Monday, September 30, 2013

2013 NCAA FBS Top 25 Ranking for Week 5

The latest Top 25 NCAA FBS rankings from the Complex Invasion College Football Production Model has idle Baylor remaining as the most productive team in the Football Bowl Subdivision.  As conference play starts going throughout the FBS, we will see some of these teams start to drop out of the Top 25 and teams that are not listed (notably Alabama - which jumped from #42 to #31) start to make an appearance.  To me the biggest surprise for this week is that Missouri is the most productive SEC team to date.  Again, I think this will change as the season progresses; but at this time that is what the model reports.

I have forgotten to mention this season that the data that I use comes from College Football Statistics.

Rank Team
1 Baylor
2 Oregon
3 Louisville
4 Florida State
5 Washington
6 Miami (Florida)
7 Wisconsin
8 Ohio State
9 Maryland
10 UCLA
11 Utah State
12 Missouri
13 Houston
14 Clemson
15 Mississippi State
16 Cincinnati
17 UCF
18 Michigan State
19 Georgia Tech
20 Iowa
21 Utah
22 Oklahoma
23 Texas A&M
24 LSU
25 Marshall

Previous Top 25 Ranks for 2013
2013 NCAA FBS Top 25 Ranking for Week 4
2013 NCAA FBS Top 25 Ranking for Week 3
2013 NCAA FBS Top 25 Ranking for Week 2

Saturday, September 28, 2013

AP Top 25 Marquis Games for Week 5

Using the AP Poll here are the four marquis games for this week and analysis using the Complex Invasion College Football Production Model.

AP #6 LSU vs. AP #9 Georgia
LSU (4-0) is currently ranked using the NCAA FBS Production Model (linked above) as the #9 most productive team in the football bowl subdivision with the #10 most productive offense and the #25 most productive defense.  LSU has not played any team that is currently above average in terms of production.  That said, LSU still has played an average strength of schedule or SOS (SOS = 92.00 which is within one standard deviation of the "league" average SOS).

Georgia (2-1) is currently ranked using the NCAA FBS Production Model as the #37 most productive team overall with the #32 most productive offense and the #54 most productive defense.  The Bulldogs are (1-1) against above average teams using the production model and have played an average SOS of 61.67 which is within one standard devation the average SOS for the "league"

AP #14 Oklahoma vs. AP #22 Notre Dame
Oklahoma (3-0) is currently ranked using the NCAA FBS Production Model as the #31 most productive team in the football bowl subdivision with the #60 most productive offense and the #15 most productive defense.  The Sooners are (1-0) against above average productive teams (West Virginia).  OU has played an average strength of schedule or SOS (SOS = 91.00 which is within one standard deviation of the "league" average SOS).

Notre Dame (3-1) is currently ranked using the NCAA FBS Production Model as the #55 most productive team overall with the #66 most productive offense and the #59 most productive defense.  The Irish are (1-1) against above average teams using the production model and has played an average SOS of 72.75.

AP #21 Mississippi vs. AP #1 Alabama
Mississippi (3-0) is currently ranked using the NCAA FBS Production Model as the #41 most productive team in the football bowl subdivision with the #58 most productive offense and the #33 most productive defense.  Ole Miss are 1-0 against teams that are currently above average in terms of production.  The Rebels have played an average strength of schedule or SOS (SOS = 82.33 which is within one standard deviation of the "league" average SOS).

Alabama (3-0) is currently ranked using the NCAA FBS Production Model as the #42 most productive team overall with the #42 most productive offense and the #50 most productive defense.  The Crimson Tide are (2-0) against above average teams using the production model and has played an tougher SOS = 56.67.  I concluded that Alabama's SOS is tougher given that their SOS is less than one standard deviation from the "league" SOS.

