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Oh, I absolutely agree that

Oh, I absolutely agree that the secondary is quite bad, and I grant that the UFR is inexact.  However, Misopogon's two benchmarks for the star ratings were a UFR-equivalent (which I was speaking too), and qualitative adjectives like "all Big Ten".  The player analogues are probably the most useful in terms of benchmarking a player's ability, though I must admit my familiarity with historical players isn't good enough to assess their validity.

I guess the issue I was grappling with is that we have not just one weak player, but several, and the UFR statistic seemed the best way to think about how all the players might fit together.  We all know that the d-line has been pretty good, the linebackers have been up and down, and the defensive backs have been pretty terrible.  My point was not to dispute that, or to trash Misopogon's ratings (which I quite enjoyed reading) - I just wanted to suggest that the defensive backs are bad but not "commit a huge blunder every three or four plays" bad.

Misopogon's Ratings

I think this is an interesting exercise, and I want to thank Misopogon for putting in the time to think through this.  However, it seems that his ratings are too pessimistic (especially in the secondary), given the UFR-equivalent definition he chose for each star and Brian's defensive UFRs.

As a rough approximation I assumed an 80-20 playing time split between starters and backups, and I counted Ezeh as the starter.  Using a 70-30 or 60-40 split wouldn't change things much.  Based on the definition of -2 for a one star to +2 for a five star every four plays, we should expect the following totals for each unit:

DL: +0.8 per four plays

LB: -1.6 per four plays

DB: -5.4 per four plays.

Total: -6.2 per four plays

If we add up Brian's UFR ratings, we get the following:

  DL LB DB Overall
U Conn 14 3 7 24
ND 13 21 -11 23
U Mass 29.5 -14.5 -8 7
BGSU 10 16 2 28
Indiana 32 3 -20.5 14.5
MSU 8 8.5 -9.5 7
Total 106.5 37 -40 103.5
Total 2 (Iowa = MSU) 114.5 45.5 -49.5 110.5
Total / 4 Plays 0.98 0.34 -0.37 0.95
Total 2 / 4 Plays 0.92 0.37 -0.40 0.89

Because Brian hasn't done the Iowa game yet, the first total ignores it, and the second total assumes it'll be the same as the MSU rating (imperfect, but the best I could do).  Our defense has faced 496 plays (436 if you don't count Iowa).

As you can see, our DL has performed in line with your ratings, but our LBs and DBs have done much better.  The DB rating is clearly an order of magnitude too negative.  Averaging -5.4 per four plays means that in a 60 play game they should have a total UFR of -81.... four times worse than the Chappel-bombing.

Now, we could instead ask whether the stars are fine in a relative sense, but that the pluses and minuses associated are too extreme.  I think that is part of it, but on the other hand according to Brian's UFRs the LBs have been a net positive, as has the team, and the DBs have been half as negative as the DLs have been positive.  By contrast in Misopogon's ratings the LBs are rated as negatives, and the DBs are rated as almost 7 times more negative than the DLs are positive.  Again, this suggests that the linebackers and (especially) the defensive backs aren't as bad as Misopogon's ratings would suggest.

Fremau predicts Michigan by

Fremau predicts Michigan by 8:

71.9% PWE; MICHIGAN 30, Michigan State 22

http://bcftoys.blogspot.com/2010/10/fei-forecasts-week-6-oct-5-oct-9.ht…

MSU spying Denard

I just listened to Brian's section of the podcast, and he makes an excellent point about the "Greg Jones as a spy" defense.  On a running play, the MLB is always going to have a blocker assigned to him, and is unlikely to be the read key on an option - so it's not clear that having Jones "spy" will do much of anything.  As Brian said "he'll just be playing run defense".  I think spying the QB would matter more if Denard was scrambling out of the pocket on passing plays, or if we were running lots of true QB draws where we pass block for a few seconds at the start of the play.  It also seems like Jones spying should open up the underneath coverage on play-action passes.

Really interesting, thanks!

Really interesting, thanks!

I think it'll be closer to

I think it'll be closer to 250 passing - 150 running.  I'm guessing that our run success will be more balanced between Denard and the RBs.

FO breaks down Michigan-Michigan State

I do like FO's stats, I was just making the point that S&P+ is a derived statistic based on a model of what's important, not a raw statistic.  I think both are important to look at.

 

BTW, FO breaks down the Michigan-Michigan State game here:http://footballoutsiders.com/7th-day-adventure/2010/sda-defending-home-…

  OVERALL When Michigan St.
Has the Ball...
When Michigan
Has the Ball...
Category Mich. St.
(5-0)
Michigan
(5-0)
Mich. St.
Off
Michigan
Def
Mich. St.
Def
Michigan
Off
2010 F/+ Rk 26 22        
2010 FEI Rk 31 16        
2010 S&P+ Rk 23 31 21 62 49 7
2010 Rushing S&P+ Rk     20 83 64 13
2010 Passing S&P+ Rk     28 48 43 9
2010 Std. Downs S&P+ Rk     22 103 44 1
Run-Pass Ratio
(Std. Downs)
    64.1% Run
(41st)
    73.8% Run
(10th)
2010 Pass. Downs S&P+ Rk     16 47 107 6
Run-Pass Ratio
(Pass. Downs)
    36.8% Run
(46th)
    36.7% Run
(47th)

And based on the F/+ ratings they pick Michigan (against the spread).

