2017 NCAA FBS Top 25 Ranking for Week 9

Below is the Top 25 ranked teams using the Complex Invasion College Football Production Model from the data provided at www.cfbstats.com.  According to the Complex Invasion College Football production model, the University of Alabama is now the most productive team in all of the Football Bowl Subdivision as of the end of last week. Links to the previous weeks rankings for this season are at the bottom of the page.

Rank	Team
1	Alabama
2	Ohio State
3	Washington
4	Penn State
5	UCF
6	Georgia
7	Notre Dame
8	Wisconsin
9	Oklahoma State
10	Virginia Tech
11	TCU
12	Clemson
13	Mississippi State
14	South Florida
15	Auburn
16	Oklahoma
17	Miami (Florida)
18	Fresno State
19	Louisville
20	North Carolina State
21	Ohio
22	UTSA
23	Florida Atlantic
24	Washington State
25	LSU

Previous 2017 Top 25 Rankings
2017 NCAA FBS Top 25 Rankings for Week #8
2017 NCAA FBS Top 25 Rankings for Week #7
2017 NCAA FBS Top 25 Rankings for Week #6
2017 NCAA FBS Top 25 Rankings for Week #5
2017 NCAA FBS Top 25 Rankings for Week #4
2017 NCAA FBS Top 25 Rankings for Week #3
2017 NCAA FBS Top 25 Rankings for Week #2

Florida Parts Ways with Jim McElwain

Earlier today the University of Florida and head football coach Jim McElwain parted ways.  Former head coach McElwain has been with the Gator's for only two and a half seasons, so there is not a lot to look at during his tenure, but here is the program using the Complex Invasion College Football Production Model.

Below is a chart of offense, defense and total production of the University of Florida Gators football program during McElwain's tenure as head football coach, along with who would be the lowest ranked team during this time period (in purple) and the average team (sky blue).   As you may notice, Florida's offense has dropped dramatically under his brief tenure. All rankings in this blog come from my Complex Invasion College Football Production Model.  More details about the program under McElwain are after the chart below, including a link to his employment contract are below.

Jim McElwain [2015 - 2017]

2015
The Gators were 10-2 during the regular season under McElwain's first year at the helm of the football program (bowl eligible), and lost the SEC conference title game to #7 ranked Alabama (15-29), and were defeated by #24 ranked Michigan in their post-season bowl game by a score of (7-41).  Florida played against a "tougher" strength of schedule (SOS) as compared to the "league" average SOS, meaning that their SOS was between one and two standard deviations below the "league" average SOS.  The Gators best game again was their victory over #6 ranked Mississippi (38-10) and their worst loss was to #16 ranked in-state rival Florida State (2-27).  Florida had the #48 ranked team in total production with the #80 ranked offense and the #15 ranked defense from the Complex Invasion College Football Production Model.

2016
Florida finished the regular season at 8-3 under McElwain's second year at the helm of the football program (bowl eligible), and again lost the SEC title game to #1 ranked Alabama (54-16) but defeated #41 Iowa (30-3) in their post-season bowl game to finish 9-4 overall.  The Gators played against an "average" strength of schedule (SOS) as compared to the "league" average SOS, meaning that their SOS was plus or minus one standard deviation of the "league" average SOS.  The Gators best game again was their victory over #7 ranked LSU (16-10) and their worst loss was to #85 ranked Arkansas (31-10).  Florida had the #34 ranked team in total production with the #102 ranked offense and the #5 ranked defense from the Complex Invasion College Football Production Model.

2017*
At the time of McElwain's departure, the Gators were 3-4 overall, playing against an "average" strength of schedule (SOS) as compared to the "league" average SOS.  The Gators best win was against #79 currently ranked Kentucky by a score of (28-27) and their worst loss was to #60 currently ranked Texas A&M by a score of (17-19).  In other words, all of Florida's victories were over below average teams and all their losses were to above average teams.  Florida had the #86 ranked team in total production, with the #122 ranked offense and the #29 ranked defense from the Complex Invasion College Football Production Model.

2017 NCAA FBS Head Coach Changes
Minnesota and Tracy Claeys
California and Sonny Dykes
Oklahoma and Bob Stoops
Mississippi (Ole Miss) and Hugh Freeze
UTEP and Sean Kugler
Oregon State and Gary Andersen
Georgia Southern and Tyson Summers

MLS Competitive Balance

Now that the 2017 MLS regular season is in the books, I decided to look at MLS competitive balance.  I did this a few years ago, but thought that I would update it.

