Major League Football Teams

¶ … league football teams with higher salaries win more frequently than other teams?

The wages of football players have risen noticeably over thirteen fold for the highest paid player from the season that ended in 1985 to that which ended in 2011. This improvement together with the mutually beneficial relationship between the sport and media has brought about an interesting field that has attracted academic scholars to do research on the impacts between different amounts of salaries and its influence on personal and team performance. (Fullard, 2012)

The matter of remunerations of professional players has always attracted public interest for a long time. There are many non-academic reading materials on the issue of salaries of professional players. Remunerations have shifted for the better from 1950's into the 21st century. Research has been done on different kinds of sports to find out the relationship between wages and performance. The most used model for these studies has been the tournament theory; however opposing outcomes have been noted in other studies on hockey. This particular paper examines wage allocation and its link to personal and team performance amongst National Football League (NFL) clubs. (Fullard, 2012)

Hypothesis

The Teams that give higher remunerations for their players will win more times than the other teams.

Approach of the study

Research has been done on personal and team performance and its link to the athletes' wages; the findings from these studies showed that there were several contradictions. The recurring link amongst the 4 studies is that the information used was gathered from seasons that the national football league did not employ a salary limit/cap. Thus there is a gap that must be filled by determining athlete salaries in terms of the salary limit. This paper will utilize data from the season NFL put in place a salary cap. (Fullard, 2012)

Literature review

In sports the American football is classified as based on progressive interdependence. A research done by Mondello and Maxcy (2009) determined if team performance was bolstered or increased when the team had an enticing pay structure (hierarchical) or just a salary-based pay structure (compressed).

The scholars studied the remuneration structures of the NFL clubs form the year 2000 to 2007. A sum total of two hundred and fifty four club year assessments were done and an analysis (regression) was made using this data. The researchers also employed a 2 factor fixed effects structure, which included random and fixed impacts. The conclusion was that salary distribution had an important positive influence on the team's field performance. On the contrary, Frick et al. (2003) determined that there was no direct relationship between wage inequality and a team's on-field performance in their observation of the National Football league. (Fullard, 2012)

Academic materials both old and recent have stressed the rise in salary inequality in the National Football league since the institution of the hard salary limit in the year 1994. The literature also elaborates on the link between salary distribution and the team performance in order to comprehend the dynamics of an optimal salary distribution structure (Winsberg, 2015)

Methodology

Utilizing statistics for all the 32 National Football League clubs in the 2010 through 2014 seasons available at the NFL Players' Association (NFLPA.org), USAToday.com, Over the Cap (overthecap.com), and ianwhetstone.com. I possess the entire salary cap information for all the clubs and all the seasons, each athlete that was paid a salary or received a bonus is included. For every individual athlete I have the statistics including the position on the field, wages, contract signing amount, and all bonuses, how these bonuses were paid back each season, which kinds of bonuses these were, the "limit value" of each athlete. The salaries are normalized using the 2014 dollars to mitigate the effects of inflation, additionally the amounts have been arranged in millions of dollars to design more comprehendible variables. Just from observation of the statistics, one can easily identify that there are huge disparities amongst clubs and the amounts they spend on each group of athletes. (Haugen, 2004)

To determine wage inequality and the disparity in the data Gini coefficients are utilized. This paper employs Gini coefficients to contrast clubs and the positional remuneration disparities against the NFL mean. A coefficient of zero means perfect competition while that of one means maximum inequality between the statistics. Therefore a low Gini score represents an equal pay structure while a high Gini score signifies a more superstar pay structure (Winsberg, 2015)

This research also utilized other statistics such as team rank, unit and team salary figures and comparisons. These statistics also comprise how much in terms of percentage a team uses against the NFL salary limit, how much the team pays its quarterback contrasting against other offense athletes as a percentage of the cap, and how much the defense players are remunerated as a percentage against the rest of the team. The statistics permit the comparison of any link amongst these standalone variables and the dependent ones being assessed including a team's sum of wins per season. These statistics explaining the structure of each club will likely offer more understanding on the pay structure of every football team and its link to on-field performance. Various franchise owners value each field position differently and therefore spend more money on certain ones than others (Winsberg, 2015)

I use the OLS regression structure to quantify the link between club performance and athlete salary. It is in the form of? = 0 + ? "1" + ? "2" + ? "3" + ? "4" + ? "5" +? The term? is team i's performance (such as sum of wins on-season, or offensive and defensive points accumulated per game) in a season (Winsberg, 2015)

When? is used to assess the number of club wins per season? is a figure that comprises positional remunerations values such as? and? These values have remuneration statistics for the offensive line (? ), quarter back (? ) and defensive line (? ) standings for club I in year t. The standalone vector? comprises the unit remuneration values for? and? both of which include the sum of the cap spent on defensive and offensive athletes respectively in year t for team I (Winsberg, 2015)

When? is used to assess offensive line performance? A vector variable comprises standings remuneration values? and? The standalone vector variable? entails the line remuneration term? (Winsberg, 2015)

When? is used to assess defensive line performance? A vector variable comprises standings remuneration value? The standalone vector variable? entails the line remuneration term? For all aspects of performance? comprises the sum of the amounts of all caps in year t for club i? comprises any general managers compensation for team I in the year t? includes ownership compensation for the club I in the year t. (Winsberg, 2015)