AP #23 Wisconsin vs. #4 Ohio State
Wisconsin (3-1) is currently ranked using the NCAA FBS Production Model as the #5 most productive team in the FBS with the #7 most productive offense and the #10 most productive defense.  The Badgers are (0-1 loss to Arizona State) against teams that are currently above average in terms of production.  Wisconsin still has played an easier strength of schedule or SOS (SOS = 101.50 which is greater than one standard deviation of the "league" average SOS).

Ohio State (4-0) is currently ranked using the NCAA FBS Production Model as the #6 most productive team overall with the #6 most productive offense and the #20 most productive defense.  The Buckeyes have not yet played a team that is above average teams using the production model and has played an average SOS of 112.00 which is easier than the average SOS for the "league" given that OSU's SOS is currently greater than one standard deviation above the leagues average SOS.

Wednesday, September 25, 2013

2013 NCAA FBS Top 25 Defensive Ranking for Week 4

Today I am going to post the top 25 teams in terms of defense for 2013 at the end of Week #4.  As a reminder, a team's defense is based on how well the team's defense keeps their opponent from acquiring the ball, moving the ball, maintaining possession of the ball, reducing their opponent's scoring efficiency and athletic conference.  Then I estimate the weight that each of those variables has on points scored against.  From there I take the estimate and multiply it by that variables number for the team.  Finally, I adjust (if applicable) for athletic conference.  For this past week, there is no adjustment made for athletic conference.  So here are the top 25 defensive teams.

Rank Team
1 Louisville
2 Oregon
3 Baylor
4 Washington
5 Florida State
6 Miami (Florida)
7 Arizona
8 Michigan State
9 Colorado
10 Wisconsin
11 UCF
12 Georgia Tech
13 Maryland
14 Stanford
15 Oklahoma
16 UCLA
17 Oklahoma State
18 Florida
19 Utah State
20 Ohio State
21 East Carolina
22 Texas State
23 USC
24 Navy
25 LSU

Tuesday, September 24, 2013

2013 NCAA FBS Top 25 Offensive Rankings for Week 4

Today I am going to post the top 25 teams in terms of offense for 2013 at the end of Week #4.  As a reminder, a team's offense is based on how well team's acquire the ball, move the ball, maintain possession of the ball, their scoring efficiency and athletic conference.  Then I estimate the weight that each of those variables has on points scored.  From there I take the estimate and multiply it by that variables number for the team.  Finally, I adjust (if applicable) for athletic conference.  For this past week, there is no adjustment made for athletic conference.  I expect this to change as the season progresses, and will update this periodically - although not sure if I will do this each week.

Rank  Team 
1 Baylor
2 Texas A&M
3 Oregon
4 Louisville
5 Wyoming
6 Ohio State
7 Wisconsin
8 Florida State
9 Utah
10 LSU
11 Maryland
12 Northwestern
13 UCLA
14 Nebraska
15 Missouri
16 Washington
17 Texas Tech
18 Mississippi State
19 Cincinnati
20 Ball State
21 Utah State
22 Georgia Tech
23 Oregon State
24 Indiana
25 Oklahoma State

Tomorrow I plan on posting the top 25 defenses as of 2013 Week #4.

Monday, September 23, 2013

2013 NCAA FBS Top 25 Ranking for Week 4

The latest Top 25 NCAA FBS rankings from the Complex Invasion College Football Production Model has Baylor retaking the number one rank from Oregon.  These two teams are rather interesting in the individual offense and defense rankings.  For Baylor on the offensive side, they are currently the #1 ranked offense in the FBS and on the defensive side of the ball they are currently ranked as the #3 ranked defense.  For Oregon they are the #3 ranked offense and #2 ranked defense.  Yet for this week, Baylor's increase in offense has more than offset their slightly lower total production on defense, allowing Baylor to reclaim the top spot in the NCAA FBS Production ranking.

Below are the top 25 for the end of week #4, as well as the previous top 25 for weeks #2 and #3.