Using the Noll-Scully measure of competitive balance under the trinomial distribution (since ties are a part of the MLS) I find that competitive balance is higher for the 2017 regular season than the average over the last 18 seasons.  The average Noll-Scully has been fairly stable over the last five years.  The Noll-Scully for the MLS 2017 regular season is 1.383 which is still more competitive than the other "major" US sports leagues.  Here is the Noll Scully since the 2000 regular season.




Want to try to calculate it yourself?  Here is my Noll-Scully competitive balance measure step-by-step guide.  Note:  I used the trinomial distribution.

Georgia Southern Fires Tyson Summers as Head Football Coach

After losing to previously winless Massachusetts, Georgia Southern fired head coach Tyson Summers this past weekend.

Below is a chart of offense, defense and total production of the Georgia Southern Eagles football program during Summers' tenure as head football coach, along with who would be the lowest ranked team during this time period (in purple) and the average team (sky blue).   As you may notice, Georgia Southern has dropped dramatically under his brief tenure. All rankings in this blog come from my Complex Invasion College Football Production Model.  More details about the program under Summers are after the chart below, including a link to his employment contract are below.

Tyson Summers [2016-2017*]

2016
The Eagles were 5-7 under Summers' first year at the helm of the football program (bowl ineligible),  playing against an "average" strength of schedule (SOS) as compared to the "league" average SOS, meaning that their SOS was plus or minus one standard deviation of the "league" average SOS.  The Eagles best game again was their victory over #31 ranked Troy (28-24) and their worst loss was to #89 ranked in-state rival Georgia State (24-30).  Georgia Southern had the #84 ranked team in total production with the #97 ranked offense and the #51 ranked defense from the Complex Invasion College Football Production Model.

2017*
At the time of Summers' firing, the Eagles were 0-6 overall, playing against an "average" strength of schedule (SOS) as compared to the "league" average SOS.  The Eagles worst loss was to FCS New Hampshire by a score of (12-22).  Georgia Southern had the #126 ranked team in total production, which is a bottom 5 team in the FBS, with the #130 ranked offense (that would be the worst in all of the FBS) and the #104 ranked defense from the Complex Invasion College Football Production Model.

2017 NCAA FBS Head Coach Changes
Minnesota and Tracy Claeys
California and Sonny Dykes
Oklahoma and Bob Stoops
Mississippi (Ole Miss) and Hugh Freeze
UTEP and Sean Kugler
Oregon State and Gary Andersen

2017 NCAA FBS Top 25 Ranking for Week 8

Below is the Top 25 ranked teams using the Complex Invasion College Football Production Model from the data provided at www.cfbstats.com.  According to the Complex Invasion College Football production model, Ohio State University is now the most productive team in all of the Football Bowl Subdivision as of the end of last week. Links to the previous weeks rankings for this season are at the bottom of the page.

Rank	Team
1	Ohio State
2	Washington
3	Penn State
4	Alabama
5	TCU
6	Georgia
7	Notre Dame
8	Wisconsin
9	Auburn
10	Mississippi State
11	Virginia Tech
12	Miami (Florida)
13	Clemson
14	Fresno State
15	Oklahoma
16	Washington State
17	Louisville
18	Northern Illinois
19	Southern Mississippi
20	Iowa State
21	Michigan State
22	West Virginia
23	UCF
24	SMU
25	Minnesota

Previous 2017 Top 25 Rankings
2017 NCAA FBS Top 25 Rankings for Week #7
2017 NCAA FBS Top 25 Rankings for Week #6
2017 NCAA FBS Top 25 Rankings for Week #5
2017 NCAA FBS Top 25 Rankings for Week #4
2017 NCAA FBS Top 25 Rankings for Week #3
2017 NCAA FBS Top 25 Rankings for Week #2

2017 NCAA FBS Top 25 Ranking for Week 7

Below is the Top 25 ranked teams using the Complex Invasion College Football Production Model from the data provided at www.cfbstats.com.  According to the Complex Invasion College Football production model, Alabama is back on top as the most productive team in all of the Football Bowl Subdivision as of the end of last week. Links to the previous weeks rankings for this season are at the bottom of the page.

