Revenue per Quality of College Football Recruit

Abstract

There is significant debate about compensation of college athletes in revenue generating sports. In college football, the potential heterogeneity in player value has received little attention in the discussion. The relationship between player quality, team performance, and sport-specific revenue should inform any compensation scheme for college football players. In this article, we provide estimates of player monetary value in college football. This is the first study to exploit player-specific ex ante recruit ratings, team performance, and football-specific revenue and profit (revenue net of expenditures) to infer player valuations. This allows us to estimate value for players whose performance can be difficult to measure given traditional sport metrics. We use a unique data set which records individual recruits by ex ante star rating annually for every Football Bowl Subdivision (FBS) school and combine that data with data on team performance, bowl appearances by type, and football-specific revenue. Using a valuation approach which links player-specific quality to team performance and subsequently to revenue, we infer the value of recruits by their ex ante recruit rating. We estimate that five-star recruits increase annual revenue by US$650,000, four-star recruits increase revenue by roughly US$350,000, and three-star recruits increase revenue by US$150,000. Two-star recruits, however, are negatively related to revenue and profit, with two-star athletes reducing annual revenue by US$13,000. Overall, our results imply that player valuations are heterogeneous and that ex ante ratings of player quality are strongly related to school-specific football revenue and profit and may be predictive measures in a compensation scheme.

What is the Impact of Post-Season Bowl Participation on a Football Program's On-Field Success, Recruiting and Revenues?

“…The first is total revenue data from the Equity in Athletics Data Analysis (EADA) website from the US Department of Education, the second is aggregate athletic department program by revenue sources from USA Today, and finally individual athletic program revenues and expenses are reported from the Membership Financial Reporting System that Division I programs send to the NCAA each year. Bergman and Logan (2020), Brook (2016), and Hunsberger and Gitter (2015) each use college football team revenue data using EADA data. There are pros and cons to using this data.…”

“…College recruiting research has addressed the high school athlete's school choice (Dumond et al, 2008), the relationship between recruit quality and team performance (Bergman & Logan, 2016; Langelett, 2003), valuing the revenue generated by recruit quality (Bergman & Logan, 2020) and examining how the cost of attendance impacts recruiting quality (Bradbury & Pitts, 2018). In this inquiry, post-season bowl game participation in the prior season is hypothesized to positively affect FBS college football program recruiting in the current season.…”

“…Bergman and Logan (2020), Brook (2016), and Hunsberger and Gitter (2015) each use college football team revenue data using EADA data. There are pros and cons to using this data.…”

Who Profits from Amateurism? Rent-Sharing in Modern College Sports

“…More recently, a series of papers have used recruiting rankings to estimate the MRP of college football and basketball players (Borghesi 2017;Bergman and Logan 2020). An advantage of this approach is that it leverages a metric of skill that is measured prior to an athlete entering college and is available for all players.…”

“…One difficulty in interpreting these studies is the potential for reverse causality --that is, do high-revenue schools attract good athletes, or do good athletes increase revenues for schools? Including school fixed effects can address this difficulty if the school-specific factors are time-invariant, but this reduces the estimated MRP by roughly 70 percent (Bergman and Logan 2020).…”