-
About
Our Story
back- Our Mission
- Our Leadership
- Accessibility
- Careers
- Diversity, Equity, Inclusion
- Learning Science
- Sustainability
Our Solutions
back
-
Community
Community
back- Newsroom
- Discussions
- Webinars on Demand
- Digital Community
- The Institute at Macmillan Learning
- English Community
- Psychology Community
- History Community
- Communication Community
- College Success Community
- Economics Community
- Institutional Solutions Community
- Nutrition Community
- Lab Solutions Community
- STEM Community
- Newsroom
- Macmillan Community
- :
- Economics Community
- :
- Economics Blog
- :
- Measuring Exploitation In Women's College Basketba...
Measuring Exploitation In Women's College Basketball
- Subscribe to RSS Feed
- Mark as New
- Mark as Read
- Bookmark
- Subscribe
- Printer Friendly Page
- Report Inappropriate Content
Exploitation was defined by Joan Robinson as a worker being paid a wage less than their marginal revenue product. As noted in Sports Economics, we expect this to happen if the worker's bargaining power is limited by an employer with monopsonistic power. A good example was Major League Baseball prior to the enactment of free agency in the mid-1970s. Another good example is college sports in the United States. The NCAA limits a college athlete's compensation to the cost of attendance. The existence of such a limit suggests a college athlete would be exploited. In fact, if that wasn't the case then we would wonder why the limit was even necessary.
Although exploitation happens outside the world of sports, the world of sports gives us an opportunity to measure the size of the effect. The first approach to measuring exploitation in sports came from Gerald Scully. In 1974, Gerald Scully empirically examined how the reserve clause -- which forced Major League Baseball players to only negotiate with one team -- led to the exploitation of professional baseball players.
The Scully approach involves estimating two relationships.
First, one looks at the link between team revenue, team wins, and a collection of control variables. From this model, we derive the dollar value of a team win.
One then examines the link between team wins and player statistics. This model is used to measure how many wins a player creates.
The Scully model has been used in a number of academic articles. Despite its repeated use, though, it has some serious flaws. For example, there is no value in the Scully model for participating in practice. A player is only given credit for producing wins in the actual games. But practice is a large part of what any athlete does and those players who don't produce wins do provide economic value to a team. In other words, contrary to the words of Allen Iverson, it is likely practice matters.
There is also an issue with the revenue model. As detailed in Sports Economics (and a working paper I wrote with Anthony Krautmann), the value of a win in baseball changes dramatically over time. Specifically, if we look back to the original sample Scully considered from the late 1960s, the value of a win is so large that the amount of revenue Scully attributes to the players exceeds all the revenue in the league. In more recent years -- as noted in a paper I wrote with Michael Leeds and Peter von Allmen (and also noted in Sports Economics) -- the impact of fixed revenues (i.e. revenues that are not impacted by wins such as broadcasting revenues), causes the estimated value of a wins to be so low that it appears most (if not all) players are now dramatically overpaid.
Given the problems with the Scully model, an alternative approach is needed. In the Marquette Sports Law Review -- and yes, in Sports Economics -- the following method for college basketball was briefly described.
We begin by looking at how pay is allocated in the National Basketball Association. As Larry Coon's NBA Salary Cap FAQ details, the NBA pays about 50% of league revenue to its players. In addition, the average minimum pay in the first year of a contract is currently $1.71 million (minimum pay varies by years of experience). Since average pay -- or total revenue shared with players divided by the number of players in the league -- was $4.24 million in 2017-18, the NBA currently sets its minimum pay at about 35% of its average pay.
One can think of minimum pay as what a player gets for practice. Again, practice matter. So, everyone's pay should begin with this payment.
Of course, some players also produce wins and those players should be paid more. Here are the specific steps one follows to allocate revenue in terms of how many wins each player produces. For illustrative purposes, the 2017-18 women's basketball team at South Carolina University is examined.
- Determine how much revenue should be paid to the players: According to the Department of Education, the South Carolina's women's basketball team reported $2,046,234 in revenue in 2016-17 (this is the last year data was available). If we assume revenue was the same in 2017-18 (likely it was higher -- as revenues grow over time), and the South Carolina Gamecocks gave 50% of its revenue to its players, then the players in 2017-18 would be splitting $1,023,117.
- Determine average and minimum pay: In 2017-18, there were 10 players who logged minutes for the Gamecocks. So, if the players received $1,023,117 then the average player would be paid $102,312. In addition, if players are guaranteed 35% of the average, then minimum pay would be $35,809.
