From Performance to Pay: Uncovering Economic Efficiency and Systemic Inequalities in NBA Salary Determination

Haoxin Liu

doi:10.54097/az81v382

Authors

Haoxin Liu

DOI:

https://doi.org/10.54097/az81v382

Keywords:

Sports Marketing, NBA, Productivity and Pay, Pay dispersion.

Abstract

This paper addresses the intricate interaction between player performance and compensation in the NBA, offering a close examination of the role of measurable productivity metrics in establishing compensation. Leveraging the availability and quantifiability of sports data—points, assists, rebounds, and so on—the paper identifies the special advantage of the NBA as a case study compared to industries where output is less directly observable. The paper weaves together five major themes: the explicit performance-pay nexus, the influence of pay disparity on team cohesion, the influence of the salary cap on competitive balance and economic welfare, and the return on investment (ROI) to franchises, as well as pervasive gender and racial disparities in wage distribution. Using a range of methodological approaches, the study analyzes traditional determinants of player compensation, the forecasting constraints of these factors, and broader economic implications of compensation differences. The research provides practical recommendations to inform policy debate and labor market practices, and by virtue of the general themes engaged with, makes a contribution to the broader economic literature on wage determination and equity across economic disciplines.

Downloads

Download data is not yet available.

References

[1] CNN Sports. Major sport salaries: NFL, NBA, MLB. CNN, 2022, 8 (9). https://www.cnn.com/2022/08/09/sport/major-sport-salaries-nfl-nba-mlb-spt-intl/index.html.

[2] Sarlis V, Papageorgiou G, Tjortjis C. Leveraging Sports Analytics and Association Rule Mining to Uncover Recovery and Economic Impacts in NBA Basketball. Data, 2024, 9 (7): 83.

[3] Simmons R. Professional labor markets in the Journal of Sports Economics. Journal of Sports Economics, 2022, 23 (6): 728 - 748.

[4] Halevy N, Chou E Y, Galinsky A D, Murnighan J K. When hierarchy wins: Evidence from the national basketball association. Social Psychological and Personality Science, 2012, 3 (4): 398 - 406.

[5] Autor D H, Dorn D. The growth of low-skill service jobs and the polarization of the US labor market. American Economic Review, 2013, 103 (5): 1553 - 1597.

[6] Biancalani F, Gnecco G, Metulini R. The relationship between players' average marginal contributions and salaries: an application to NBA basketball using the generalized Shapley value. Statistica Applicata, 2023, 35 (2): 1 - 29.

[7] Papps K L. Sports at the vanguard of labor market policy. IZA World of Labor, 2020.

[8] Sarlis V, Tjortjis C. Sports analytics: data mining to uncover NBA player position, age, and injury impact on performance and economics. Information, 2024, 15 (4): 242.

[9] Özbalta E, Yavuz M, Kaya T. National Basketball Association Player Salary Prediction Using Supervised Machine Learning Methods. Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation: Proceedings of the INFUS 2021 Conference, 2022: 189 - 196.

[10] Papadaki I, Tsagris M. Are NBA Players' Salaries in Accordance with Their Performance on Court? Advances in Econometrics, Operational Research, Data Science and Actuarial Studies: Techniques and Theories, 2022: 405 - 428.

[11] Terner Z, Franks A. Modeling player and team performance in basketball. Annual Review of Statistics and Its Application, 2021, 8 (1): 1 - 23.

[12] Johnson C, Minuci E. Wage discrimination in the NBA: Evidence using free agent signings. Southern Economic Journal, 2020, 87 (2): 517 - 539.

[13] Chatzistamoulou N, Kostas K, Theodor A. Salary cap, organizational gap, and catch-up in the performance of NBA teams: A two-stage DEA model under heterogeneity. Journal of Sports Economics, 2022, 23 (2): 123 - 155.

[14] Wang Y, Liu W, Liu X. Explainable AI techniques with application to NBA gameplay prediction. Neurocomputing, 2022, 483: 59 - 71.

[15] Stiroh K J. Playing for Keeps: Pay and Performance in the NBA. Economic Inquiry, 2007, 45 (1): 145 - 161.

[16] Kim P, Lee S H, Moon J. Evaluating the operational efficiency of NBA teams on franchise value: An assessment of data envelopment analysis. Plos One, 2024, 19 (3): e0297797.

[17] Naito H, Takagi Y. Is racial salary discrimination disappearing in the NBA? evidence from data during 1985 - 2015. International Review of Applied Economics, 2017, 31 (5): 651 - 669.

[18] Olsen A, Leeds M A. Integration and Team Performance in the NBA. Journal of Sports Economics, 2024, 25 (2): 257 - 278.

[19] Keefer Q. Sunk costs in the NBA: the salary cap and free agents. Empirical Economics, 2021, 61 (6): 3445 - 3478.

[20] Assani S, Mansoor M S, Asghar F, Li Y, Yang F. Efficiency, RTS, and marginal returns from salary on the performance of the NBA players: A parallel DEA network with shared inputs. Journal of Industrial and Management Optimization, 2022, 18 (3): 2001 - 2016.

[21] Oved N, Feder A, Reichart R. Predicting in-game actions from interviews of NBA players. Computational Linguistics, 2020, 46 (3): 667 - 712.

[22] Mishel L, Bivens J. Identifying the policy levers generating wage suppression and wage inequality. Economic Policy Institute, 2021, 13.

[23] Wen R, Cao Q, Wang H. Are Pay Decisions Based on Pre-Contract Efficiency Necessarily Correct? Evidence From Players Contracts of National Basketball Association. SAGE Open, 2023, 13 (4): 21582440231204149.

[24] Cao Z, Price J, Stone D F. Performance under pressure in the NBA. Journal of Sports Economics, 2011, 12 (3): 231 - 252.

[25] Shao W C, Zhang H, Chou L C, Ye X X. Comparing athletes' mastery of salary information before and during the COVID-19 pandemic: Evidence from the national basketball association. Economic Modelling, 2023, 128: 106517.