Team Payroll Versus Performance in Professional Sports: Is Increased Spending Associated with Greater Success?
by Grant Shorin
Abstract
Professional sports are a billion-dollar industry, with player salaries accounting for the largest expenditure. Comparing results between the four major North American leagues (MLB, NBA, NHL, and NFL) and examining data from 1995 through 2015, this paper seeks to answer the following question: do teams that have higher payrolls achieve greater success, as measured by their regular season, postseason, and financial performance? Multiple data visualizations highlight unique relationships across the three dimensions and between each sport, while subsequent empirical analysis supports these findings. After standardizing payroll values and using a fixed effects model to control for team-specific factors, this paper finds that higher payroll spending is associated with an increase in regular season winning percentage in all sports (but is less meaningful in the NFL), a substantial rise in the likelihood of winning the championship in the NBA and NHL, and a lower operating income in all sports.
Professor Peter Arcidiacono, Faculty Advisor
Professor Kent Kimbrough, Faculty Advisor
JEL Codes: Z2, Z20, Z23, J3
Determinants of Franchise Value in the National Basketball Association
By Matthew Van Liedekerke
Franchise values in the National Basketball Association (NBA) have more than tripled over the last five years, with the average franchise worth $1.36 billion. Using panel data on NBA franchises between 2009 and 2016, this paper finds that market, performance, star players, and brand are significant determinants of franchise value at the team level and the NBA’s television contract is the primary driver of league-wide franchise value appreciation. The valuation methodologies used in this paper predict that a franchise in Seattle would be worth $1.4 billion in 2017, which could inform the NBA’s decision on expansion.
Advisors: Connel Fullenkamp, Alison Hagy, Kent Kimbrough | JEL Codes: Z2, Z23, G32
Long-Term Contracts and Predicting Performance in MLB
By Drew Goldstein
In this paper, I examine whether MLB teams are capable of using players’ past performance data to sufficiently estimate future production. The study is motivated by the recent trend by which teams have increasingly signed long-term contracts that lock in players for up to ten seasons into the future. To test this question, I define the “initial years” of a player’s career to represent a team’s available information at the time of determining whether or not to sign him. By analyzing the predictive ability these initial years have on subsequent performance statistics, I am looking to answer whether—and if so for how long—teams can justify signing players to long-term contracts with guaranteed salaries. I also compare the results of the predictive tests with actual contract data to determine the per-dollar returns on these deals for different types of contracts.
I conclude from my analysis that a player’s past performance does in fact provide sufficient insight into his future value for teams to make informed decisions at the time of signing a contract. Teams are able to better predict the future production of potential signees by examining their consistency and relative value in the initial seasons of their careers. Furthermore, the results from examining the contract data coincide with my findings on performance; teams and players arrive at salaries for long-term contracts that divide the future risk between the two parties. The returns on long-term contracts are thus demonstrated to be higher than for short-term contracts, as the overall value of longer deals compensates teams for the associated higher annual salaries.
Advisors: Peter Arcidiacono, Michelle Connolly, Duncan Thomas | JEL Codes: Z2, Z22, Z23
