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Cited by 52Sports Analytics and PerformanceSports Performance and TrainingStatistical Methods and Bayesian Inference

How often does the best team win? A unified approach to understanding randomness in North American sport

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Lopez, Michael J., Matthews, Gregory J., Baumer, Benjamin S.·2018·The Annals of Applied Statistics
DOI 10.1214/18-aoas1165
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Abstract

Statistical applications in sports have long centered on how to best separate signal (e.g., team talent) from random noise. However, most of this work has concentrated on a single sport, and the development of meaningful cross-sport comparisons has been impeded by the difficulty of translating luck from one sport to another. In this manuscript we develop Bayesian state-space models using betting market data that can be uniformly applied across sporting organizations to better understand the role of randomness in game outcomes. These models can be used to extract estimates of team strength, the between-season, within-season and game-to-game variability of team strengths, as well each team’s home advantage. We implement our approach across a decade of play in each of the National Football League (NFL), National Hockey League (NHL), National Basketball Association (NBA) and Major League Baseball (MLB), finding that the NBA demonstrates both the largest dispersion in talent and the largest home advantage, while the NHL and MLB stand out for their relative randomness in game outcomes. We conclude by proposing new metrics for judging competitiveness across sports leagues, both within the regular season and using traditional postseason tournament formats. Although we focus on sports, we discuss a number of other situations in which our generalizable models might be usefully applied.

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58 of 58 references verified0 citation errors · 0 not checkable

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Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Normalized implied probabilities are accurate, unbiased, and efficient estimates of the true unknowable probabilities.

    “Many different researchers have shown that these normalized implied probabilities are accurate, unbiased, and efficient estimates of the true unknowable probabilities (see Lopez et al., 2018 for discussion and an extensive list of references).”

    From Big ideas in sports analytics and statistical tools for their investigation (2023) · cites this paper as Lopez et al., 2018

  • Betting market data is probably the best source for estimating the true probability of a team winning a game.

    “First, betting market data is probably the best source for estimating the true probability of a team winning a game.”

    From Big ideas in sports analytics and statistical tools for their investigation (2023) · cites this paper as Lopez et al., 2018

  • Lopez et al. (2018) extend Glickman and Stern (1998)'s state-space model to understand randomness in the four major American sports leagues.

    “More recently, Lopez et al. (2018) extend Glickman and Stern (1998)'s state-space model to understand randomness in the four major American sports leagues.”

    From Big ideas in sports analytics and statistical tools for their investigation (2023) · cites this paper as Lopez et al. (2018)

  • Both Glickman and Stern (1998) and Lopez et al. (2018) motivate the usefulness of model-based measures of team strength by demonstrating their superiority to low-resolution win-loss records.

    “Both papers motivate the usefulness of model-based measures of team strength by demonstrating their superiority to low-resolution win-loss records.”

    From Big ideas in sports analytics and statistical tools for their investigation (2023) · cites this paper as Lopez et al. (2018)

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Related

Authors
Lopez, M. J., Matthews, G. J., & Baumer, B. S.
Affiliations
Loyola University Chicago (US)
ORCID
Venue
The Annals of Applied Statistics
Publisher
Institute of Mathematical Statistics
Published
2018-12-01
Volume
12
Issue
4
Pages
2483-2516
ISSN
  • 1932-6157 (ISSN-L)
  • 1941-7330
DOI
10.1214/18-aoas1165
OpenAlex
W2579988816
Cited by
52
References
60
Citations by year
2026: 3 · 2025: 5 · 2024: 12 · 2023: 6 · 2022: 5 · 2021: 7 · 2020: 7 · 2019: 5 · 2018: 2
FWCI
8.00
Type
journal article
Language
en
Open access
Locations
  • The Annals of Applied Statistics (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • Creative Matter (Skidmore College) (submittedVersion)
  • Loyola eCommons (Loyola University of Chicago) (submittedVersion, cc-by-nc-nd)
  • Smith ScholarWorks (Smith College) (submittedVersion, cc-by)
  • Project Euclid (Cornell University) (submittedVersion)
  • arXiv (Cornell University)
Topics
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Sports Analytics and Performance
  • Health Sciences › Medicine › Orthopedics and Sports Medicine › Sports Performance and Training
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Keywords
home advantage, Bayesian state-space model, NFL, NHL, NBA, Major League Baseball

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