Measuring competitive balance in sports

Doria Matthew () and Nalebuff Barry ()
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Doria Matthew: Salary Cap Management at NBA, New York, NY, USA
Nalebuff Barry: Yale School of Management, New Haven, Connecticut, USA

Journal of Quantitative Analysis in Sports, 2021, vol. 17, issue 1, 29-46

Abstract: In order to make comparisons of competitive balance across sports leagues, we need to take into account how different season lengths influence observed measures of balance. We develop the first measures of competitive balance that are invariant to season length. The most commonly used measure, the ASD/ISD or Noll-Scully ratio, is biased. It artificially inflates the imbalance for leagues with long seasons (e.g., MLB) compared to those with short seasons (e.g., NFL). We provide a general model of competition that leads to unbiased variance estimates. The result is a new ordering across leagues: the NFL goes from having the most balance to being tied for the least, while MLB becomes the sport with the most balance. Our model also provides insight into competitive balance at the game level. We shift attention from team-level to game-level measures as these are more directly related to the predictability of a representative contest. Finally, we measure competitive balance at the season level. We do so by looking at the predictability of the final rankings as seen from the start of the season. Here the NBA stands out for having the most predictable results and hence the lowest full-season competitive balance.

Keywords: competitive balance; HHI; Noll-Scully index; sports analytics; uncertainty of outcome (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1515/jqas-2020-0006

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