Saturday, February 10, 2018

2017 NCAA FBS Attendance

Recently the NCAA posted the attendance data for the 2017 season.  So let's take a look what happened in terms of attendance in the football bowl subdivision.  First thing to notice is that average team season attendance is the lowest it has been since 2008's average season attendance of 291,053 to 264,397 in 2017.  Average attendance this past season decreased by 7,485 which is the largest decline since the 2013 to 2014 season decline of 10,441 fans per team on average.  The correlation of average season attendance from the 2016 to 2017 season is 0.9699 which is almost identical from one season to another since the 2006 to 2007 seasons.

Given this decline in average season attendance, the question is if the decline is statistically significant.  In order to determine this I calculated a pairwise t-test on the average season attendance over the last two seasons.  Using a 95% confidence level, which is standard in statistics, I find that the pairwise t-test "fails to accept" that the two seasons are statistically significant different from each other.  So while attendance is down, it is not significantly down.

Saturday, January 27, 2018

Competitive Balance in the NFL

With the NFL regular season over, let's take a look at how competitively balanced the NFL was since 1981.  As a reminder, I am using the Noll-Scully measure of competitive balance which statistically measures the actual performance from the ideal performance.  An ideal level of competitive balance using the Noll-Scully measure would equal 1.000, and levels above 1.000 means that the league has some competitive imbalance, with higher Noll-Scully numbers meaning more competitive imbalance.  (Here is a step-by-step guide if you want to calculate this on your own.)  By competitive balance I am looking at how well a league's standings are in relation to a league where wins and losses are determined randomly.  In order to do this, I am going to look at the NFL season statistically as a sample and as a population - mainly for comparison purposes.  The data comes from profootball-reference.com

As you can see below, whether I use a sample or the population, the Noll-Scully measure of competitive balance is very similar.  Additionally, the level of competitive balance has not changed much over the last few seasons, with the Noll-Scully for a sample in 2017 equal to 1.601 and for the population equal to 1.576.  So even with the Brown's win-less season, competitive balance has not declined much from last season.

Tuesday, January 9, 2018

2017 NCAA FBS Final Top 25 Rankings

Below is the list of the Top 25 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 Crimson Tide is the number one team in terms of the most productive team in the FBS!  Links to the previous weeks rankings at the bottom.

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

Previous 2017 Top 25 Rankings
2017 NCAA FBS Top 25 Rankings for Week #15
2017 NCAA FBS Top 25 Rankings for Week #14
2017 NCAA FBS Top 25 Rankings for Week #13
2017 NCAA FBS Top 25 Rankings for Week #12
2017 NCAA FBS Top 25 Rankings for Week #11
2017 NCAA FBS Top 25 Rankings for Week #10
2017 NCAA FBS Top 25 Rankings for Week #9
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

Saturday, January 6, 2018

2017 NCAA FBS National Championship Game

The culmination of the NCAA FBS 2017 takes place as the University of Alabama Crimson Tide and the University of Georgia Bulldogs (both of the Southeastern Conference) will play for the national championship (unless you are the University of Central Florida - which has already claimed that title for their own).  So here is my analysis of the National Championship Game based on the Complex Invasion College Football Production Model.  The model uses data provided from www.cfbstats.com.

Prediction
Given the overall productivity of the two programs, the Complex Invasion College Football Production Model gives the edge to the Alabama Crimson Tide.  Below is a look at each of these two football programs during the 2017 regular season.

Alabama Crimson Tide
The Crimson Tide finished the regular season at 11-1, while playing against an "average" strength of schedule (SOS) as compared to the "league" average SOS, meaning that Alabama's SOS was plus or minus one standard deviation of the "league's" average SOS.  For this season the Crimson Tide's best victory was over #17 ranked LSU by a score of (24-10).  The Crimson Tide's only loss was to #11 ranked Auburn by a score of (14-26).  Alabama has the #1 ranked team in total production with the #13 ranked offense and the #2 ranked defense from the Complex Invasion College Football Production Model.  Last Monday night, Alabama defeated #8 ranked Clemson in the All-State Sugar Bowl by a score of (24-6) to be currently 12-1.

