Fremeau Efficiency numbers are out, Michigan ends regular season at #32.

Fremeau Efficiency numbers are out, Michigan ends regular season at #32.

Submitted by Yeoman on December 3rd, 2013 at 12:38 PM

It's been a season with more than its share of end-of-game dice rolls, and instead of arguing about which wins could or should have been losses and which losses could or should have been wins I thought it might be worth turning to the finer-grained drive-by-drive analysis by the smart folks at Football Outsiders.

The new FEI numbers are out: Michigan is #26 on defense, #38 on offense, #32 overall.

That is not a typo; I did not mistake an 8 for a 3. Michigan finished the regular season #38 in offensive FEI and the offense on the whole was only marginally worse than the defense. In fact the relative positions of the offense and defense weren't much different than 2012; both were down from last year by about the same amount. (In the index itself, not in the ranking.)

Something curious I noticed for the first time today: on a drive-by-drive basis Michigan's defense was #26, but on a play-by-play basis they were #48. I wonder if that's related to Mattison's emphasis this year on "keeping the ball in front and inside", not giving up big plays and forcing the offense to grind out a drive? They get a lot of successful plays, but things go wrong before they get to the endzone? There's probably a diary here if I ever find the time to look at it.

Some historical context might be useful. The database only goes back to 2007, unfortunately--I'd really like to have some Carr seasons that weren't marred so badly by key injuries. But here's how the seven Michigan seasons in the database stack up. Note that in the overall and offensive FEIs positive numbers are good, but on defense negative numbers are good. In all three metrics, zero is the FBS mean.

Overall:

Season

FEI

FBS rank

B1G rank

2011

.202

9

2

2007

.141

22

2

2012

.133

26

5

2013

.118

32

5

2009

.007

59

9

2010

.005

55

6

2008

-.036

70

9

 

Offense:

Season

oFEI

FBS rank

B1G rank

2010

.652

2

1

2011

.472

9

2

2012

.267

25

3

2013

.237

38

4

2007

.001

56

7

2009

-.027

66

8

2008

-.167

81

9

 

Defense:

Season

dFEI

FBS rank

B1G rank

2007

-.477

11

1

2011

-.414

16

2

2012

-.338

26

5

2013

-.299

26

4

2008

-.111

44

6

2009

-.005

60

8

2010

.419

109

11

 

Would anyone have gueesed that the '09 defense would grade out better than the offense?

I suspect we're going to see some bashing of Fremeau's method in the comments. I hope it's well-informed; I'd love to know more about how he calculates these.

 

Offensive Line Experience: Short Ride in a Broken-Down Machine

Offensive Line Experience: Short Ride in a Broken-Down Machine

Submitted by Yeoman on November 16th, 2013 at 1:56 PM

[Ed: BUMP]

A moment comes when you first start listening to minimalist music—for some people it comes quickly, for some people it never clicks at all—when your perception of time changes. As a musician famously described his first exposure to a Philip Glass opera; his initial boredom was transformed as...

I began to perceive...a whole world where change happens so slowly and carefully that each new harmony or rhythmic addition or subtraction seemed monumental...

...he said as the rhythmic woodblock...no, it's Adams not Glass...the woodblock crack of the pulling Stanford guard's pads as he thumped the Oregon SAM out of the hole play after play after play after...

NO! I will NOT spend my Thursday evening in an altered state of consciousness. So I started using the media timeouts, and then the time between plays (well, at least when Stanford had the ball, which thankfully was just about always) to work on a project I'd started a few days earlier during the Gameboy diaries, pulling participation reports for all 125 FBS teams and pulling roster/bio information to get the classes of their starters on the o-line.

And some of you people think huddles serve no purpose.

Honestly, the Horse Wasn't Dead When I Started

The results are here, usefully tabled in a spreadsheet to save some work for the next sap that starts on one of these projects.

Of course, as I sat down at my computer to do some regression analysis on the data I opened the blog and saw Gandalf's diary covering most of what I was planning to do (and doing a better job of it I might add). But I was taking a slightly different tack and found a couple of wrinkles, so for the sake of the eight of you that are still interested I'll continue on....

