In July I blogged about MLS income inequality and one reader asked me about the NFL. My response, was basically - cool idea; I don't know; have not done it. Now I have. I am using the Gini coefficient (step-by-step guide to make this calculation) which is a measure of income inequality. The Gini coefficient is bound between zero (complete equality) and one (complete inequality). For comparison purposes, the Gini coefficient for the US in 2010 is 0.411 (or 41.1 for the Gini Index, which is the Gini coefficient multiplied by 100).
Specifically, what I have done is taken every active player pay (not the amount attributed to the salary cap) listed on the website for the 2014 season and measured the amount of income inequality. I have not included players on injured reserve or players that were given a contract but then dropped from the team. Here is the link for Arizona in 2014, follow the dropdown menu for the other teams. Once all the players have been included in the dataset, I have a total of 1688 NFL players in 2014. Total payroll among those players was $3.331 billion. For all the active players, the Gini coefficient was 0.5942, which is quite a bit more unequal than the US in 2010.
UPDATE: (09/16/2015: US Gini coefficient for 2014 is 0.480.)
Friday, September 11, 2015
Thursday, September 10, 2015
Friday, September 4, 2015
Air Force Football Program in 2014
No, I am not going to review all the teams in NCAA FBS from last season - although that might be put on my bucket list someday. Rather I am reviewing Air Force since @USAFAFalcons is currently a Twitter follower; yeah its that easy. So here are the Falcons for the 2014 season using the Complex Invasion College Football Production Model.
The Air Force Falcons finished the 2014 regular season at 9-3 (and the winner of the Commander In Chief trophy). Air Force's best game was a 28-14 win over #13 ranked Boise State in Colorado Springs and their worst loss was to #109 ranked Wyoming in Cheyenne. The Falcons played against an "average" strength of schedule (SOS) as compared to the rest of the "league". An average SOS occurs where a team in within one standard deviation from the mean SOS for the league. Given the mean SOS was 67.57 and the standard deviation was 10.74 and Air Force played against a SOS = 77.00 for the entire season, they were just within (on the easier side) the average range for SOS. Their regular season performance allowed Air Force to be bowl eligible and play in the Famous Idaho Potato Bowl on December 20th of last year where Air Force defeated #36 ranked Western Michigan 38-24 to finish overall at 10-3. This resulted in Air Force to finish as the #60 most productive team in all of the FBS. On the offensive side, the Falcons were the #58 ranked team and on the defensive side they were the #57 ranked team.
The Air Force Falcons finished the 2014 regular season at 9-3 (and the winner of the Commander In Chief trophy). Air Force's best game was a 28-14 win over #13 ranked Boise State in Colorado Springs and their worst loss was to #109 ranked Wyoming in Cheyenne. The Falcons played against an "average" strength of schedule (SOS) as compared to the rest of the "league". An average SOS occurs where a team in within one standard deviation from the mean SOS for the league. Given the mean SOS was 67.57 and the standard deviation was 10.74 and Air Force played against a SOS = 77.00 for the entire season, they were just within (on the easier side) the average range for SOS. Their regular season performance allowed Air Force to be bowl eligible and play in the Famous Idaho Potato Bowl on December 20th of last year where Air Force defeated #36 ranked Western Michigan 38-24 to finish overall at 10-3. This resulted in Air Force to finish as the #60 most productive team in all of the FBS. On the offensive side, the Falcons were the #58 ranked team and on the defensive side they were the #57 ranked team.
Thursday, September 3, 2015
NCAA Football and Income Inequality
Recently, I have been researching NCAA bowl eligible football revenues, so given that tonight is the start of the college football season for bowl eligible teams I thought that I would look at college football income inequality. Specifically, I am using data from the Equity in Athletics database from 2007 to 2013 college football seasons. (The 2014 season is not currently available).
Here I am going to report the team with the smallest amount of football revenue and the amount, the team with the largest amount of football revenue and the amount and the Gini coefficient for that season. Please note that I have not adjusted for inflation in the revenue numbers presented below. For comparison purposes, the Gini coefficient for the US in 2010 is 0.411 (or 41.1 for the Gini Index, which is the Gini coefficient multiplied by 100). As you can see in the table below, NCAA football is slightly more unequal in terms of revenues than the US was in 2010.
We also notice that the University of Texas has the highest amount of revenue during this entire time period and that CUSA, Mid American or Sun Belt conference teams have had the lowest total football revenues during this time period.