Recently Wisconsin has tended

Recently Wisconsin has tended to do worse than expected when initially ranked highly, and better than expected when initially ranked low.  They'll probably end up in the middle of the pack in the Big 10 this year.

Cal

OK, it looks like the Cal stats really are 504 rush yards total  - that's what Cal's official webpage has).

 

That means it should be

Michigan: was 125.8/game (#37), now is 139.4/game (#36)

Tulane: was 119.75/game (#33), now is 142.25/game (#38)

Cal: was 126/game (#38), now is 144.5/game (#41)

 

Therefore we improve by one rank instead of two.

You have to move the sack

You have to move the sack yards from rush defense to pass defense for everyone before reranking all the teams.  We move ahead two spots because two teams near us (Cal and Tulane) have more sack yards per game thank we do, so their rush defense gets worse by a larger amount than ours.

 

Specifically, we have 13.6 sack yards per game.  Cal has 18.5 and Tulane has 18.  That means for rushing defense we get...

Michigan: was 125.8/game (#38), now is 139.4/game (#36)

Tulane: was 119.75/game (#33), now is 142.25/game (#38)

Cal: was 125.5/game (#37), now is 144/game (#40)

 

BTW, I'm using stats from here: http://www.cfbstats.com/2010/leader/national/team/defense/split01/categ…

I'm not sure why there is a slight difference from the NCAA.com stats you link to.  It matters for Cal, since your link has them at 126 rush yards/game, moving them down to #38.  If we take the NCAA.com stats then the raw numbers likely won't change much but we'll only move up one rank instead of two (since we'd start one rank higher).

The Football Outsiders stats

The Football Outsiders stats are interesting, but do a lot different than just control for sacks and SoS.

If you just want to move sack yards from rush defense to pass defense I find that it makes no difference for our passing defense rank, and actually improves our rushing defense rank:

 

Pass Defense: was 307.8/game (#120), now is 294.2/game (#120)

Rush Defense: was 125.8/game (#38), now is 139.4/game (#36)

Brian Fremau talks about some

Brian Fremau talks about some of these same issues in his Football Outsiders column this week (http://footballoutsiders.com/fei-ratings/2010/fei-better-late-never).  He handles things a little differently, since he strips out "garbage time" posessions and he ignores games with FCS schools.  He only lists a couple of top 10 tables, but he lists Michigan as 9th in terms of points per possession on offense with 3.386.  Top 10 defenses allow somwhere in the 0.5 to 1.3 points per posession range, so we're letting teams score twice as often as that.  He also shows that top 10 defenses are able to make a stop for a drive that has already gone 10+ yards at least two-thirds of the time, where we're only doing it half the time (see below).

 

Overall he's got us ranked 16th with a rating of 0.142  (I don't have a good feel for the units on his metric, but the #1 team is 0.297 and the #25 team is 0.122. projects us to win on average 4.4 of our remaining games (so end with a total of 9.4 wins).  For comparison Michigan State is ranked 31st with a rating of 0.95.  He doesn't have a prediction yet (will probably come out later today), but for reference last week he had MSU at 0.73 and Wisconsin at 0.69 and gave MSU a 60% chance to win.  He had Iowa at 0.148 and Penn State at 0.102 and gave Iowa a 71% chance to win.  So I'm guessing we'll be like 65-70% favorites in his system.

Drives by number of plays

I definitely think it would be interesting to break drives down by number of plays rather than yardage -  I used yardage because that was the information bigmc6000 had in original table.  I do think the yardage breakdown is useful if you think about three groups - immediate stops, short drives and long drives.  About a third of the drives against our defense stop in 10 yards or less (i.e. one set of downs), about a third go for a while and then stop, and a third drive for 50+ yards and mostly score.  Field position certainly plays into this, but again wasn't in the data yet.

I think the other thing that you can tell from yards is that when a drive has gone a long way, we basically need a turnover to stop it.  We're not very good at just forcing a stop when the other team has already gotten deep in our half of the field.  You see that clearly in the second table, which looks cumulatively rather than by total drive yardage (so avoids the problem of categories with few observations).  The longer a drive has already gone, the more we need a turnover to stop it.