Rank Team
1 Baylor
2 Oregon
3 Louisville
4 Florida State
5 Wisconsin
6 Ohio State
7 Washington
8 Maryland
9 LSU
10 UCLA
11 Miami (Florida)
12 Georgia Tech
13 Wyoming
14 Utah State
15 Oklahoma State
16 Texas A&M
17 Arizona
18 Mississippi State
19 Utah
20 Missouri
21 Cincinnati
22 Houston
23 UCF
24 Michigan State
25 Marshall

Previous Top 25 Ranks for 2013
2013 NCAA FBS Top 25 Ranking for Week 3
2013 NCAA FBS Top 25 Ranking for Week 2

Friday, September 20, 2013

Does Strength of Schedule Matter? - Revisited

In November 2010 I wrote a blog about the impact that strength of schedule has on winning in the NCAA Football Bowl Subdivision.  What I concluded was that strength of schedule does not have a statistically significant effect on winning percentage in FBS college football.  So I thought that now would be a good time to revisit the strength of schedule argument, as this is the time in the season where teams have played a larger proportion of their games against poor performing FBS teams or against FCS teams.  Thus this should be the time where schedule strength should have the greatest impact on winning percent.  I collected the data for all 125 teams in the NCAA FBS (winning percent, points scored, points surrendered and a measure of strength of schedule) through the third week of the 2013 regular season, since this seems to be a time period for strength of schedule to have the greatest impact on winning percent.

To investigate what the effect of strength of schedule has on NCAA FBS winning percentage, I conducted a statistical analysis using linear regression.  The regression just fits a line to the underlying data and estimates the impact and statistical significant (if any) of the independent variables on the dependent variable.  For our purposes, the dependent variable is winning percentage and the independent variables are points scored, points surrendered and strength of schedule.

The results are that points scored is positive and statistically significant (has a statistical impact with at least a 95% level of confidence), that points surrendered is negative and statistically significant, and that strength of schedule is statistically no different from zero using a 95% confidence level. I have also adjusted for heteroskedasticity (unequal scatter in the data) and adjusted for the different FBS conferences and in each case the overall conclusion remains the same.

In other words, for the "league" as a whole schedule strength does not affect whether teams win or lose.  Another way of thinking about this is that high quality teams win against high quality opponents and low quality opponents and low quality opponents lose to both high quality and low quality opponents on average.  This schedule strength issue seems to be a reason to discount the performance of "inferior" teams - think Boise State and Utah a few years ago or most likely Louisville this season.  Yet while this may be a prevailing attitude among many college football fans, especially fans of the "high class" conferences - this perception does not hold up to statistical scrutiny.

Thursday, September 19, 2013

Arizona State's Todd Graham Contact Extension

AP reports that Arizona State's head football coach Todd Graham will receive a contract extension, subject to Board approval through 2018.  His previous contract was through 2016.  So I thought would be a good time to look at ASU under Graham using the Complex Invasion College Football Production Model, which is just the 2012 and part of the 2013 seasons.

In 2012, the Sun Devils went 7-5 in the regular season and played in the Kraft Fight Hunger Bowl defeating Navy (as the model "predicted") to finish 8-5.  Of ASU's five losses - four were to teams that were ranked #50 or higher (at the end of the season) and the other was a loss to Missouri which was ranked #93 at the end of the season.  All of ASU's victories were against teams ranked (at the end of the season) #60 or higher. The Sun Devil's victory of the highest ranked opponent was against in state rival University of Arizona at #61.  Overall, ASU faced an "easier" than average strength of schedule (SOS) of 76.54 as compared to the average of 65.53 for the "league".  Given that ASU's SOS is greater than one standard deviation above the mean, I conclude that their SOS was "easier".  Yet, ASU finished the 2012 season as the #24 team in overall productivity, with the #25 most productive offense and the #34 most productive defense, which is an improvement over the Sun Devil's #63 final total production ranking for the 2011 season.