Georgia Bulldogs
The Bulldogs finished the regular season at 11-1, and defeated #11 ranked Auburn (28-7) in the Southeastern conference championship game to be currently 12-1 overall, while playing against an "average" strength of schedule (SOS) as compared to the "league" average SOS, meaning that Georgia's SOS was plus or minus one standard deviation of the "league's" average SOS.  For this season the Bulldogs' best victory was over #20 ranked Appalachian State by a score of (31-10).  The Bulldogs' only loss was to #11 ranked Auburn (during the regular season) by a score of (17-40).  Georgia has the #9 ranked team in total production with the #20 ranked offense and the #4 ranked defense from the Complex Invasion College Football Production Model.  Last Monday night, Georgia defeated #4 ranked Oklahoma in the Rose Bowl by a score of (54-48 - OT) to be currently 13-1.

Friday, January 5, 2018

Arizona Fires Rich Rodriguez

Recently, the University of Arizona has fired head football coach Rich Rodriguez amid a complaint filed by a workplace employee. Arizona was 43-34 during Rodriguez's tenure as head football coach and as can be seen in the chart below, the Wildcats were generally an above average offense and a below average defense, leading to a team that waffled back and forth around mediocrity.

Below is a chart of offense, defense and total production of the Arizona Wildcats football program during Rodriguez'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).   All rankings in this blog come from my Complex Invasion College Football Production Model.  More details about the program under Rodriguez including a link to his most recent contract extension are after the chart below.


Rich Rodriguez [2012 - 2017]

2012
At the end of the regular season the Wildcats were 7-5 (and were bowl eligible) and won their bowl game over #55 ranked Nevada (49-48) to finish the season at 8-5 overall.  Arizona played against a "tougher" strength of schedule (SOS) as compared to the "league" average SOS, meaning that the Wildcats SOS was between one and two standard deviations lower than the "league's" average SOS.  The Wildcats best win was over #21 ranked Oklahoma State (59-38) and their worst loss was to #36 ranked UCLA by a score of (10-66).  Arizona had the #61 ranked team in total production with the #13 ranked offense and the #119 ranked defense from the Complex Invasion College Football Production Model.


2013
At the end of the regular season the Wildcats were 7-5 (and were bowl eligible) and defeated #73 ranked Boston College (42-19) to finish the season at 8-5 overall.  Arizona played against an "average" strength of schedule (SOS) as compared to the "league" average SOS, meaning that the Wildcats SOS was plus or minus one standard deviation of the "league" SOS.  The Wildcats best victory was against #3 ranked Oregon (42-16) and their worst loss was to #81 ranked Washington State by a score of (17-24).  Arizona had the #42 ranked team in total production with the #44 ranked offense and the #60 ranked defense from the Complex Invasion College Football Production Model.

2014
The Wildcats finished the regular season at 10-2 and were again bowl eligible.  The Wildcats lost the Pac 12 conference championship game to #2 Oregon (13-51) and then were defeated by #13 ranked Boise State in their bowl game by a score of (30-38) to finish at 10-4 overall.  Arizona played against an "average" strength of schedule (SOS) as compared to the "league" average SOS.  The Wildcats best regular season game was a victory (31-24) over #2 ranked Oregon and their worst loss was to #44 ranked UCLA by a score of (7-17).  Overall, the Wildcats had the #46 ranked team with the #15 ranked offense and the #110 ranked defense from the Complex Invasion College Football Production Model.

2015
Arizona finished the regular season overall at 6-6 (bowl eligible), and defeated #78 New Mexico by a score of (45-37) to finish with a winning overall record of 7-6.  Arizona played against an "average" strength of schedule (SOS) as compared to the "league" average SOS.  The Wildcats best game was their victory over #49 ranked Utah (37-30) and their worst loss was to in state rival #81 ranked Arizona State (37-52).  Arizona had the #70 ranked team in total production with the #30 ranked offense and the #110 ranked defense from the Complex Invasion College Football Production Model.

2016
At the end of the regular season the Wildcats were 3-9 (and were bowl ineligible), while playing against an "average" strength of schedule (SOS) as compared to the "league" average SOS.  The Wildcats best win was over #104 ranked Hawaii (47-28) and their worst loss was to #95 ranked Oregon State by a score of (17-42).  Arizona had the #107 ranked team in total production with the #84 ranked offense and the #109 ranked defense from the Complex Invasion College Football Production Model.