First a couple of comments about the dataset (feel free to skip the rest of this section, but it might be important if anyone uses the data for further analysis). Gandalf took his data from depth charts at the ourlads.com scouting site; mine come from the starting lineup listed in each school's participation report in the official game stats for their most recent game against FBS competition (sometimes coaches play with their lineup for games they're treating as exhibitions, give a start to a loyal walk-on for example, so if the most recent game was against a Delaware State I pulled the lineup for the week prior).

The official reports have the virtue, or defect, of being precise accounts of who was on the field. Sometimes that was a problem because everyone doesn't actually use five offensive linemen all the time. Idaho started a game with four, presumably spreading the field with covered, ineligible tight ends and wide receivers. Somebody else came out heavy and listed six. There were also some schools that simply listed their linemen as “OL” without assigning specific positions.

Where possible I straightened those situations out by using the schools' published depth charts. When that didn't work either I looked at third-party depth charts and did my best to reconcile them with the actual starters. It's possible there are a couple of players out of position here, but I don't think it's material.

For teams, usually pistol teams, that flop their line, I assumed the tight end would line up to the right and assigned the quick tackle and guard to the left side and the strong tackle and guard to the right.

For obvious reasons, service academies don't redshirt players. If an academy lineman's bio showed a year in which he didn't see game action, I counted that year as a redshirt and subtracted the year from his class. The point after all was to look at experience, not remaining eligibility.

Additive and Multiplicative Measures of Experience

 

My starting point was two proposals in the Gameboy diaries. Gameboy himself proposed assigning a value to each player (one point for each year, half a point for a redshirt) and adding them (well, averaging them, which of course is the same thing but for scale). That average appears in the spreadsheet as the GLEM (Gameboy Line Experience Metric).

In a comment to one of the diaries reshp1 suggested an alternative: assigning a value to each player based on experience (conceived as the probability that the player in question will successfully carry out his assignment) and multiplying those values and subtracting the product from one to get the probability that an assignment will be busted on a given play. That probability appears in the spreadsheet as the RBI (Reshp Bust Index). It's basically the weakest-link theory with the additional recognition that anyone might turn out to be the weakest link on a given play.

I focused on the latter metric because conceptually it makes sense to me and because it wasn't treated in Gandalf's diary. Reshp1 pulled the probabilities out of the air, or his hat, or somewhere, but the analysis doesn't seem to be sensitive to the particular choices here. The values are in a lookup table on page 2 of the spreadsheet if anyone wants to play around with alternatives.

Before I go on, a sanity check on Reshp1's metric—a list of the ten youngest lines:

  • UCLA (7-2, 4-2)
  • Idaho (1-9)
  • California (1-9, 0-7)
  • Wake Forest (4-6, 2-5)
  • Eastern Michigan (2-8, 1-5)
  • Western Kentucky (6-4, 2-3)
  • Tulane (6-4, 4-2)
  • Maryland (5-4, 1-4)
  • Arkansas (3-7, 0-6)
  • Michigan (6-3, 2-3)

Not a list you want to be on; those are some bad teams right there, combining for a 16-37 record in their respective conferences and that's flattering because it leaves out independent Idaho, who's probably the worst of the lot. (You can point to UCLA if you like as proof that, if everything goes right, you can survive starting multiple freshmen. Arkansas fans are probably pointing to Michigan and saying the same thing.)

The Running Game

 

Sanity check #2 is to redo Gandalf's work, but with Reshp's metric. Here's a graph of yards per carry vs. RBI:

chart 1

That looks familiar. R2 is .058; the correlation coefficient is -.24 (these coefficients will all be negative because RBI is smaller for more experienced lines). And if we strip out the tackles and just look at the interior?

chart 2

R2 is .084, the correlation coefficient is -.29, and it's not a coincidence that this looks an awful lot like Gandalf's chart using “youngest interior lineman”.

Weakest link, check. Experience matters more on the interior than at the tackles, check.

Offensive Efficiency

 

But what I really wanted to do was to look at the impact of o-line experience on an offense as a whole. To do that I've used the offensive component of the Fremeau Efficiency Index, which looks at all offensive drives (except for clock-kills and garbage-time drives) and compares the results to expectations based on the starting field position. By its nature it's pace-adjusted and independent of the effect of the team's defense; they also apply a strength of schedule adjustment.

Here's the chart:

chart 3

R2 is .026, the correlation coefficient is –.16. The effect’s not as large, but a young line impacts the whole offense, not just the run game.

