Pay Differential in Sports Based on Performance
The salary gap between genders has been a predominant issue in the sports arena. Women are continually paid less than their male counterparts, but men experience pay differentials between each other in some sports. In male dominated sports, such as hockey, baseball, and basketball, there is a variation in an individual’s salary that adversely affects the team’s performance and vice versa. In a capitalist society, everybody is paid what their work is worth. Sports such as hockey, basketball, and baseball are pay-for performance sports, in that the players are paid what their skills are worth to the team.
The less common a desired talent is, the more money an athlete will make because of it. There has been a continuous debate about how athletes should be paid. Is a defensemen in hockey who can score as valuable as a forward or more so? Is a catcher in baseball who can hit multiple homeruns in a season as valuable as a star pitcher? Many researchers use economic theories to analyze “Pay-For-Play” or the idea that athletes are paid better for a better performance. In order to examine athlete’s salaries certain definitions need to be established beforehand.
are not athletes are not players who are paid more than what they are worth, but rather are the top earners in their sport. Underpaid athletes are athletes who are paid less than the average player. It needs to be acknowledged that the success of a team is not just dependent on salary, but also coach and managerial input that are often omitted from research papers. The following examines the idea of pay-for-performance in hockey, baseball, and basketball. The correlation between a team’s performance and the individual salaries of the players are examined.
Whether or not being a free agent or having a signed contract and the influences these may have on an athlete’s effort exerted are also looked at. Hockey, baseball, and basketball are all pay-for-performance sports where the best performing players are paid top salaries. Idson & Kahane (2000) used the National Hockey League (NHL) to examine coworker productivity and its influence on salary. Because the statistics of a team’s performance and the salary of each player are publicly recorded and readily available, the information was considered accurate and ideal to use in the investigation.
Idson & Kahane (2000) asked the question as to whether an individual’s special attributes were rewarded/valued differently (in the form of a higher salary) in a variety of environments or in special cases. The investigators got the statistical data from Hockey News [February 8, 1991 and November 15, 1991] and the Hockey News Complete Hockey Book that compiled data from various years. The final data set of Idson and Kahane (2000) contained data on 930 players from the 1991-92 and 1992-93 seasons.
The points and plus/minus interaction were statistically significant at the 10% level indicating that an individual player performed at a higher level when playing with a team that contained better players. One of the main problems with studying athletes is that players can be traded midyear and essentially play on multiple teams in a given season. To counter this, the researchers placed an athlete on the team that reported the athlete’s total salary for the year. There is no one way to examine a player’s skill in hockey.
Idson & Kahane (2000) placed players as either a “forward” or “other”, such as defenseman or goalie. The strict dichotomy of this category might have had an adverse influence on their results because defenseman and goalies are not known for scoring points. Jones & Walsh (1988) made two categories for position in their data by labeling forwards and defensemen as forwards that would be examined by the points they scored. Goalies were the other category and were analyzed using goals allowed on average.
Because defensemen do not score as many points as forwards, the researchers pointed out that a defenseman scoring an equal number of goals as a forward would earn more money because of the added skill. In hockey, goalies make the big saves of the game, while forwards score the big goals of the game. Doing routine defensive maneuvers in a typical and habitual manner, defensemen are covered in a sheet of ambiguity. The top paid forward in hockey, Vincent Lacaviler, made $10 million, while the top paid defense man was, Zendo Chara, made only $7. 5 million for the 2009-10 season.
Both had relatively equal statistics for the season, but Lacaviler is a well known forward who makes the big plays people remember. Jones & Walsh (1988) incorporate the number of trophies and the number in the draft pick into their equation. Both trophies and draft pick numbers help defense men more than forwards. Adding these in was an attempt to even the playing field between forwards and defenseman. It was still shown that forwards with defensive skills, “enforcers” as they are called, make more money than defensemen with scoring abilities.