This season through week #3, ASU is 2-0 with an average SOS but an above average production ranking (#25 in total production, #40 in offensive production and #19 in defensive production).  Given their performance so far, it seems as if the Sun Devils are making a good investment to date in Todd Graham.

I hope to look at head coach Graham since 2008 in early 2014, given his head coaching stops at Tulsa, Pitt, and now Arizona State it would be interesting to see how those teams have performed before, during, and after (probably only possible with my data for Pitt).

Wednesday, September 18, 2013

NHL Goalie Ranking

ESPN has ranked current NHL goalies and so have I in the past.  So I thought that I would link to my latest NHL goalie ranking at the end of the 2013 regular season and re-post the top 20 here.


Player Team
WAA
SV%
1 Sergei Bobrovsky CBJ
3.720
0.932
2 Craig Anderson OTT
3.364
0.941
3 Henrik Lundqvist NYR
2.863
0.926
4 Tuukka Rask BOS
2.860
0.929
5 Antti Niemi SJS
2.518
0.924
6 Cory Schneider VAN
2.152
0.927
7 Jimmy Howard DET
2.137
0.923
8 James Reimer TOR
2.054
0.924
9 Corey Crawford CHI
1.850
0.926
10 Robin Lehner OTT
1.745
0.936
11 Devan Dubnyk EDM
1.563
0.920
12 Braden Holtby WSH
1.550
0.920
13 Viktor Fasth ANA
1.025
0.921
14 Ben Bishop OTT, TBL 0.968
0.920
15 Ray Emery CHI
0.792
0.922
16 Jason LaBarbera PHX
0.791
0.923
17 Chad Johnson PHX
0.777
0.954
18 Kari Lehtonen DAL
0.732
0.916
19 Nikolai Khabibulin EDM
0.712
0.923
20 Ryan Miller BUF
0.668
0.915

On opening day I will come back to NHL goalies and look at how consistent goalies have been over the last few years.

Tuesday, September 17, 2013

Texas After Week 3 in 2013

As I mentioned yesterday, since there is some interest in the University of Texas, I have decided to take a more in depth look at the Longhorns for the last two weeks using the Complex Invasion College Football Production Model.  (There is not enough variation in the data for the model to be very reliable for the first week.  I could run it and it would come out OK, but not good enough for such a small sample of games).

FYI:  2013 NCAA FBS Top 25 for Week 3 (link at bottom of blog for week two)

This past weekend the Texas Longhorns lost to Mississippi (aka Ole Miss) and the week before lost to BYU.  As I have written about earlier, Texas has not really been an elite team since 2009 with final season rankings of #70 in 2010, #46 in 2011 and #53 in 2012.  The last two seasons Texas has been above average in terms of on-field production, but the Longhorns are no where near competing at a national championship level.

At the end of the second week of the regular season, the Longhorns lost (21-40) to BYU and fired their defensive coach as a result.  At the end of that week, Texas was the #72 most productive team in the NCAA FBS (which is below average).  On the bright side they had the #18 most productive offense, but the #117 most productive defense.  In other words, their were only eight other teams in the NCAA FBS that had a defense with lower productivity.  In terms of strength of schedule, Texas had an 82.5 versus an 82.94 for the "league" as a whole, meaning that Texas was playing an average strength of schedule.

This past weekend also saw the Longhorns losing to #64 ranked Mississippi going into the game.  Mississippi ended up as the #41 ranked team at the end of last week.  Looking at the Longhorns, even though they lost the game they improved their overall ranking to #64 (slightly below average).  On the offensive side their rank slipped to #22 and their defensive rank improved to #98.  Like the previous week, their strength of schedule was 79 as compared to a 78.98 for the "league" as a whole, meaning that they have played a schedule that is average to the league.

It looks like it might be a long season for Longhorn fans, given that they are rather average and their future schedule (other than Iowa State) is against teams currently ranked better than Texas.