Here I am going to report the team with the smallest amount of football revenue and the amount, the team with the largest amount of football revenue and the amount and the Gini coefficient for that season. Please note that I have not adjusted for inflation in the revenue numbers presented below. For comparison purposes, the Gini coefficient for the US in 2010 is 0.411 (or 41.1 for the Gini Index, which is the Gini coefficient multiplied by 100). As you can see in the table below, NCAA football is slightly more unequal in terms of revenues than the US was in 2010.
| Season | Team | Min. Revenue | Team | Max. Revenue | Gini | |||||
| 2007 | Buffalo | $1,882,475 | Texas | $72,952,397 | 0.4564 | |||||
| 2008 | Akron | $1,577,189 | Texas | $87,583,986 | 0.4516 | |||||
| 2009 | Florida Atlantic | $2,280,834 | Texas | $93,942,815 | 0.4515 | |||||
| 2010 | Louisiana-Monroe | $2,953,497 | Texas | $95,749,684 | 0.4465 | |||||
| 2011 | Louisiana-Monroe | $3,588,964 | Texas | $103,813,684 | 0.4381 | |||||
| 2012 | Louisiana-Monroe | $3,277,727 | Texas | $109,400,688 | 0.4418 | |||||
| 2013 | Central Mich. | $3,899,929 | Texas | $112,508,162 | 0.4448 |
We also notice that the University of Texas has the highest amount of revenue during this entire time period and that CUSA, Mid American or Sun Belt conference teams have had the lowest total football revenues during this time period.
Friday, August 28, 2015
University of Illinois Dismisses Head Football Coach Tim Beckman
FootballScoop reports that the University of Illinois has dismissed head football coach Tim Beckman with cause before the 2015 NCAA FBS season. Bill Cubit will be the interim head coach for the season and here is my analysis of Western Michigan under Cubit's last five seasons as head football coach.
So let's take a look at Illinois using the Complex Invasion College Football Production Model before and during Beckman's tenure. I will be starting with the 2008 season and move forward through 2014.
Below is a chart of the Illinois Illini offense, defense and total production rankings since 2008 along with the rank of the worst team in the Football Bowl Subdivision during the time period. More information from the model is presented below.
2008
Unfortunately, I do not have all the data to run the model before the 2008 season, so I am unable to show how Illinois performed in the previous Rose Bowl season. As such, I can only evaluate based on the data that I have and the model that I am using is the same since the 2008 season. That said, Illinois finished the 2008 season at 5-7 and bowl ineligible and played against an "average" strength of schedule (SOS) as compared to the "league" average, meaning that their actual SOS was within one standard deviation of the "league" average SOS. The Illini's best game was a victory over #9 ranked Iowa and their worst loss was to #75 ranked Minnesota. Overall, the Illini's had the #49 most productive college football team with the #45 ranked offense and the #54 ranked defense.
2009
Statistically this was Ron Zook's worst team during this time period (but better than Beckman's first season as I detail below). Illinois finished the regular season at 3-9 and played against an "average" strength of schedule (SOS) as compared to the "league" average. The Illini's best game was a victory over #79 ranked Michigan and their worst loss was to #89 ranked Indiana. Overall, the Illini's had the #95 ranked team in terms of total production with the #84 ranked offense and the #92 ranked defense.
2010
Illinois significantly turned their production around in this season although the wins and losses do not reflect the relative productivity of the team in this season. Illinois finished at 7-6 while playing against a "average" strength of schedule (SOS) as compared to the "league" average. The Illini's best game was a victory over #8 ranked Northern Illinois and their worst loss was to #89 ranked Minnesota. Illinois had the #18 ranked team in overall productivity with the #35 ranked offense and the #11 ranked defense.
2011
In Zook's last season as head football coach the Illini finished at 7-6. Illinois played against an "average" strength of schedule (SOS) as compared to the "league" average. The Illini's best game was a victory over #25 ranked Arkansas State and their worst loss was to #101 ranked Minnesota. The Illini's had the #61 ranked team (just on the other side of below average) with the #91 ranked offense and the #31 ranked defense.
2012
Tim Beckman took over for Ron Zook this season and while Illinois played against an "average" strength of schedule (SOS) as compared to the "league" average, meaning that their actual SOS was within one standard deviation of the "league" average SOS. Illinois finished the regular season at 2-10 and their worst winning percentage during this time period. The Illini's best game was a victory over #65 ranked Western Michigan and their worst loss was to #103 ranked Indiana. Overall, the Illini's had the #115 ranked team with the #118 ranked offense and the #91 ranked defense. Clearly, a year to forget.
2013
In Beckman's second season as head football coach the Illini finished the regular season at 4-8 and were bowl ineligible. Illinois played against a "tougher" strength of schedule (SOS) as compared to the "league" average, meaning that their actual SOS was between one and two standard deviations lower than the "league" average SOS. The Illini's best game was a victory over #25 ranked Cincinnati and their worst loss was to #77 ranked Indiana. Overall, the Illini had the #97 ranked team with the #63 ranked offense and the #117 ranked defense.
2014
In what turns out to be Beckman's last season as head football coach the Illini finished the regular season at 6-6 and lost to Louisana Tech in the bowl game. Illinois again played against a "tougher" strength of schedule (SOS) as compared to the "league" average. This season the Illini's best game was a victory over #45 ranked Minnesota and their worst loss was to #110 ranked Purdue. Overall, the Illini had the #93 ranked team with the #76 ranked offense and the #111 ranked defense.
Thus Illinois has performed under Beckman worse on average than Zook's worst team during this time period.
So let's take a look at Illinois using the Complex Invasion College Football Production Model before and during Beckman's tenure. I will be starting with the 2008 season and move forward through 2014.
