Monday, August 19, 2019

Which FBS teams have Stadium Wide Alcohol Availabilty?

Recently, the WSJ had an article regarding the sale of alcohol and its impact on college football attendance.  The conclusion was that alcohol sales should help college football attendance.  I am skeptical.  First of all, the number of FBS schools that now allow general admission alcohol sales to legally aged spectators has been increasing over the last few years (from 25 in 2012 to 70 (currently) in 2019), while at the same time average attendance has been falling over the same time period.  Second, unpublished research of mine suggests that general admission alcohol sales at FBS stadiums has no statistically significant effect on college football attendance, which is the same conclusion found by Chastian, Gohmann & Stephenson in the Journal of Sports Economics for three "Group of Five" conferences during the 2005 to 2012 seasons.


Below is a list of FBS teams that allow general admission alcohol sales, the year in which general admission alcohol sales began and a link on each team's name for the source that I used to determine if alcohol sales are allowed and the year in which it began.  My links are not 100% complete, as I cant find the original article stating that UNLV allowed alcohol sales in 1971; but I feel that the list is accurate.  Of course, more FBS teams may allow (or revoke) alcohol sales to general admission spectators in the future.  I plan to update this blog as new information becomes available.  If you find any errors, please look over the link first, and then let me know about the error.

FBS School and Year Began/Re-newed

Air Force 2017

Akron 2012

Arizona 2018

Arizona State 2018

Arkansas 2019

Boston College 2018

Bowling Green 2008

California 2019

Cincinnati 2007 (at least since 2007)

Colorado 2018

Colorado State 1976

Connecticut 2009 (maybe earlier than this)

Florida Atlantic 2014

Fresno State 2017 [allowed before 2006; not allowed from 2006 - 2016]

Georgia State 2013

Hawai'i 2004 (at least since 2004)

Houston 1998

Illinois 2019

Indiana 2019

Kent State 2009

Louisiana-LaFayette (Louisiana) 2009

Louisiana-Monroe 2013

Louisiana State University (LSU) 2019

Louisville 1998

Marshall 2017

Maryland 2015

Massachusetts 2012 (at least since 2012)

Memphis 2009

Miami (FL)  (at least since 2004)

Miami (OH) 2016

Minnesota 2012 [(at least) 2000 - 2008 allowed; 2009 - 2011 not allowed]

Missouri 2019

Nevada 1992

New Mexico 2016

New Mexico State 2015

North Texas 2014

Northern Illinois 2015

Ohio 2017

Ohio State 2016

Oklahoma 2019

Oklahoma State 2018

Oregon 2018

Oregon State 2018

Pittsburgh 2016

Purdue 2017

Rice 2015

Rutgers 2019

San Diego State at least since 2004

San Jose State 2017  [2004-2012 allowed; 2013-2016 not allowed]

Southern Methodist (SMU) 2014

South Alabama 2012 [will continue for its on campus stadium in 2020]

South Florida 2018

Syracuse 1980

Temple 2004 (at least since 2004)

Tennessee 2019

Texas 2015

Texas A&M 2019

Texas State 2016

Texas Tech 2019

Toledo 2013

Troy 2014

Tulane 2014

Tulsa 2016

UAB 2018

UNLV 1971

UTEP 2012

UTSA 2009

Vanderbilt 2019

Wake Forest 2016

Western Kentucky 2012

West Virginia 2011

Wyoming 2017

Wednesday, August 14, 2019

Does the English Premier League have a Competitive Balance Problem?

Recently, the Wall Street Journal addressed concerns about the competitiveness of the English Premier League (paywall).  So let's take a look at the numbers.  First, I calculated the Noll-Scully measure of competitive balance for the last decade in the English Premier League.

Since the English Premier League has "draws" or ties, the Noll-Scully competitive balance measure must be calculated with the trinomial distribution, which as Richardson shows in his Eastern Economic Journal article, the idealized standard deviation is [(1-p)4n]^(1/2); where n is the number of games played and p is the probability of balanced teams tying.  The number of games played is simple, its 38.  The calculation of p is not as simple.  Here, I have to make a determination.  What I did was to look at the last (approximately) 20% of the season, and calculate the number of games teams that finished 9th, 10th, 11th and 12th in the EPL final table, in which those teams tied.  Then I took the average of those four teams to calculate p.