Monday, September 16, 2013

2013 NCAA FBS Top 25 Ranking for Week 3

The latest Top 25 NCAA FBS rankings from the Complex Invasion College Football Production Model have Oregon moving up to #1 over idle Baylor.  Alabama and Texas A&M are most notable still absent.  Given the rather similar production performance of the two teams relative to the rest of the "league", this is not surprising.  As teams play more games, the variance between the teams relative performance should get smaller and thus teams such as Alabama will increase in their ranking.  So given Alabama plays my alma mater Colorado State next week, expect that Alabama will move up from their current ranking, but not sure if they will crack the top 25 yet.

Rank Team
1 Oregon
2 Baylor
3 Louisville
4 Arizona
5 Oklahoma State
6 LSU
7 Utah State
8 Florida State
9 Maryland
10 Marshall
11 Utah
12 Georgia Tech
13 Michigan State
14 USC
15 Oklahoma
16 Washington
17 UCLA
18 Houston
19 Texas Tech
20 Wisconsin
21 Wyoming
22 UCF
23 Cincinnati
24 Colorado
25 Arizona State

Given there is some interest by readers of this blog in the University of Texas, I plan to look at Texas over the last two weeks (in terms of their offense and defense) and how they compare to the rest of the "league".  I hope to have this done tomorrow.

Previous Top 25 Ranks
2013 NCAA FBS Top 25 Ranking for Week 2

Saturday, September 14, 2013

NCAA FBS Performance 2008 to 2012

Over the last few weeks I have wanted to look at how NCAA FBS teams have fared year to year.  After spending just a little time putting the data together, I have calculated the correlation coefficient (called r, which measures the degree to which two variables vary together or apart) and the coefficient of determination (called r2, which measures the proportion of variance in common between the two variables).  So I will present both statistics - though I will only be interpreting r2 as that is the statistic that looks at what I am interested in explaining.

Since the 2008 NCAA FBS season, the variation in common of winning percentage in one year to the next explains from 36% in the 2008-2009 seasons to 23.5% for the 2011-2012 seasons.

Winning Percent r r2
2008-2009 0.5999 0.3599
2009-2010 0.5257 0.2764
2010-2011 0.5527 0.3055
2011-2012 0.4851 0.2354

So given that NCAA FBS previous seasons winning percent explains less than half of the next seasons winning percent, how does the Complex Invasion College Football Production Model's ranking relate year to year?  As you can see in the table below the variation in total NCAA FBS Production Rank from one year to the next explains between 28% and 43% of the variation in total rank.

Total Rank r r2
2008-2009 0.6536 0.4272
2009-2010 0.5362 0.2875
2010-2011 0.6551 0.4291
2011-2012 0.5262 0.2769

In terms of offensive ranking, the previous seasons offensive rank explains from 19% to 34% and in terms of defensive ranking, the prior seasons defensive rank explains from 28% to 34%.

Off. Rank r r2
2008-2009 0.4830 0.2333
2009-2010 0.4853 0.2355
2010-2011 0.5861 0.3435
2011-2012 0.4439 0.1970



Def. Rank r r2
2008-2009 0.5833 0.3402
2009-2010 0.5296 0.2805
2010-2011 0.5511 0.3037
2011-2012 0.5334 0.2845

In each case, the previous season is not a great predictor of the next season in that the variation in common is less than 50%; which is what makes college football so interesting - that for the "league" as a whole we really cannot predict what will happen.

Friday, September 13, 2013

Trouble in Texas

After being man-handled by BYU over the past weekend, head football coach Mack Brown of the University of Texas fired their defensive coordinator according to ESPN.  So let's take an in depth look at the University of Texas Longhorn's football team over the last few years using my Complex Invasion College Football Production Model from 2008 to 2012.