Below is a chart of the Illinois Illini offense, defense and total production rankings since 2008 along with the rank of the worst team in the Football Bowl Subdivision during the time period. More information from the model is presented below.
2008
Unfortunately, I do not have all the data to run the model before the 2008 season, so I am unable to show how Illinois performed in the previous Rose Bowl season. As such, I can only evaluate based on the data that I have and the model that I am using is the same since the 2008 season. That said, Illinois finished the 2008 season at 5-7 and bowl ineligible and played against an "average" strength of schedule (SOS) as compared to the "league" average, meaning that their actual SOS was within one standard deviation of the "league" average SOS. The Illini's best game was a victory over #9 ranked Iowa and their worst loss was to #75 ranked Minnesota. Overall, the Illini's had the #49 most productive college football team with the #45 ranked offense and the #54 ranked defense.
2009
Statistically this was Ron Zook's worst team during this time period (but better than Beckman's first season as I detail below). Illinois finished the regular season at 3-9 and played against an "average" strength of schedule (SOS) as compared to the "league" average. The Illini's best game was a victory over #79 ranked Michigan and their worst loss was to #89 ranked Indiana. Overall, the Illini's had the #95 ranked team in terms of total production with the #84 ranked offense and the #92 ranked defense.
2010
Illinois significantly turned their production around in this season although the wins and losses do not reflect the relative productivity of the team in this season. Illinois finished at 7-6 while playing against a "average" strength of schedule (SOS) as compared to the "league" average. The Illini's best game was a victory over #8 ranked Northern Illinois and their worst loss was to #89 ranked Minnesota. Illinois had the #18 ranked team in overall productivity with the #35 ranked offense and the #11 ranked defense.
2011
In Zook's last season as head football coach the Illini finished at 7-6. Illinois played against an "average" strength of schedule (SOS) as compared to the "league" average. The Illini's best game was a victory over #25 ranked Arkansas State and their worst loss was to #101 ranked Minnesota. The Illini's had the #61 ranked team (just on the other side of below average) with the #91 ranked offense and the #31 ranked defense.
2012
Tim Beckman took over for Ron Zook this season and while Illinois played against an "average" strength of schedule (SOS) as compared to the "league" average, meaning that their actual SOS was within one standard deviation of the "league" average SOS. Illinois finished the regular season at 2-10 and their worst winning percentage during this time period. The Illini's best game was a victory over #65 ranked Western Michigan and their worst loss was to #103 ranked Indiana. Overall, the Illini's had the #115 ranked team with the #118 ranked offense and the #91 ranked defense. Clearly, a year to forget.
2013
In Beckman's second season as head football coach the Illini finished the regular season at 4-8 and were bowl ineligible. Illinois played against a "tougher" strength of schedule (SOS) as compared to the "league" average, meaning that their actual SOS was between one and two standard deviations lower than the "league" average SOS. The Illini's best game was a victory over #25 ranked Cincinnati and their worst loss was to #77 ranked Indiana. Overall, the Illini had the #97 ranked team with the #63 ranked offense and the #117 ranked defense.
2014
In what turns out to be Beckman's last season as head football coach the Illini finished the regular season at 6-6 and lost to Louisana Tech in the bowl game. Illinois again played against a "tougher" strength of schedule (SOS) as compared to the "league" average. This season the Illini's best game was a victory over #45 ranked Minnesota and their worst loss was to #110 ranked Purdue. Overall, the Illini had the #93 ranked team with the #76 ranked offense and the #111 ranked defense.
Thus Illinois has performed under Beckman worse on average than Zook's worst team during this time period.
Friday, July 31, 2015
Wednesday, July 29, 2015
2015 MLS Position Income Inequality
Today, I want to finish measuring income inequality in MLS by looking at how salaries are distributed by player position. Taking the data from MLSPU, I have found for each player (except one) their position and then evaluated the level of income inequality by each position. For players that are listed at multiple positions I have included them for each position.
Last year the position with the most equal salary were goal keepers and the most unequal were forwards. This season goal keepers are still the most equal, but now midfielders are the most unequal. Here is the Gini coefficients for this season using MLSPU's data.
As you can see midfielder are twice as unequal as goal keepers. Defenders are close to goal keepers and forwards are close to midfielders for the league as a whole.
Prior posts on 2015 MLS Income Inequality:
MLS Team Income Inequality
MLS Overall Income Inequality
Last year the position with the most equal salary were goal keepers and the most unequal were forwards. This season goal keepers are still the most equal, but now midfielders are the most unequal. Here is the Gini coefficients for this season using MLSPU's data.
| Pos | Base Salary | Guaranteed Comp. | |
| D | 0.4137 | 0.4183 | |
| F | 0.6844 | 0.6772 | |
| GK | 0.3457 | 0.3518 | |
| M | 0.7108 | 0.7109 |
As you can see midfielder are twice as unequal as goal keepers. Defenders are close to goal keepers and forwards are close to midfielders for the league as a whole.
Prior posts on 2015 MLS Income Inequality:
MLS Team Income Inequality
MLS Overall Income Inequality
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