University of Texas at El Paso DigitalCommons@UTEP Open Access Theses & Dissertations 2018-01-01 An Econometric Analysis Of The 2016-2017 Nba Regular Season Michael Lynn Jaeger University of Texas at El Paso, [email protected] Follow this and additional works at: https://digitalcommons.utep.edu/open_etd Part of the Economics Commons Recommended Citation Jaeger, Michael Lynn, "An Econometric Analysis Of The 2016-2017 Nba Regular Season" (2018). Open Access Theses & Dissertations. 97. https://digitalcommons.utep.edu/open_etd/97 This is brought to you for free and open access by DigitalCommons@UTEP. It has been accepted for inclusion in Open Access Theses & Dissertations by an authorized administrator of DigitalCommons@UTEP. For more information, please contact [email protected]. AN ECONOMETRIC ANALYSIS OF THE 2016-2017 NBA REGULAR SEASON MICHAEL LYNN JAEGER Master’s Program in Economics APPROVED: Thomas M. Fullerton, Ph.D., Chair James H. Holcomb, Ph.D. Joshua Fan, Ph.D. Charles Ambler, Ph.D. Dean of the Graduate School . Dedication My thesis is dedicated to my wife, Ana Jaeger. You have given up so much and allowed me time to study, while you took care of our family. To my daughter, Daniela Jaeger, not only did you keep me on my toes through this process, I read you a lot of economic journals, which I hope will stick for the future. Daniela, thank you for showing me how many much I can accomplish on many sleepless nights. And to our new baby arriving in spring 2019, you will not know the pain and suffering I endured to get to this point. AN ECONOMETRIC ANALYSIS OF THE 2016-2017 NBA REGULAR SEASON by MICHAEL LYNN JAEGER, B.A. THESIS Presented to the Faculty of the Graduate School of The University of Texas at El Paso in Partial Fulfillment of the Requirements for the Degree of MASTER OF SCIENCE Department of Economics and Finance THE UNIVERSITY OF TEXAS AT EL PASO December 2018 Acknowledgements I would like to thank Dr. Tom Fullerton for his continued support and patience during this process. Through his leadership, I was able to complete this thesis and graduate. His lectures influenced and impacted me in my academic growth and as the teacher I am today. I am indebted to his encouragement, mentorship and guidance toward my success and completion of my thesis. I would also like to acknowledge my dedicated thesis committee, Dr. Holcomb and Dr. Fan, for investing their time toward helping me and volunteering to be part of the process. iv Abstract This study examines the on-court performance of the thirty National Basketball Association (NBA) teams during the 2016-17 NBA basketball season. Cross sectional data are employed to analyze the wins for the 2016-17 NBA basketball season. Although the results are inconclusive, there is one notable outcome in the negative variable for human capital payroll. Field goal percentage is favored over other in game statistics. Replication of this study for the 437 teams in National Collegiate Athletics Association provides and intriguing opportunity for further research. v Table of Contents Acknowledgements ........................................................................................................................ iv Abstract ............................................................................................................................................v Table of Contents ........................................................................................................................... vi List of Tables ................................................................................................................................ vii List of Figures .............................................................................................................................. viii Chapter 1: Introduction ....................................................................................................................1 Chapter 2: Literature Review ...........................................................................................................2 Chapter 3: Data and Methodology ...................................................................................................3 Chapter 4: Empirical Results .........................................................................................................11 Chapter 5: Conclusion....................................................................................................................23 References ......................................................................................................................................24 Appendix A: Data ..........................................................................................................................26 Appendix B: Additional Regression Results .................................................................................30 Vita ..............................................................................................................................................33 vi List of Tables Table 3.1: Variables and Units........................................................................................................ 4 Table 3.2: Summary Statistics ........................................................................................................ 6 Table 4.1: OLS Regression With In-Sample Simulation Results ................................................. 11 Table 4.2 OLS Regression Results With White (1980) Homscedasticity Test Summary Table . 12 Table 4.3 OLS Regression With White Standard Errors ............................................................. 14 Table 4.4 Independent Vaiable Marginal Effects Table ............................................................... 21 vii List of Figures Figure 4.1: 2016-2017 NBA Wins vs. Field Goal Percentage per Game ..................................... 13 Figure 4.2: 2016-2017 NBA Wins vs. Average Free Throw Percentage per Game ................... 155 Figure 4.3: 2016-2017 NBA Wins vs. Average Offensive Rebounds per Game ....................... 166 Figure 4.4: 2016-2017 NBA Wins vs. Average Defensive Rebounds per Game ....................... 177 Figure 4.5: 2016-2017 NBA Wins vs. Average Turnovers per Game ........................................ 188 Figure 4.6: 2016-2017 NBA Wins vs. Coaching Salaries .......................................................... 199 Figure 4.7: 2016-2017 NBA Wins vs. Team Payroll.................................................................. 200 Figure 4.8: 2016-2017 NBA Wins vs. Standard Deviation of Payroll ....................................... 211 viii Chapter 1: Introduction The National Basketball League produces an increasingly popular product in the United States and abroad. Games are watched or attended by millions every year, especially as the league continues to expand its market across the globe. However, lost among the hype is attention paid to the empirical analysis of the sport, specifically, the influences of the win-loss records of the regular season. Many have looked at the variables of the glitzy post season (Berri and Eschker, 2005; Wallace, Caudill and Mixon, 2013; Zimmer and Kuethe, 2009), but little has been analyzed regarding the plodding long regular season. The following study examines the potential impacts of both on-court performance measures and several management variables, such as salaries on win-loss records for the 2016- 2017 NBA season. The analysis is similar to what has been used in recent studies of Major League Baseball (MLB) regular season outcomes (Fullerton et al., 2014; Peach et al., 2016; Fullerton and Peach, 2016). There are no guarantees, however, that what works for empirical post-mortems of one spectator sport will be applicable to another segment of the entertainment athletics complex. The study is structured as follows: section two provides an overview of related studies; section three details the data and methodology; and, section four discusses empirical results. The analysis is summarized in the concluding section. A statistical data appendix is included at the end of the document. 1 Chapter 2: Literature Review Many different studies examine the impacts of payroll dispersion on team success. Jewell and Molina (2004) focus on different aspects of MLB and document an inverse correlation between salary dispersion and victories. More recently, Fullerton et al. (2014) provides evidence that payroll dispersion may not affect team win-loss performances. The difference from the highest paid player to the lowest paid player is not found to hurt the team records. As hypothesized, on-field performances are important to the win-loss column. Peach et al. (2016) notes that each season should be looked at “in isolation from predecessors,” due to parameter heterogeneity. That outcome is confirmed by Fullerton and Peach (2016). Beri (1999) looks at the NBA regular season statistics and team wins, but does not include salaries in the analysis. The empirical results of this study show there is a correlation between player performance and team wins. That study cautions that player performances can be affected by trades, free agent acquisitions, and/or minutes played. Roster changes may require adjustments to new playing styles and reduced playing times. Berri and Eschker (2005) examines NBA post- seasons from 1994-2003. That study finds no evidence of player performances being enhanced during the playoffs. The widespread claim of “Prime-Time Players” found to be fictional. Katayama and Nuch (2011)