- Determine how much revenue will be allocated by a player's production of wins: If each player is paid at least $35,809, then the summation of minimum pay across all players is $358,091. This number is subtracted from $1,023,117 (i.e. the total allocation to players) to determine how much revenue will be allocated by wins produced. The result of this subtraction is $665,026.
- Address players who produce negative wins: A player's production of wins can be measured in basketball (again, this is detailed in Sports Economics and in other places for the NBA and WNBA). Some players, though, have an estimated negative impact. If we believe all players should be guaranteed a minimum wage, we need to address this issue. The approach taken is to sum the wins production of all players who produced a positive quantity of wins. For the Gamecocks in 2017-18, the summation of wins for all players who produced a positive quantity of wins is 28.92. The value of each of these wins is then $22,997 (i.e. $665,026 divided by 28.92).
- Determine how much revenue should be paid to each player: A'Ja Wilson -- the number one pick in the 2018 WNBA draft -- produced 7.71 wins for the Gamecocks in 2017-18. Wilson's estimated value would then be as follows:
Wilson's Economic Value: 7.71 * $22,997 + $35,809 = $213,049
In words… a player's value is simply the value of their wins production (or wins produced time the value of a win) plus the value of the minimum wage. If a player didn't produce wins, or their wins production was negative, then that player is simply worth the minimum wage.
Here are the results for all players who logged minutes for South Carolina in 2017-18.
Player | Wins Produced | Economic Value |
A'Ja Wilson | 7.71 | $213,049 |
Tyasha Harris | 6.61 | $187,880 |
Alexis Jennings | 4.82 | $146,765 |
Bianca Jackson | 3.13 | $107,871 |
Doniyah Cliney | 2.64 | $96,602 |
Mikiah Herbert Harrigan | 1.59 | $72,390 |
Lele Grissett | 1.21 | $63,733 |
Lindsey Spann | 0.97 | $58,150 |
Ladazhia Williams | 0.22 | $40,867 |
Victoria Patrick | -0.28 | $35,809 |
TOTALS | 28.63 | $1,023,117 |
South Carolina won 29 games in 2017-18. So, the estimated wins are quite close to the actual total. In addition, the summation of economic values exactly matches the 50% split of revenue determined in step one above.
The cost of attending South Carolina for out-of-state students is $47,587. This cost is the sticker price, which generally is not paid by many students. Nevertheless, if this value was taken as an estimate of what South Carolina is paying players, then we can see that eight of these ten players are -- by definition -- exploited.
So, does this analysis suggest that Ladazhia Williams and Victoria Williams are not exploited? Well, maybe not. There is an important impact of sports that are not captured in the revenue numbers submitted to the Department of Education. A universities' sports teams provide an immense amount of advertising for the school. This is especially true when we consider "the Flutie Effect"; or the impact athletic success has on a school's admissions. The analysis reported above ignore this effect, so what we are seeing above likely underestimates a player's value. In sum, it is likely all the players listed above are paid a wage that is less than their marginal revenue product.
Of course, is the measure listed above really a player's marginal revenue product? The approach taken above assumes that players should be paid 50% of league revenues. But that is based solely on current bargaining in the NBA. In the past, the NBA gave a higher percentage of revenue to its players. Furthermore, in European soccer in the past as much as 76% of its revenue went to its players.
So, what is the "right" revenue split? It doesn't appear this can be determined. What we can do is say what a player would be paid if
- revenues were split in a certain fashion
- players were guaranteed a minimum wage
- players were generally paid for wins
When we take that approach, it appears the basketball players for the women's basketball team at South Carolina in 2017-18 were generally underpaid. In other words, exploitation was the norm.
This is not an unusual story in college sports. Exploitation is not simply something that happens in men's basketball and football. We can find players that would likely be paid more than the cost of attendance in a number of sports; if the NCAA had to pay like a professional sports league. Again, this is what economic theory would predict. The advantage of sports is that we have the data to examine this prediction.
You must be a registered user to add a comment. If you've already registered, sign in. Otherwise, register and sign in.
-
Achieve
3 -
Chiang
3 -
Cowen-Tabarrok
4 -
EconEd
121 -
iClicker
1 -
Krugman-Wells
5 -
Online Learning
2 -
Poverty and Income Distribution
3 -
Price Controls
1 -
Public Goods and Common Resources
10 -
Stevenson-Wolfers
8 -
Taxes
1 -
Teach Econ
5 -
TeachEcon
5 -
Trade
2 -
Unemployment
4 -
Webinars
12