Rank	Team
1	Alabama
2	Ohio State
3	Washington
4	Penn State
5	South Florida
6	Wisconsin
7	Oklahoma State
8	UCF
9	North Carolina State
10	Oklahoma
11	TCU
12	Miami (Florida)
13	Auburn
14	Georgia
15	Texas Tech
16	Michigan
17	Southern Mississippi
18	Stanford
19	USC
20	Minnesota
21	Texas A&M
22	Clemson
23	Arizona
24	Iowa State
25	Virginia

Previous 2017 Top 25 Rankings
2017 NCAA FBS Top 25 Rankings for Week #6
2017 NCAA FBS Top 25 Rankings for Week #5
2017 NCAA FBS Top 25 Rankings for Week #4
2017 NCAA FBS Top 25 Rankings for Week #3
2017 NCAA FBS Top 25 Rankings for Week #2

2017 MLB Pay and Performance

Last week I blogged about competitive balance in MLB.  Now I want to turn to the relationship between MLB payroll and MLB performance.  I have looked at this using USA Today MLB team payroll data in the past (2015 and 2016), but now I want to use data from spotrac.com for MLB.  I find that the data from spotrac is excellent and probably more accurate than the USA Today MLB team payroll data.  The data from spotrac starts in 2011, so I have a smaller time frame to work with, but I thought it would be good to see if the relationship between payroll and performance differs using a different set of MLB team payroll data.  If you are interested in doing this type of analysis, here is a step-by-step guide to payroll and performance analysis.

So, after collecting and organizing the 2011 through 2017 MLB team payroll and team performance data, I ran the regression on team performance using relative payroll as the independent variable.  I use a software package called Stata for the statistical analysis and found that relative payroll is positive and statistically significant with respect to MLB team performance, just like I have found in each previous time I have done this type of statistical analysis using data from USA Today.  The coefficient on relative payroll is 0.06868, which means that a one unit increase in relative payroll will lead to a 0.06868 increase in team winning percent.  In terms of wins, the regression results show that a one unit increase in relative payroll would result in just over 11 additional wins.  In order to get those wins, a MLB team would have to increase team payroll by one unit of relative payroll, which is the same thing as average payroll.  For the 2017 MLB season, that is an increase of $152,327,084 using data from spotrac.  So those approximately 11 wins would cost about $13,690,875 per win.  That is a rather costly amount to pay for each win.

Finally, the regression results show that while the relationship between MLB team performance and relative payroll is positive and statistically significant, the amount that relative payroll "explains" of MLB team performance is not that much.  In this case, using data from spotrac, the explanatory power of the regression is rather weak, with an adjusted r-squared equal to 0.127.  Another way of saying that is that relative payroll only "explains" 12.7% of MLB team performance.  I will let you decide if you think that is good enough.  But will state that there are other variables that explain a greater amount of MLB team performance than relative payroll.

Gary Andersen Departs as Head Football Coach at Oregon State

Gary Andersen has departed as head football coach at Oregon State University yesterday.  Andersen was under contract until 2021, but decided it was best for the program to leave now, with the Beavers currently 1-5, their only victory over FCS Portland State in their second game of the season.  So, here is a look at Oregon State since Andersen's arrival.

Below is a chart of offense, defense and total production of the Oregon State Beavers football program during Andersen's tenure as head football coach, along with who would be the lowest ranked team during this time period (in purple) and the average team (sky blue).   Oregon State has been below average each season under his tenure. All rankings in this blog come from my Complex Invasion College Football Production Model.  More details about the program under Andersen are after the chart below as well as a link to his contract.

Gary Andersen [2015 - 2017*]

2015
In head coach Andersen's first year at the helm of the Beavers football team, Oregon State  finished the regular season overall at 2-10 (bowl ineligible).  Oregon State played against a "tougher" strength of schedule (SOS) as compared to the "league" average SOS, meaning that Oregon State's SOS was between one and two standard deviations lower than the "league" average SOS.  The Beavers best game again was their victory over #60 ranked San Jose State (35-21), and their worst loss was to #87 ranked Colorado (13-17).  Oregon State had the #120 ranked team in total production with the #113 ranked offense and the #113 ranked defense from the Complex Invasion College Football Production Model.

2016
At the end of the regular season the Beavers were again bowl ineligible with a 4-8 win/loss record, while playing against an "average" strength of schedule (SOS) as compared to the "league" average SOS, meaning that UTEP had an SOS plus or minus one standard deviation of the "league" average SOS.  The Miners best win was over #98 ranked California (47-44) and their worst loss was to #70 ranked UCLA by a score of (24-38).  Oregon State had the #95 ranked team in total production with the #90 ranked offense and the #74 ranked defense from the Complex Invasion College Football Production Model.