It made some sense that in the running game experience would matter more in the interior than at the tackles since it's an interior lineman that makes the line calls and the assignments tend to be more complicated inside. It wasn't so clear that this would still hold when the passing game was added in:

chart 4

but that's what we find. The correlation is greater when we only look at the interior. R2 is .048, the correlation coefficient is -.22.

It's on the interior that experience really matters. And Michigan's interior RBI ranks 123rd of 125 FBS teams.

How Large an Effect?

 

A lot was made in Gandalf's diary, and especially in the comments, about the low R2 values here, which were seen as a demonstration of the relative unimportance of experience vs. other factors, like coaching.

I see it differently. This is an extremely diverse universe of teams we're looking at here. There are differences between Michigan and Eastern, or between Ohio State and Ohio U., that can't ever be overcome by something as simple as inexperience on the line. A lot of the scatter in these charts is just a matter of big programs being big and small programs being small. Given those enormous differences in baseline levels of the various FBS teams it's amazing to me that we could see anything like 5-8% of a performance difference being credited to any one team demographic, especially when the difference is measured using an SOS-adjusted metric like Fremeau.

And the slopes of these trend lines aren't small. The expected oFEI difference between 2012 Michigan and 2013 Michigan is .32; the actual difference is .197. The expectation, just correcting last year's performance for the youth on the field this year, was for a worse offense than we've actually seen.

Put another way, if you use that trend line to adjust for this year's lack of experience, add the missing .32, Michigan's offense goes to 19th in the nation, right behind Stanford and Louisville. UCLA turns into Oregon. Eastern becomes Bowling Green and maybe English keeps his job. Everybody's happy.

 

Good Teams are All Alike, Every Bad Team is Bad in its Own Way

 

I thought I'd try to get a handle on that by comparing each team's performance to the baseline they've established historically. I've averaged the oFEI's for each program for the five-year period from 2008-2012, then calculated the deviation of this year's performance from that average.

Basically, we're now looking at year-to-year deviations in performance within each program.

On the one hand, this gets rid of the scatter due to the vast discrepancy in baseline performance expectations from the top to the bottom of the division.

On the other hand, this also filters out any effect from programs like Wisconsin whose strength largely comes from the fact that they always field powerful, experienced lines. There's not much year-to-year variance there—they're always old, always good.

So it's possible we won't see any bigger correlation here than before...

chart 5

...what happened? R2 is .009. Two-thirds of the effect is now gone. (A result, by the way, that's consistent no matter what metrics I use for line experience.) Apparently, only a third of the effect we’re looking at is a matter of one-off bad seasons due to a young line; most of the effect is systematic, inherent in particular programs. It's almost as if there were a correlation between poor past performance and current youth, and that's because there is:

chart 6

There's the missing two-thirds. Historically (well, over the last five years anyway) bad teams are on the left, good programs on the right. There's less current youth (lower Bust Index) as you move right.

A look back at the teams listed earlier provides a clue. It's a mix of historically bad programs like Eastern, struggling FCS converts like Idaho, and programs that have suffered some sort of recent calamity, the kind that makes you decide to hire John L. Smith to be your substitute teacher for a year. Some had horrible recruiting, some had retention problems…each one has had its peculiar issues but every one of them is a program in disarray—some recovering, some not. Teams don’t field multiple freshmen because they want to; they do it because things fell apart.

We'll know more if someone does the study suggested in the comments to Gandalf's diary, looking at overall roster depth instead of just the age of the starters, but I think what's happening here is that the Wisconsin effect is the dominant effect in the study. Good programs don't suffer from youth on their lines because (a) it doesn't happen to them and (b) when it does, it's not a sign of weakness. When Andrus Peat finds his way to the top of the depth chart as a sophomore it's because he's beaten out multiple upperclassmen and won the position. When Kyle Bosch find his way to the top of the depth chart it's by default; the juniors and seniors he's supposed to be competing against aren't on the roster.

I think the next thing I might try, if I were of a mind to keep flogging this, is to do something so straightforward and blunt as to look for a correlation between offensive efficiency and the number of scholarship upperclass o-linemen on a roster (more telling than the percentage, I would guess).

