

Overview

Integrity signals

Registry

Crossref · 10.1177/1527002508327388

Cites

4 of 4 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Citations

Cites

Research works printed but not linked: 7

  1. Beck, H., 2007, The New York Times, D.1
  2. Cannella, S., 2006, Sports Illustrated, 104, 26
  3. Fridson, M., 2006, Barron's, 86, 48
  4. Gibbs, J., 2007, Point shaving in the NBA: An economic analysis of the National Basketball Association's point spread betting market. Undergraduate Honor's Thesis
  5. Knightly, A.M., 2006, Las Vegas Business Press, 23, 10
  6. Leonhardt, D., 2006, The New York Times, C.1
  7. McCarthy, M., 2007, USA Today, 01c

Cited by

See all 14

Related

See all

Metadata

Authors
Johnson, N.
Affiliations
Pacific Lutheran University (US)
Corresponding author
Johnson, Neal
Venue
Journal of Sports Economics
Publisher
SAGE Publications
Published
2009-02
Volume
10
Issue
1
Pages
59-67
ISSN
  • 1527-0025 (ISSN-L)
  • 1552-7794
DOI
10.1177/1527002508327388
OpenAlex
W2059116951
Semantic Scholar
babc006f706b7329435a273484436caeabba8d41
Cited by
14
References
5
Citations by year
2024: 1 · 2023: 2 · 2022: 1 · 2020: 1 · 2019: 1 · 2018: 2 · 2016: 1 · 2015: 1 · 2013: 1 · 2012: 2
FWCI
1.96
Type
journal article
Language
en
Open access
closed
Licence
journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
Locations
  • Journal of Sports Economics (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Sports Analytics and Performance
  • Social Sciences › Sociology and Political Science › Doping in Sports
  • Physical Sciences › Mathematics › Statistics and Probability › Benford’s Law and Fraud Detection
Keywords
NCAA basketball, regression effect, betting markets, tie games, sports corruption

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

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.