Determining the Economic Factors of American Professional Sports Franchise Valuations Open Access
Saxena, Varun (Spring 2024)
Published
Abstract
This study analyzes the effects of American professional sports teams’ location, in-game success, star players, fan engagement, and business operations on their financial valuation. Metropolitan area population, metropolitan area median personal income, average game attendance, number of team all-stars, regular season wins, franchise championships, and recent championship are the independent variables that capture these effects in this study. These measures are analyzed for the National Football League (NFL) and National Basketball Association (NBA) sports leagues. The methods for these analyses are an Ordinary Least Squares (OLS) regression and Random Forest regression. Across both leagues, population, income, and operating income are the most significant estimators of franchise value, indicating that location and business operations are the most relevant factors in determining franchise value. The in-game success and fan engagement metrics vary in significance based on the model and league. The presence of star players is largely insignificant in determining franchise value across both leagues. The results of this study explain the economic benefits of franchise relocation to larger markets and growth of sponsorship deals, among other phenomena in the NFL and NBA.
Table of Contents
1 Abstract 1
2 Background 1
2.1 American Team Sports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
2.2 American Sports Markets . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
2.3 Franchise Values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.4 OLS Regression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.5 Random Forest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.6 Purpose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
3 Methods 10
3.1 Data Collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
3.2 Independent Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
3.3 Regression Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
4 Results 19
4.1 Summary Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
4.2 OLS Regression Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
4.2.1 NFL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
4.2.2 NBA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
4.2.3 NBA and NFL Combined . . . . . . . . . . . . . . . . . . . . . . . . 34
4.2.4 NFL Team Fixed-Effects . . . . . . . . . . . . . . . . . . . . . . . . . 38
4.3 Random Forest Regression Results . . . . . . . . . . . . . . . . . . . . . . . 39
5 Discussion 43
5.1 Determinants of Franchise Value . . . . . . . . . . . . . . . . . . . . . . . . . 43
5.1.1 Study Takeaways . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
5.1.2 Franchise Relocation . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
5.1.3 Star Power in the NBA . . . . . . . . . . . . . . . . . . . . . . . . . . 45
5.1.4 Importance of Factors Over Time . . . . . . . . . . . . . . . . . . . . 46
5.2 Predictive Capabilities of OLS and Random Forest . . . . . . . . . . . . . . 48
5.3 Study Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
5.4 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
6 References 50
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