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

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.

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

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.

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

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.

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).

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.

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.

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

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.

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

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

2013 MLB Payroll and Hits Graph

The New York Times has a nice graph of MLB payroll and hits by the top 10 players.  Notice that the Yankees are an outlier (far away from the rest of the league in terms of payroll).

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).