Using data from [https://datahub.io/sports-data/english-premier-league#resource-season-1819], the Noll-Scully Competitve Balance measure reveals the following:


As you can see, the English Premier League has been becoming less competitive since the 2015/16 season.  Yet, is it a problem?  That is much harder to definitively answer.  Overall, it seems to me that an economic problem exists if the league becoming less competitive results in a significant decrease in attendance, revenues and viewership.  That doesn't seem to be the case, so even with the EPL recently becoming less competitive, it is not a problem.

For those interested in the actual numbers, see below.

Season Noll-Scully
2009/10 3.104
2010/11 2.469
2011/12 3.178
2012/13 3.141
2013/14 3.808
2014/15 3.066
2015/16 2.826
2016/17 3.507
2017/18 3.584
2018/19 4.086


Wednesday, June 19, 2019

U.S. Women's Soccer Salary Discrimination Suit

In March of this year, members of the US Women's Soccer team filed a lawsuit alleging that women's soccer team are being discriminated against in terms of their salary.   The legal definition of gender discrimination is different from the economic definition.  In economics, we think about how salaries are determined based on two concepts:  production and revenue.  Let's take each in turn.  There is no debate that the US Soccer women's team is more productive than the US Soccer men's team.  US Soccer women's team has been one of the premier teams in international play, with the women's team winning the 2015 World Cup.  The second is revenue and until recently, not much was publicly know regarding revenue.  Now that has changed; ticket sales revenue between the two programs has been very similar, with the women's program now generating more ticket sales revenue than the men's program.   So economically, since the women's program is superior in performance and now slightly better in terms of revenue, then the women's players should be paid more than the men's player's in a competitive market.  

US Soccer denied gender discrimination.  US Soccer stated, "that no pay comparison can be made between the women’s players, who are paid in guaranteed salaries and benefits, and men’s players, who are paid in appearance fees." 

Ok, so the two groups are paid differently and that difference is their argument as to why the salaries are different.  I can understand that different salary structures yield different salaries, but it is unclear as to why the men's program and the women's program have different salary structures.  It could be that the men's players have a substantial substitute salary options as compared to women's players; and as such the women's players chose the guaranteed salaries option as opposed to the appearance fee option chosen by the men's players. 

What is going to happen?  Who knows.  While I am not a lawyer, I think the women's lawsuit has an uphill battle, since their salaries are based on a collective bargaining agreement. 

Wednesday, January 9, 2019

2018 NCAA FBS Competitive Balance

With the end of the NCAA FBS 2018 season, I can update the how competitive the highest tier of college football was using the Noll-Scully Competitive Balance measure.  I have decided to calculate this since 1996 (the year that the NCAA FBS went to overtime to decide games), thus there are no ties and the version used by Roger Noll and Gerald Scully is used here.  For those that are interested in calculating this on their own, here is a step-by-step guide as to how to perform the Noll-Scully competitive balance calculation.

As you can see below, competitive balance slightly improved this past season as the Noll-Scully moved closer to one (a league where wins and losses randomly occur), and that for the last 20 plus years, competitive balance among NCAA FBS programs has been relatively stable.



Tuesday, January 8, 2019

2018 NCAA FBS Final Top 25 Ranking

With all of the NCAA FBS post season now complete here is the final Top 25 rankings using the Complex Invasion College Football Production Model from the data provided from www.cfbstats.com

According to the Complex Invasion College Football production model, the Clemson University Tigers are the most productive team in all of the Football Bowl Subdivision rankings.  In terms of overall productivity, Clemson is the best team, and Alabama the second best team; the rest of the FBS is quite a ways behind those two.  Kinda nice that it also worked out that way on the field.

Here are the details of the Complex Invasion College Football production model.

Rank Team
1 Clemson
2 Alabama
3 Utah State
4 Fresno State
5 Mississippi State
6 Appalachian State
7 Georgia
8 Cincinnati
9 UCF
10 Florida
11 Ohio State
12 Washington
13 Ohio
14 Notre Dame
15 Iowa
16 Boise State
17 Michigan
18 Army
19 Miami (Florida)
20 Memphis
21 UAB
22 Penn State
23 West Virginia
24 Oklahoma
25 Virginia