2017 
The Wildcats finished the regular season at 7-5, while playing against an "easier" strength of schedule (SOS) as compared to the "league" average SOS, meaning that Arizona's SOS was between one and two standard deviations higher than the "league's" average SOS.  For this season the Wildcats' best victory was over #39 ranked Washington State by a score of (58-37); their only victory over a team currently ranked in the top half of the FBS.  The Wildcats' worst loss was to in-state rival #78 ranked Arizona State by a score of (30-42).  Arizona has the #49 ranked team in total production with the #12 ranked offense and the #105 ranked defense from the Complex Invasion College Football Production Model.  They played the #44 ranked Purdue Boilermakers in the Foster Farms Bowl, where they lost by a score of 38-35 to finish 7-6 overall for the season.
 
Louisiana (Lafayette) and Mark Hudspeth

Tuesday, January 2, 2018

Has the NFL Player Protests Led to Lower NFL Regular Season Home Game Attendance?

Has the NFL Player Protests Led to Lower NFL Regular Season Home Game Attendance?  During the 2017 NFL season, some NFL players knelt during the playing of the national anthemVice President Pence left one game after the players knelt and President Trump also voiced concerns about the NFL players protesting during the national anthem.  Some NFL fans have proposed boycotting NFL games due to the players actions, although its impact is not clear.

Now that the regular season is over, let's take a look at the numbers and see if there is a statistically significant change in NFL regular season home game attendance.  First, the numbers.  Using the NFL attendance data from Pro Football Reference, I looked at the 2002 to 2017 NFL regular seasons.  This is a time period where the number of teams remained constant at 32 (even though some teams moved cities or stadium capacity changed).  Given the relative stability during this time period, it is easier to make season to season comparisons.  As you can see below, 2016 had the highest total regular season home game attendance, followed by a rather large decrease in 2017.  Also notice, that NFL regular season total home game attendance increases and decreases from season to season.



Let's look at that dip from 2016 to 2017.  That represents a decline of 535246 total fans for the 2017 season as compared to the leagues high water mark in 2016.  Over half of the decline is due to the Los Angeles Chargers playing in a much smaller stadium that in the past.  The Los Angeles Rams, the Cincinnati Bengals and the Washington Redskins also had sharp declines in total home game attendance.  Of the 32 teams, 22 had declines in total home game attendance, 9 had increases in attendance and 1 team (Philadelphia) had no change in total home game attendance as compared to 2016.  In percentage terms, attendance is down 3.1% from 2016 overall, and taking out the LA Chargers, total home game attendance is down 1.6%.  There is no doubt that NFL regular season total home game attendance is down from 2016.

But other seasons have seen declines in home game attendance, even without NFL player national anthem protests.  So a decline in attendance from one season to another is not unusual.  What I want to know is if this decline is unusual as compared to the ups and downs of NFL regular season team home attendance, and the way to determine that is if the team's home attendance is statistically different from last season to this season.

To do that i will use a statistical technique called a t-test.  Specifically, I am using a paired, two-tailed t-test; paired since the same teams have been in the NFL since 2002 and two-tailed since attendance can go up or down for each team from one season to the next.  A t-test is a statistical technique that compares the means of two variables and tells us if they are different from each other, and lets us know if they are significantly different as opposed to them happening by chance.  Statistical significant is the way to judge whether the results are meaningful.  In general we use an error rate less than 5% (p value <=0.05) to judge whether two variables (like NFL team home game attendance from one season to the next) are different from each other.  We choose a low error rate to avoid Type I error, which is to incorrectly conclude the existence of something that does not exist.

So what are the results?  First, from 2002 to 2016, none of the paired, two-tailed t-tests for NFL team home attendance are statistically significant.  Even the "great recession" of 2007 to 2009 did not yield a statistically significant difference in NFL team regular season home game attendance, even though we see attendance declining during that time period.  If something that large did not impact the NFL team regular season home game attendance, would a fan boycott?

Using the same paired, two-tailed t-test, I find that team regular season home game attendance was not statistically significant, and as such I cannot conclude that the NFL players protests during the national anthem lead to a decline in attendance as opposed to NFL team regular season home game attendance decreased due to random chance.