Below is a table with Texas' wins, losses, total production rank, offensive production rank, defensive production rank and average strength of schedule.  The lower the rank number the better their production.  As you can see, Texas was a very productive team during the 2008 and 2009 seasons, and then the Texas Longhorn offense declined dramatically leading to below average production in the 2010 season.  The 2011 and 2012 seasons resulted with above average production but was no where near their 2008 and 2009 performances.  Given that Texas has had top 10 recruiting classes from 2008 to 2012 (according to ESPN), why are the Longhorns not performing better?





NCAA Production Rank

Season Wins Losses
Total Offense Defense
SOS
2008 12 1
5 6 30
51.69
2009 13 1
5 6 11
57.07
2010 5 7
70 87 33
63.00
2011 8 5
46 65 27
60.69
2012 9 4
53 37 64
54.54

Tuesday, September 10, 2013

2013 NCAA FBS Top 25 Ranking for Week 2

Each week during the season I plan to rank the top 25 NCAA FBS teams using my Complex Invasion College Football Production Model.  Now that we have two weeks of data, the model does a fairly good job of estimating "offensive production" and "defensive production", so I have decided to post the first of the top 25 ranks for this past week.  I had a lot of changes to make (teams switching conferences - and how that was coded in the data along with the addition of Georgia State).  I am still working on the strength of schedule stuff as the source that I used in the past is no longer reporting the data, so I will either have to find another source or start entering it myself.

In the future I plan on having the top 25 done on Monday morning, with a small delay for this week.  So, without any more delay - here is the Top 25 for this past weekend.
FYI:  2013 NCAA FBS Top 25 for Week 3

Rank Team
1 Baylor
2 Oregon
3 Maryland
4 Wisconsin
5 Houston
6 Georgia Tech
7 Louisville
8 Marshall
9 UCF
10 Duke
11 Tennessee
12 Florida State
13 Arizona State
14 Utah
15 Michigan
16 Wyoming
17 LSU
18 Ohio State
19 Texas Tech
20 Boston College
21 Texas A&M
22 Colorado
23 Michigan State
24 Texas State
25 Arizona

Tuesday, September 3, 2013

Olympic Wrestling Trials and Economic Impact

Sports economists have been notorious for their consensus on the limited impact that sporting events have on local economies.  Studies from all types of sporting events (Super Bowl, World Cup, etc.) tend to find little to no economic gains from these events (opens up in a .pdf file).  So recently the Daily Iowan reports that Iowa City hopes to repeat the economic boom from recently hosting the Olympic wrestling trials in April of 2012.  That got me to thinking about sporting events and economic impact and is Iowa City special?  So what I decided to do was to look at hotel/motel sales tax revenues up to and during this time period and see if there was some uptick in tax revenue to support the hypothesis. So I grabbed the Iowa Hotel and Motel Tax Summary by fiscal year and broken down by quarter from the 2009, 2010, 2011 and 2012 fiscal years - which covers the Olympic wrestling trials time period.  I then calculated the change in hotel/motel tax from the previous quarter in the third column.  The nominal (not-seasonally adjusted) data is below.

Time
Hotel Tax
Change
Sep-08
$67,418
-----
Dec-08
$53,756
-----
Mar-09
$51,041
-----
Jun-09
$52,528
-----
Sep-09
$59,684
($7,734)
Dec-09
$34,466
($19,290)
Mar-10
$43,241
($7,800)
Jun-10
$51,075
($1,453)
Sep-10
$56,922
($2,762)
Dec-10
$42,011
$7,545
Mar-11
$48,458
$5,217
Jun-11
$64,880
$13,805
Sep-11
$69,035
$12,113
Dec-11
$49,425
$7,414
Mar-12
$52,339
$3,881
Jun-12
$65,518
$638


As you can see there is not much change from second quarter of 2011 and the second quarter of 2012 in terms of tax revenues.  Given that Johnson County (where both Iowa City and Coralville are located) has kept the same hotel/motel tax rate (7%) during the entire time period, it does not look like there is much economic impact of the Olympic wrestling trials (even if all the gains were due to the trials as opposed to hotel and motel attendance for parents of University of Iowa graduates during this time).