Week #11 Statistics and FEI Prediction for Iowa

Week #11 Statistics and FEI Prediction for Iowa

Submitted by Enjoy Life on November 14th, 2012 at 1:14 PM

Prediction for Iowa: The FEI Forecast for this Saturday is Michigan 28 – Iowa 16 with a 78% Probable Win Expectation for Michigan. Michigan's offense continues to be excellent (4.81 PPPo) against poor teams (AFA, UMass, Purdue, Illinois, Minnesota, Northwestern) but has struggled (0.90 PPPo) against every good team (Alabama, ND, MSU, Nebraska). Iowa is ranked #88 in OFEI and #30 in DFEI. Looks like FEI has it just about right this week.

Strength of Schedule: Michigan's SoS for Out of Conference games is much harder than the B1G games. This is quite unusual and because of the OOC Strength of Schedule, M is actually doing better in B1G games versus OOC for both offense (2.7 vs. 2.5 PPPo) and defense (1.3 vs. 2.0 PPPo). The defense had their worst game (2.8 PPPo) since Alabama.

imageFremeau Efficiency Index: Michigan improved in both overall and offense FEI with defense basically unchanged. In the detailed chart below, GE represents the raw data for FEI before adjustments for opponents.

The S&P Ratings (Also from Football Outsiders) is a play based analysis (rather than possession based) and M is ranked #19 overall, #18 in offense, and #27 in defense. The S&P ratings DO include games against non-FBS opponents (go figure).

The FEI is a drive based analysis considering each of the nearly 20,000 drives each year in FBS vs. FBS college football. The data is filtered to eliminate garbage time (at the half or end of game) and is adjusted for opponent. A team is rewarded for playing well against good teams (win or lose) and is punished more severely for playing poorly against bad teams than it is rewarded for playing well against bad teams.

imageNational Rankings: The rankings for offense and defense are based on scoring (yardage statistics are inherently flawed). These are simply raw numbers without any adjustments for opponent, garbage time, or anything else. The data is from TeamRankings and includes only games between two FBS teams.

FEI Details: Here are the FEI numbers for Michigan and their opponent ( Football Outsiders FEI ).

imageimage_thumb15_thumb1_thumb_thumb

imageimagePoints Per Possession: Cumulative PPPo is 2.6 for the offense and 1.6 for the defense. M finished 2011 outscoring opponents by almost a 2:1 margin with PPPo for offense of 2.8 and defense of 1.4. The 2 charts show the raw data for offense and defense with the number of possessions adjusted for "kneel downs" at the half or end-of-game (maximum deduction = 2).

Using Scoring Offense and Scoring Defense National Rankings for the past 5 years (FBS AQ teams only), this table shows the percentage of teams that finish the season with a +WLM and a +5 WLM. For example, teams that finished in the Top 40 in both offense and defense had a 100% chance to be +WLM and an 82% chance to be +5 WLM (9-4 or better).

image_thumb34_thumb

Week #10 Statistics and FEI Prediction for Northwestern

Week #10 Statistics and FEI Prediction for Northwestern

Submitted by Enjoy Life on November 6th, 2012 at 11:47 AM

Prediction for Northwestern: The FEI Forecast for this Saturday is Northwestern 22 – Michigan 21 with a 52% Probable Win Expectation for Northwestern. Another toss up game? NSFMF! FEI is wrong yet again and M wins this one 31 —13. M has the #3 ranked Strength of Schedule and NW is #69 in SoS. In National statistics, M & NW are ranked about equal in scoring offense (#50 & #53) but M is ranked #13 in scoring defense with 16.8 PPG and NW is ranked #43 allowing 24.2 PPG.

Michigan's offense continues to be excellent (4.81 PPPo) against poor teams (AFA, UMass, Purdue, Illinois, Minnesota) but has struggled (0.90 PPPo) against every good team (Alabama, ND, MSU, Nebraska). Northwestern would be classified as a poor defensive team.

imageFremeau Efficiency Index: Not much movement in the FEI. In the detailed chart below, GE represents the raw data for FEI before adjustments for opponents. M is ranked #28 in GE and overall FEI is #34. This seems about right since M has lost 3 of the 4 games to their highly ranked opponents.

The S&P Ratings (Also from Football Outsiders) is a play based analysis (rather than possession based) and M is ranked #20 overall, #19 in offense, and #20 in defense. The S&P ratings DO include games against non-FBS opponents (go figure).