Previous 2018 Top 25 Rankings
2018 NCAA FBS Top 25 Rankings for Week #1
2018 NCAA FBS Top 25 Rankings for Week #2
2018 NCAA FBS Top 25 Rankings for Week #3
2018 NCAA FBS Top 25 Rankings for Week #4
2018 NCAA FBS Top 25 Rankings for Week #5
2018 NCAA FBS Top 25 Rankings for Week #6
2018 NCAA FBS Top 25 Rankings for Week #7
2018 NCAA FBS Top 25 Rankings for Week #8
2018 NCAA FBS Top 25 Rankings for Week #9
2018 NCAA FBS Top 25 Rankings for Week #10
2018 NCAA FBS Top 25 Rankings for Week #11
2018 NCAA FBS Top 25 Rankings for Week #12
2018 NCAA FBS Top 25 Rankings for Week #13
2018 NCAA FBS Top 25 Rankings for Week #14
2018 NCAA FBS Top 25 Rankings for Week #15

Monday, January 7, 2019

2018 NCAA FBS National Championship Game

Tonight the NCAA FBS National Championship game pits the Alabama Crimson Tide from the Southeastern Conference against the Clemson Tigers from the Atlantic Coast Conference .  Here is my analysis of based on the Complex Invasion College Football Production Model, which uses data provided at www.cfbstats.com.  The model has been updated to include all the bowl game results, which is why the numbers below might be different from last weeks game.

Here are the details of the Complex Invasion College Football production model.

Prediction
Given the overall productivity of the two programs, the Complex Invasion College Football Production Model gives the edge to the Clemson Tigers.  Below is a "tale of the tape" for each of these two football programs this season.

Alabama Crimson Tide (14-0) of the Southeastern Conference
Based on the Complex Invasion College Football Production Model:
Strength of Schedule:  Average
Highest Ranked Victory:  #6 currently ranked Mississippi State
Lowest Ranked Loss:  -----
Current Total Production Rank:  #2
Current Offense Production Rank:  #2
Current Defense Production Rank:  #13

Clemson Tigers (14-0) of the Atlantic Coast Conference
Based on the Complex Invasion College Football Production Model:
Strength of Schedule: Average
Highest Ranked Victory:  #15 currently ranked Notre Dame
Lowest Ranked Loss:  -----
Current Total Production Rank:  #1
Current Offense Production Rank:  #1
Current Defense Production Rank:  #4

2018 Bowl Game Analysis
2018 Cure Bowl
2018 New Mexico Bowl
2018 Las Vegas Bowl 
2018 Camellia Bowl 
2018 New Orleans Bowl
2018 Cheribundi Boca Raton Bowl
2018 DXL Frisco Bowl 
2018 Bad Boys Mowers Gasparilla Bowl 
2018 Makers Wanted Bahamas Bowl
2018 Famous Idaho Potato Bowl 
2018 Jared Birmingham Bowl 
2018 Dollar General Bowl 
2018 Sofi Hawai'i Bowl 
2018 Lockheed Martin Armed Forces Bowl 
2018 ServPro First Responder Bowl 
2018 Quick Lane Bowl 
2018 Cheez-it Bowl 
2018 Walk On's Independence Bowl 
2018 New Era Pinstripe Bowl

Thursday, January 3, 2019

2018 NFL Payroll and Performance

Yesterday, I blogged about competitive balance in the NFL for the 2018 season.  Today I will look at the relationship between payroll and performance in the NFL for the 2018 season.  The basic idea is that teams that pay higher salaries to their players will perform better.  As sports economists, we tend to be highly skeptical of this hypothesis, but it is a persistent topic - especially in baseball.  So let's see what happens.

To do this, first I need the data.  Payroll data is from spotrac and performance data is from profootball reference.   Once that is done, the first thing I did was to calculate the correlation coefficient between payroll and performance, and the correlation between payroll and performance is NEGATIVE!!  That is a first for me.  Now, one thing we know statistically is that you should not draw conclusions from descriptive statistics, but there are those that do.  If one was to draw a conclusion (again this is not statistically valid, then those who do this would have to conclude that lower pay results in better performing NFL teams).  I doubt you will hear much from the pay and performance crowd about the 2018 NFL season.

Running a regression between performance and payroll (with robust standard errors), I get that the coefficient on payroll is negative and statistically significant as well.  This is a problem for the payroll and performance hypothesis holders.  Additionally, just for the 2018 season, payroll "explains" only 17% of team performance, so this seems to be not only the wrong sign, but also the not a lot.