2017*
Near the halfway mark of the regular season the Beavers are 1-5, while playing against a "much tougher" strength of schedule (SOS) as compared to the "league" average SOS, meaning that Oregon State's SOS is lower than two standard deviations of the "league" SOS.  The Beavers only victory to date was over FCS Portland State and their worst loss was to currently ranked #34 Minnesota by a score of (14-48).  At the time of Andersen's departure, Oregon State had the #123 ranked team in total production (that is the worst team), with the #116 ranked offense and the #118 ranked defense from the Complex Invasion College Football Production Model. 

2017 NCAA FBS Head Coach Changes
Minnesota and Tracy Claeys
California and Sonny Dykes
Oklahoma and Bob Stoops
Mississippi (Ole Miss) and Hugh Freeze
UTEP and Sean Kugler

2017 NCAA FBS Top 25 Ranking for Week 6

Below is the Top 25 ranked teams using the Complex Invasion College Football Production Model from the data provided at www.cfbstats.com.  According to the Complex Invasion College Football production model, Washington is now the most productive team in all of the Football Bowl Subdivision as of the end of last week. Links to the previous weeks rankings for this season are at the bottom of the page.

Rank	Team
1	Washington
2	Alabama
3	Ohio State
4	Penn State
5	Washington State
6	Georgia
7	Clemson
8	Notre Dame
9	Wisconsin
10	Oklahoma
11	UCF
12	Virginia Tech
13	Auburn
14	Louisville
15	Wake Forest
16	Miami (Florida)
17	San Diego State
18	Oregon
19	TCU
20	Texas Tech
21	West Virginia
22	Michigan State
23	USC
24	Colorado State
25	Kansas State

Previous 2017 Top 25 Rankings
2017 NCAA FBS Top 25 Rankings for Week #5
2017 NCAA FBS Top 25 Rankings for Week #4
2017 NCAA FBS Top 25 Rankings for Week #3
2017 NCAA FBS Top 25 Rankings for Week #2

2017 MLB Competitive Balance

With the 2017 MLB regular season finished, let's take a look at competitive balance using the Noll-Scully measure of competitive balance.  The Noll-Scully uses the actual standard deviation of a league's winning percentage and compares it to a league if wins and losses were randomly determined in a statistical sense.  A Noll-Scully of 1.000 indicates wins and losses were randomly determined and thus the league is perfectly balanced in a competitive sense.  A Noll-Scully higher indicates that the league is less than perfectly balanced.  As the value increases the league is less competitive.

For the 2017 MLB regular season, we see that the American League had a competitive balance of 1.658 and the National League had a competitive balance of 1.897, meaning that the National League was less competitive than the American League.  Overall, MLB had a Noll-Scully of 1.783, which is slightly more competitive than the league average Noll-Sculy since 1982.

If you are interested in doing this on your own, here is a step-by-step guide to calculate the Noll-Scully measure of competitive balance using Microsoft Excel.  

2017 MLB Regular Season Attendance

Today I will look at regular season home attendance in MLB.  To do so I grabbed the data from ESPN. First thing to note is that overall regular season attendance has decreased by 488,645 fans from the 2016 regular season and the 2016 regular season dropped by about 600,000 fans from the 2015 season.  Yes, that is a million fewer people attended a MLB game in 2017 as compared to 2015.

The three largest attendance declines were Kansas City (-337,342), Pittsburgh (-329,574) and the New York Mets (-328,980), and the three largest attendance increases were Atlanta (484,338), Cleveland (456,471) and Colorado (351,126).

While total attendance and average attendance are lower this regular season as compared to the 2016 regular season, is it statistically different from the previous regular season?  We need a statistical tool to determine if attendance is different between the two regular seasons with some degree of confidence.  The statistical tool I use is a t-test as the means to perform the analysis.

A t-test looks at the differences between attendance for two regular seasons average home attendance and allows us to judge the difference between their means relative to the variability of their regular season average home attendance.  You can quickly perform a t-test in Microsoft Excel =t.test(...).  I choose to use a two tailed test, since regular season average home attendance can increase and decrease as compared to the previous regular season.

I am going to look at regular season average home attendance for the 2016 and 2017 MLB season, just like I did for the 2016 MLB regular season.  The reason I am looking at average attendance is that not all teams play the same number of home games from one season to the next and using the average is a much more accurate for comparing one season to another.

So after running the t-test between the 2016 and 2017 regular season home attendance using a paired t-test, a t-tests where the sample variance is assumed to be equal, and a t-test where the sample variance is not assumed to be unequal; in each case, the result of the t-test is that it fails to accept (rejects) that regular season average home attendance is different between the two seasons.