The FEI is a drive based analysis considering each of the nearly 20,000 drives each year in FBS vs. FBS college football. The data is filtered to eliminate garbage time (at the half or end of game) and is adjusted for opponent. A team is rewarded for playing well against good teams (win or lose) and is punished more severely for playing poorly against bad teams than it is rewarded for playing well against bad teams.

imageNational Rankings: The rankings for offense and defense are based on scoring (yardage statistics are inherently flawed). These are simply raw numbers without any adjustments for opponent, garbage time, or anything else. The data is from TeamRankings and includes only games between two FBS teams.

FEI Details: Here are the FEI numbers for Michigan and their opponent ( Football Outsiders FEI ).

imageimage_thumb15_thumb1_thumb

imageimagePoints Per Possession: Cumulative PPPo is 2.5 for the offense and 1.5 for the defense. M finished 2011 outscoring opponents by almost a 2:1 margin with PPPo for offense of 2.8 and defense of 1.4. The 2 charts show the raw data for offense and defense with the number of possessions adjusted for "kneel downs" at the half or end-of-game (maximum deduction = 2).

Using Scoring Offense and Scoring Defense National Rankings for the past 5 years (FBS AQ teams only), this table shows the percentage of teams that finish the season with a +WLM and a +5 WLM. For example, teams that finished in the Top 40 in both offense and defense had a 100% chance to be +WLM and an 82% chance to be +5 WLM (9-4 or better).

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Week #9 Statistics and FEI Prediction for Minnesota

Week #9 Statistics and FEI Prediction for Minnesota

Submitted by Enjoy Life on October 31st, 2012 at 2:46 PM

Prediction for Minnesota: The FEI Forecast for this Saturday is Michigan 24 – Minnesota 19 with just a 61% Probable Win Expectation for Michigan. If Denard is able to play most of the game, I don't think it will be that close. Michigan's offense has been excellent (3.8 PPPo) against poor teams (AFA, UMass, Purdue, Illinois) but has really struggled (0.90 PPPo) against every good team (Alabama, ND, MSU, Nebraska). In 2011 this was not the case as M scored about the same versus poor teams (3.7 PPPo) but was much better (2.2 PPPo) against good teams  (ND, MSU, Nebraska, and Iowa). That said, Minnesota would be classified as a poor team (sorry Goldie).

imageFremeau Efficiency Index: Not much movement in the overall FEI or DFEI but the OFEI went from #40 to #56 (no surprise there). In the detailed chart below, GE represents the raw data for FEI before adjustments for opponents. M is ranked #34 in GE and overall FEI is #36. This seems about right since M has lost 3 of the 4 games to their highly ranked opponents.

The S&P Ratings (Also from Football Outsiders) is a play based analysis (rather than possession based) and M is ranked #12 overall, #16 in offense, and #16 in defense.

The FEI is a drive based analysis considering each of the nearly 20,000 drives each year in FBS college football. The data is filtered to eliminate garbage time (at the half or end of game) and is adjusted for opponent. A team is rewarded for playing well against good teams (win or lose) and is punished more severely for playing poorly against bad teams than it is rewarded for playing well against bad teams.

imageNational Rankings: The rankings for offense and defense are based on scoring (yardage statistics are inherently flawed). These are simply raw numbers without any adjustments for opponent, garbage time, or anything else. The data is from TeamRankings and includes only games between two FBS teams.

FEI Details: Here are the FEI numbers for Michigan and their opponent ( Football Outsiders FEI ).

imageimage_thumb15_thumb1

imageimagePoints Per Possession: The offense has now struggled against ALL the good opponents. The TOs in the Nebraska game put the D at a significant disadvantage and the stats reflect that.

Cumulative PPPo is 2.4 for the offense and 1.5 for the defense. M finished 2011 outscoring opponents by almost a 2:1 margin with PPPo for offense of 2.9 and defense of 1.5. The 2 charts show the raw data for offense and defense with the number of possessions adjusted for "kneel downs" at the half or end-of-game (maximum deduction = 2).

Using Scoring Offense and Scoring Defense National Rankings for the past 5 years (FBS AQ teams only), this table shows the percentage of teams that finish the season with a +WLM and a +5 WLM. For example, teams that finished in the Top 40 in both offense and defense had a 100% chance to be +WLM and an 82% chance to be +5 WLM (9-4 or better).