It is a possibility that enforcers are paid more because they excite fans with both their scoring and fighting skills. George Steinbrenner once said, “You measure the value of a [player] by how many fannies he puts in the seats. ” People who go to athletic events go to see the home team win, not just to observer one power player. Sommers, P. M. , & Quinton, N. (1982) used that approach to examine how having a superstar on the team, regardless of their input to winning the game, would affect revenue. It was discovered that although superstar have a slight influence on revenue, winning has a big influence on crowd attendance.
Because the players were organized into the categories of “free agents” and “not free agents”, it was also shown that free agents make more money on average than players without contracts. Harder (1992) hypothesized that pay-for performance contracts would lessen the effects of being underpaid on an individual. It was also hypothesized that underpaid individuals would not cooperate as much and would tend to have more self-centered behaviors. Using the equity theory, Harder (1992) compiled data for four seasons of players in the National Basketball Association (NBA) and Major League Baseball (MLB).
Statistical data was accumulated from Sporting News [May 8, 1988]. The number of points a player got in a season and the overall number of points in a career were positive indicators that basketball is a pay-for-performance sport. The results for baseball are the same; the better an athlete was in the season and overall his career, the better that athlete’s salary was. The first hypothesis was proven partially correct in that Harder (1992) found in baseball, the players who were paid less had lower average statistics, but this did not affect the number of runs from the underpaid athletes.
In basketball, an underpaid athlete was more like to shot the ball, but would not score as often as overpaid athletes. Overpaid athletes would contribute more to the team as a whole, rather than just scoring points, and were generally more team oriented than underpaid players. This was consistent with the second hypothesis put forth by Harder (1992). Some limitations put on Harder’s (1992) work was that when using sports salaries in equity theory, the salaries tend to be much higher. Although sports teams are a good area to research performance-based pay because of the easily accessible data, it also limits how generalizable a study can be.
A more recent way to interpret pay-for-performance was with the agency theory. Contracts in sports, such as basketball, are intended to make both the athlete and the team managers, content. Athletes who are at different cyclical stages of their contract perform in various ways. Just before signing or resigning a contract, athletes are more likely to put forth more effort to get a better contract (multi-million dollar, multi-year, or both). Just after or in the middle of a contract, players tend to play less strenuously (Stiroh, 2007).
Stiroh’s (2007) hypothesized that the decline in the effort a player puts forth is directly linked to the length of a contract and also the age of the athlete. The results showed that there is statistical evidence at the 1% level that before a contract was signed, an athlete put more effort into a performance. There was a negative regression in relation to age such that as age increases, the performance of an athlete steadily declines. The hypothesis that a player’s effort will decline after a contract is signed depends on the length of the contract.
The longer a contract is, the less likely that a player is going to keep playing with the same effort. Stiroh (2007) concludes that the status of an individual player’s contract is a good predictor of the athlete’s overall performance. An examination between the win/loss percentage of a team and the team’s payroll using multiple sports (baseball, hockey, football, and basketball) was conducted by Quirk and Fort (1999). Over a six year period (1990-96), there was significant evidence in both the NHL and the NBA to suggest that a difference in payroll for athletes on a team will affects the win/loss percentage.
There was not conclusive evidence for the MLB and NFL. One needs to be wary of the results though; the evidence may be misleading because of unforeseen events like injuries and players holding out on signing contracts. These four sports were examined again in the same context by Forrest & Simmons (2000) using the results for the 1999-2000 season and came to the same conclusion. In the three main sports that were focus on (hockey, baseball, and basketball), there is repeated significant evidence to support the idea that the performance of an athlete and/or a team is influenced by the payroll of the individuals on the team.
The only sport that shows a slight discrimination in the pay of an athlete is defensemen in the NHL. More research and analysis is needed to see if a stronger correlation between the win/loss percentage and the team wages because current research suggests a weak predictive power. All of the current research is focused on regular season. Play-off performances are an area where more research needs to be done to see if the added pressure changes the team dynamics thus influencing an individual player’s salary.
