A Quantitative Analysis of Optimal NBA Expansion and Relocation Strategy

Abstract

This thesis undertakes a comprehensive quantitative analysis to uncover why certain National Basketball Association (NBA) teams achieve superior financial outcomes compared to their counterparts, despite displaying similar on-court performances. This paper investigates how various characteristics of a team's host city influence its financial success by utilizing a linear-quadratic regression model to analyze data from 2010 to 2019 of NBA teams and their corresponding Metropolitan Statistical Areas. The findings delineate the optimal attributes of an ideal NBA host city, spotlight prime candidates for potential team expansion or relocation, and highlight inefficiencies among existing teams. Furthermore, the study engages in a comparative analysis between the proposed linear-quadratic model with alternative neural network models, ultimately substantiating the fitter efficacy of the linear-quadratic approach in the context of the available data. This thesis contributes to the discourse by offering a novel perspective on the interplay between urban characteristics and the financial dynamics of professional basketball teams, providing valuable insights for both academic scholars and industry stakeholders.