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Week #8 Statistics and FEI Prediction for Nebraska

Week #8 Statistics and FEI Prediction for Nebraska

Submitted by Enjoy Life on October 25th, 2012 at 10:22 AM

Prediction for MSU: The FEI Forecast for this Saturday is Nebraska 27  – Michigan 24 with a 57% Probable Win Expectation for Nebraska. This difference is entirely the home field advantage. Basically a toss up and, like the Purdue and MSU games, FEI is wrong and Michigan wins the game 31 – 10. For whatever reason, FEI remains unimpressed with the Wolverines. As you can see  below, M is ranked better than Nebraska in every FEI category except offense.

imageFremeau Efficiency Index: Even though it was a low scoring and close victory, FEI rewarded Michigan and moved M from #47 to #36 because MSU is still ranked very high by FEI (#29 if you can believe that!). The S&P Ratings (Also from Football Outsiders) is a play based analysis (rather than possession based) and M is ranked #11 overall, #5 in offense, and #29 in defense.

The FEI is a drive based analysis considering each of the nearly 20,000 drives each year in FBS college football. The data is filtered to eliminate garbage time (at the half or end of game) and is adjusted for opponent. A team is rewarded for playing well against good teams (win or lose) and is punished more severely for playing poorly against bad teams than it is rewarded for playing well against bad teams.

imageNational Rankings: The rankings for offense and defense are based on scoring (yardage statistics are inherently flawed). These are simply raw numbers without any adjustments for opponent, garbage time, or anything else. The data is from TeamRankings and includes only games between two FBS teams.

FEI Details: Here are the FEI numbers for Michigan and their opponent ( Football Outsiders FEI ).

imageimage_thumb15

imageimagePoints Per Possession: The defense continues to excel. After those first two games, M is allowing just 9.8 points per game (13, 13, 13, 0, and 10).

Cumulative PPPo is 2.7 for the offense and 1.4 for the defense. M finished 2011 outscoring opponents by almost a 2:1 margin with PPPo for offense of 2.8 and defense of 1.4. The 2 charts show the raw data for offense and defense with the number of possessions adjusted for "kneel downs" at the half or end-of-game (maximum deduction = 2).

Using Scoring Offense and Scoring Defense National Rankings for the past 5 years (FBS AQ teams only), this table shows the percentage of teams that finish the season with a +WLM and a +5 WLM. For example, teams that finished in the Top 40 in both offense and defense had a 100% chance to be +WLM and an 82% chance to be +5 WLM (9-4 or better).

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Week #7 Statistics and FEI Prediction for MSU

Week #7 Statistics and FEI Prediction for MSU

Submitted by Enjoy Life on October 17th, 2012 at 5:24 PM

Prediction for MSU: The FEI Forecast for this Saturday is Michigan State 20 – Michigan 18 with a 56% Probable Win Expectation for Sparty? Basically a toss up but, like the Purdue game, FEI is wrong and Michigan wins the game 24 – 13. As you can see below, FEI has been really schizophrenic about M this year. M at #47 is the lowest ranked 4 win AQ team in FEI and MSU at #27 is the highest ranked 3 loss team in FEI.

imageFremeau Efficiency Index: Week #7 is significant because all remnants of preseason projected data is removed from the formulas and all data represents 2012 games only. In addition both offense and defense efficiency are now opponent-adjusted and are referenced as OFEI and DFEI (up until this point OE and DE were just raw numbers).

That said, WTF!!!

After a 45-0 drubbing of an admittedly weak Illinois team, FEI blasted the overall rating to #47 (from #24 last week) and pummeled the offense efficiency to #63 (from #40 last week). Defense efficiency improved to #27 (from #33 last week).

The S&P Ratings (Also from Football Outsiders) is a play based analysis (rather than possession based) and M is ranked #9 overall, #7 in offense, and #22 in defense.

The FEI is a drive based analysis considering each of the nearly 20,000 drives each year in FBS college football. The data is filtered to eliminate garbage time (at the half or end of game) and is adjusted for opponent. A team is rewarded for playing well against good teams (win or lose) and is punished more severely for playing poorly against bad teams than it is rewarded for playing well against bad teams.

imageNational Rankings: The rankings for Week #7 offense and defense are based on scoring (yardage statistics are inherently flawed). These are simply raw numbers without any adjustments for opponent, garbage time, or anything else. The data is from TeamRankings and includes only games between two FBS teams.