That might not be much consolation to the Royals, Pirates and Mets, but the decline in attendance is not significant as compared to the prior regular season.

2017 NCAA FBS Top 25 Ranking for Week 5

Below is the Top 25 ranked teams using the Complex Invasion College Football Production Model from the data provided at www.cfbstats.com.  According to the Complex Invasion College Football production model, Alabama is now the most productive team in all of the Football Bowl Subdivision as of the end of last week. Links to the previous weeks rankings for this season are at the bottom of the page.

Rank	Team
1	Alabama
2	Washington
3	Penn State
4	Ohio State
5	Clemson
6	South Florida
7	Washington State
8	Oregon
9	Oklahoma
10	Louisville
11	Georgia
12	Wisconsin
13	Virginia Tech
14	Oklahoma State
15	Auburn
16	Wake Forest
17	TCU
18	Notre Dame
19	North Carolina State
20	Miami (Florida)
21	Kansas State
22	UCF
23	SMU
24	Texas A&M
25	Utah

Previous 2017 Top 25 Rankings
2017 NCAA FBS Top 25 Rankings for Week #4
2017 NCAA FBS Top 25 Rankings for Week #3
2017 NCAA FBS Top 25 Rankings for Week #2

Sean Kugler Resigns at UTEP

Earlier today University of Texas at El-Paso (UTEP) head football coach Sean Kugler resigned.  The Miners are currently winless this season, with an 0-5 mark.  With his resignation, let's take a look at the UTEP Miners under Kugler's tenure as head football coach.

Below is a chart of offense, defense and total production of the UTEP Miners football program during Kugler's tenure as head football coach, along with who would be the lowest ranked team during this time period (in purple) and the average team (sky blue).   UTEP has been below average each season under his tenure. All rankings in this blog come from my Complex Invasion College Football Production Model.  More details about the program under Kugler are after the chart below as well as a link to his contract.

Sean Kugler [2013-2017*] (2015 amended contract)

2013
At the end of the Kugler's first season, the Miners finished 2-10.  UTEP played against an "average" strength of schedule (SOS) as compared to the "league" average SOS, meaning that their SOS was plus or minus one standard deviation from the "leagues" SOS.  The Miners best victory was against #117 New Mexico State (42-21) and their worst loss was to #106 ranked Tulsa by a score of (20-34).  UTEP had the #116 ranked team in total production with the #107 ranked offense and the #118 ranked defense from the Complex Invasion College Football Production Model.

2014
The Miners again finished the regular season at 7-5 and were bowl eligible, but lost their bowl game against #32 ranked Utah State by a score of (6-21).  UTEP played against an "average" strength of schedule (SOS) as compared to the "league" average SOS.  The Miners best regular season game was a victory (24-21) over #74 ranked Middle Tennessee State, and their worst loss was to #101 ranked Texas Tech by a score of (26-30).  Overall, the Miners had the #69 ranked team with the #75 ranked offense and the #69 ranked defense from the Complex Invasion College Football Production Model.

2015
UTEP finished the regular season overall at 5-7 (bowl ineligible).  UTEP played against an "easier" strength of schedule (SOS) as compared to the "league" average SOS.  The Miners best game again was their victory over #101 ranked Florida Atlantic (27-17), and their worst loss was to #105 ranked UTSA (6-25).  UTEP had the #115 ranked team in total production with the #119 ranked offense and the #98 ranked defense from the Complex Invasion College Football Production Model.

2016
At the end of the regular season the Miners were again bowl ineligible with a 4-8 win/loss record, while playing against an "easier" strength of schedule (SOS) as compared to the "league" average SOS, meaning that UTEP had an SOS between one and two standard deviations higher than the "league" average SOS.  The Miners best win was over #71 ranked UTSA (52-49) and their worst loss was to #124 ranked Rice by a score of (24-44).  UTEP had the #82 ranked team in total production with the #71 ranked offense and the #73 ranked defense from the Complex Invasion College Football Production Model.

2017
Near the halfway mark of the regular season the Miners were 0-5, while playing against an "average" strength of schedule (SOS) as compared to the "league" average SOS.  The Miners worst loss was to currently ranked #125 Rice by a score of (14-31).  At the time of Kugler's resignation, UTEP had the #130 ranked team in total production (that is the worst team), with the #120 ranked offense and the #128 ranked defense from the Complex Invasion College Football Production Model.