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The relative wages of offense and defense in the NBA: a setting for win-maximization arbitrage?

Author

Listed:
  • Ehrlich Justin

    (Assistant Professor of Sport Analytics, Department of Sport Management, Falk College, Syracuse University, Syracuse, NY, USA)

  • Sanders Shane

    (Associate Professor of Sports Economics & Analytics, Department of Sport Management, Falk College, Syracuse University, 316 MacNaughton Hall, Syracuse, NY, USA)

  • Boudreaux Christopher J.

    (Florida Atlantic University, Department of Economics, Boca Raton, FL, USA)

Abstract

In basketball, a point scored on offense carries a nearly identical on-court (win) value as a point denied on defense (e.g. within the Pythagorean expected wins model). Both outcomes bear the same score margin implication. As such, a win-maximizing team is expected to value the two outcomes equally. We ask whether the salaries of NBA players reveal such an equality among NBA teams. If not, a win-maximizing team would enjoy a disequilibrium arbitrage opportunity, whereby the team could improve, in expectation, even while reducing roster payroll. We considered the 322 National Basketball Association (NBA) players during the 2016–2017 season who were on a full-season contract for which the salary was not stipulated under the NBA Collective Bargaining Agreement. We estimated the implied marginal wage of an additional point created on offense (denied on defense) per 100 possessions. Namely, we constructed a set of fixed effects, ordinary least squares regression models that specify a player’s pre-assigned 2016–2017 player salary as a function of primary team fixed effects, offensive adjusted plus minus, defensive adjusted plus minus, position-of-play, and control variables such as age. We conclude that a win-maximizing NBA team currently faces a substantial arbitrage opportunity. Namely, one unit of offense carries the same estimated implicit salary as approximately two and a half to four units of defense. We also find moderate between-team variation in adjusted plus minus return on payroll allocations.

Suggested Citation

  • Ehrlich Justin & Sanders Shane & Boudreaux Christopher J., 2019. "The relative wages of offense and defense in the NBA: a setting for win-maximization arbitrage?," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 15(3), pages 213-224, September.
  • Handle: RePEc:bpj:jqsprt:v:15:y:2019:i:3:p:213-224:n:5
    DOI: 10.1515/jqas-2018-0095
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    References listed on IDEAS

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    1. Macdonald Brian, 2011. "A Regression-Based Adjusted Plus-Minus Statistic for NHL Players," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 7(3), pages 1-31, July.
    2. Kevin J. Stiroh, 2007. "Playing For Keeps: Pay And Performance In The Nba," Economic Inquiry, Western Economic Association International, vol. 45(1), pages 145-161, January.
    3. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    4. Johnny Ducking & Peter Groothuis & James Hill, 2015. "Exit Discrimination in the NFL: A Duration Analysis of Career Length," The Review of Black Political Economy, Springer;National Economic Association, vol. 42(3), pages 285-299, September.
    5. Gramacy Robert B. & Taddy Matt & Jensen Shane T., 2013. "Estimating player contribution in hockey with regularized logistic regression," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 9(1), pages 97-111, March.
    6. Johnny Ducking & Peter Groothuis & James Hill, 2015. "Exit Discrimination in the NFL: A Duration Analysis of Career Length," The Review of Black Political Economy, Springer;National Economic Association, vol. 42(3), pages 285-299, September.
    7. Macdonald Brian, 2012. "Adjusted Plus-Minus for NHL Players using Ridge Regression with Goals, Shots, Fenwick, and Corsi," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 8(3), pages 1-24, October.
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    Cited by:

    1. David Rösch & Florian Schultz & Oliver Höner, 2021. "Decision-Making Skills in Youth Basketball Players: Diagnostic and External Validation of a Video-Based Assessment," IJERPH, MDPI, vol. 18(5), pages 1-17, February.
    2. Shankar Ghimire & Justin A Ehrlich & Shane D Sanders, 2020. "Measuring individual worker output in a complementary team setting: Does regularized adjusted plus minus isolate individual NBA player contributions?," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-11, August.

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