FEI Details: Here are the FEI numbers for Michigan and their opponent ( Football Outsiders FEI ).

imageimage

Points Per Possession: The offense continued to rack up the points and the defense recorded their first shutout. Cumulative PPPo is 2.9 for the offense and 1.5 for the defense. M finished 2011 outscoring opponents by almost a 2:1 margin with PPPo for offense of 2.8 and defense of 1.4. The 2 charts show the raw data for offense and defense with the number of possessions adjusted for "kneel downs" at the half or end-of-game (maximum deduction = 2).imageimage

Using Scoring Offense and Scoring Defense National Rankings for the past 5 years (FBS AQ teams only), this table shows the percentage of teams that finish the season with a +WLM and a +5 WLM. For example, teams that finished in the Top 40 in both offense and defense had a 100% chance to be +WLM and an 82% chance to be +5 WLM (9-4 or better).

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Week #6 Statistics and FEI Prediction for Illinois

Week #6 Statistics and FEI Prediction for Illinois

Submitted by Enjoy Life on October 9th, 2012 at 1:06 PM

image

Prediction for Illinois: The FEI Forecast for this Saturday is Michigan 34 – Illinois 6 with a 97% Probable Win Expectation for Michigan. This game is a complete mismatch in every category.

Fremeau Efficiency Index: After a large improvement for Michigan during the bye week, the overall FEI barely moved after the Purdue game. The offense efficiency also was basically unchanged while the defense efficiency improved significantly (from #48 to #33).

The FEI is a drive based analysis considering each of the nearly 20,000 drives each year in FBS college football. The data is filtered to eliminate garbage time (at the half or end of game) and is adjusted for opponent. A team is rewarded for playing well against good teams (win or lose) and is punished more severely for playing poorly against bad teams than it is rewarded for playing well against bad teams.

imageNational Rankings: The rankings for Week #6 offense and defense are based on scoring (yardage statistics are inherently flawed). These are simply raw numbers without any adjustments for opponent, garbage time, or anything else. The data is from TeamRankings and includes only games between two FBS teams.

image

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FEI Details: Here are the FEI numbers for Michigan and their opponent ( Football Outsiders FEI ).

imageimagePoints Per Possession: The offense had their second best performance of the year and the defense had their best performance of the year.

The 2 charts show the raw data for offense and defense with the number of possessions adjusted for "kneel downs" at the half or end-of-game (maximum deduction = 2).

Using Scoring Offense and Scoring Defense National Rankings for the past 5 years (FBS AQ teams only), this table shows the percentage of teams that finish the season with a +WLM and a +5 WLM. For example, teams that finished in the Top 40 in both offense and defense had a 100% chance to be +WLM and an 82% chance to be +5 WLM (9-4 or better).

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Week #5 Statistics and FEI Prediction for Purdue

Week #5 Statistics and FEI Prediction for Purdue

Submitted by Enjoy Life on October 2nd, 2012 at 1:45 PM

image

What The What?: The FEI computers were apparently very impressed with Ms bye week as we improved to a ranking of #23 (from #42 last week) and FBS mean wins jumped to 7.5 (it was just 5.8 last week)!? This appears to be the result of adjustments being made due to strength of schedule (SoS). Michigan's SoS is now #4.

Prediction for Purdue: The FEI Forecast for this Saturday is Purdue 24 – Michigan 16 with a 71% Probable Win Expectation for Purdue. FEI is wrong this week and Michigan lets Denard be Denard: Michigan 35 – Purdue 17.

Purdue is ranked #15 in the FEI and has a strength of schedule (SoS) of #43. As you can see from the detailed FEI chart below, M is ranked 39 positions better for SoS, 21 positions better for offense, and 4 positions better for defense versus Purdue. Purdue has beaten an FCS team (Eastern Kentucky), Eastern Michigan (#92 FEI), and Marshall (#87 FEI). M's tougher schedule is what makes the difference in this game.

Fremeau Efficiency Index: The FEI is a drive based analysis considering each of the nearly 20,000 drives each year in FBS college football. The data is filtered to eliminate garbage time (at the half or end of game) and is adjusted for opponent. A team is rewarded for playing well against good teams (win or lose) and is punished more severely for playing poorly against bad teams than it is rewarded for playing well against bad teams.

imageNational Rankings: The rankings for offense and defense are based on scoring (yardage statistics are inherently flawed). These are simply raw numbers without any adjustments for opponent, garbage time, or anything else. The data is from TeamRankings and includes only games between two FBS teams.

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FEI Details: Here are the FEI numbers for Michigan ( Football Outsiders FEI ). imageimagePoints Per Possession: The 2 charts show the raw data for offense and defense with the number of possessions adjusted for "kneel downs" at the half or end-of-game (maximum deduction = 2). The charts both indicate significant improvement in each subsequent game. Of course, this may be due in great measure to the fact that the opponent has been weaker in each subsequent game.

Using Scoring Offense and Scoring Defense National Rankings for the past 5 years (FBS AQ teams only), this table shows the percentage of teams that finish the season with a +WLM and a +5 WLM. For example, teams that finished in the Top 40 in both offense and defense had a 100% chance to be +WLM and an 82% chance to be +5 WLM (9-4 or better).

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Week #4 Statistics (Bye Week – No FEI Prediction)

Week #4 Statistics (Bye Week – No FEI Prediction)

Submitted by Enjoy Life on September 27th, 2012 at 1:47 PM

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Note: I've added the FEI rankings for offense and defense – these are currently  NOT adjusted and FEI waits until week #7 to have enough data to make adjustments to OE and DE.

Synopsis: The folks at FEI are predicting just a 6-6 season for Michigan (the same as last week before the loss to ND). However, this is not quite as bad as you might suspect because early in the season, FEI has universally pessimistic predictions. At the beginning of the year, FEI predicted ZERO teams to go undefeated and ZERO teams to have just one loss! Currently, FEI is still predicting that ZERO FBS teams will go undefeated. Only 2 FBS teams are predicted to have one loss (Florida State & Alabama). All others are predicted to have at least 2 losses.

Alabama (ranked #2 in FEI) is playing only 11 FBS games this year and FEI is predicting a 10.3 FBS win season. Florida State (ranked #1 in FEI) plays just 10 FBS games and is predicted by FEI to win 8.9 FBS.

Michigan is ranked #42 in the FEI. This is an improvement from last week even though we lost the game. This should not be entirely unexpected because the basic purpose of any ranking system is to better reflect the relative strength of a team by making adjustments to the raw win/loss data. In the FEI, the GE (Game Efficiency) represents the raw data before adjustments. M is ranked #60 for GE and after adjustments is ranked #42 for FEI.

Last year after Week#4, M was ranked #10 in the FEI with 10.3 predicted wins.

Fremeau Efficiency Index: The FEI is a drive based analysis considering each of the nearly 20,000 drives each year in FBS college football. The data is filtered to eliminate garbage time (at the half or end of game) and is adjusted for opponent. A team is rewarded for playing well against good teams (win or lose) and is punished more severely for playing poorly against bad teams than it is rewarded for playing well against bad teams. (This is why M was ranked relatively high after that loss to Alabama, actually fell 13 places after the blowout of UMass, and improved 4 places after a loss to ND.)

imageNational Rankings: The rankings for offense and defense are based on scoring (yardage statistics are inherently flawed). These are simply raw numbers without any adjustments for opponent, garbage time, or anything else. The data is from TeamRankings and includes only games between two FBS teams.

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FEI Details: Here are the FEI numbers for Michigan ( Football Outsiders FEI ). FEI is predicting a 6-6 season for the Wolverines (FBS Mean Wins = 6.0). Like most predictive tools, the FEI is less reliable at the beginning of the year because there is so little data.

imageimagePoints Per Possession: The defense played very well and allowed just 1.3 PPP. The offense also played well but the TOs just were too much to overcome. M lost almost 14 points due to their TOs. The overall average for offense points per possession is 2.5 and for defense points per possession is 2.0. The 2 charts show the raw data for offense and defense with the number of possessions adjusted for "kneel downs" at the half or end-of-game (maximum deduction = 2).

Using Scoring Offense and Scoring Defense National Rankings for the past 5 years (FBS AQ teams only), this table shows the percentage of teams that finish the season with a +WLM and a +5 WLM. For example, teams that finished in the Top 40 in both offense and defense had a 100% chance to be +WLM and an 82% chance to be +5 WLM (9-4 or better).

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