 

I would definitely be in favor of someplace where basic scraped data can be centrally located.  bigmc6000 posting the individual drives in addition to his analysis made it easy for me to add my two cents.    It would be very useful, for example, to have the basic play-by-play numbers from the UFRs in a spreadsheet.  On the other hand people like Mathlete who do a lot to transform the raw data into something else like PAN shouldn't feel like they should have to share that (though if he wants to that'd be great!).

Oops, I left in the EOH

Oops, I left in the EOH drives for the total drives, but not for stops.  Here are the corrected tables.  I also switched the Indiana EOH touchdown to be a scoring drive.

Drive Length Drives % of Drives Stops % of Stops Stops/Drives Stops w/ TO
<= 10 yards 16 27% 16 39% 100% 19%
11 to 20 yards 3 5% 3 7% 100% 33%
21 to 30 yards 12 20% 10 25% 83% 30%
31 to 40 yards 3 5% 3 7% 100% 33%
41 to 50 yards 4 7% 3 7% 75% 0%
51+ yards 20 33% 3 7% 15% 100%
Drive of at least Prob(Stop) Prob(TO) Stops w/ TO
10 yards 52% 19% 36%
20 yards 49% 18% 37%
30 yards 33% 15% 44%
40 yards 25% 13% 50%
50 yards 15% 15% 100%
Sure, go ahead.  The other

Sure, go ahead.  The other thing I was hoping to pull from the UFRs was whether on defensive stops we got other kinds of "big plays" in the last set of downs - sacks or TFLs.

Thanks for doing this - I

Thanks for doing this - I wanted to go through the UFR's to look at what our defensive stops looked like, but I can use your data to do most of what I had in mind.

I took a look at all the drives that we got stops on (other than EOH drives), breaking them down by how long the drive was.  I think this will show how much we're bending, and if we bend do we break.

Drive Length Drives % of Drives Stops % of Stops Stops/Drives Stops w/ TO
<= 10 yards 20 31% 16 42% 80% 19%
11 to 20 yards 3 5% 3 8% 100% 33%
21 to 30 yards 12 19% 10 26% 83% 30%
31 to 40 yards 3 5% 3 8% 100% 33%
41 to 50 yards 5 8% 3 8% 60% 0%
51+ yards 21 33% 3 8% 14% 100%

So, we actually get a fair number of quick stops.  However, the longer the drive is, the more dependent we are on getting a stop via a turnover (interception, fumble or missed field goal) rather than just stiffening.

Another way to look at that is to ask, given that a drive has already gone X yards, what is the probability of a stop and/or a turnover?

Drive of at least Prob(Stop) Prob(TO) Stops w/ TO
10 yards 50% 18% 36%
20 yards 46% 17% 37%
30 yards 31% 14% 44%
40 yards 23% 12% 50%
50 yards 14% 14% 100%

Not surprisingly, the longer the drive goes, the less likely we are to get a stop, and the more likely we are to need a turnover to get a stop.  With Brian now including the number of rushers in UFR it would be interesting to see whether we're more likely to blitz the longer a drive has gone in order to get a TO.

Do your stats for tackles

Do your stats for tackles include special teams tackles?  This list of tackling stats (http://www.cfbstats.com/2010/team/418/tackle/index.html) appears to, since John McColgan (the FB) is listed as the #16 tackler.

So things actually look a bit

So things actually look a bit better when I redo the analysis only for AQ conference teams.

Year End 70th or better End +15 Avg Incr
2004 12.5% 12.5% 4.6
2005 37.5% 37.5% 26.6
2006 20.0% 30.0% 6.9
2007 22.2% 44.4% 11.2
2008 40.0% 40.0% 24.4
2009 33.3% 44.4% 18.0

So, just based on historical averages, we have something like a 30% chance to improve enough to end up 70th or better in total defense, and something like a 40% chance to improve by at least 15 ranks.

I left the spreadsheet that

I left the spreadsheet that had all the data at work, so I won't be able to check until tomorrow.  I do have a list I was working on of all the teams that increased by at least 40 ranks.  Of the 16 teams that did so, 8 were from AQ conferences.

In 2009, Syracuse went from 96 to 37, and Colorado went from 101 to 57.

In 2008, UCLA went from 102 to 47, and Purdue went from 109 to 61.

In 2006, Boston College went from 92 to 34.

In 2005, Oregon went from 90 to 44, LSU went from 102 to 3, and Arkansas went from 103 to 34.

I took a look at how often

I took a look at how often teams with terrible defenses early in the season improve to be somewhat better than terrible.  It was easiest to compare Aug/Sept rankings to final rankings, so I looked at how many teams ranked 90th or below in total defense at the end of Sept improved to be at least 70th or above by the end of the year.  Michigan was 92nd at the end of Sept (and is currently 102).

2004: 14%

2005: 23%

2006: 20%

2007: 17%

2008: 13%

2009: 16%

If instead you look at how many of the teams 90th and below after September improve at least 15 ranks by the end of the year, you get the following:

2004: 34%

2005: 44%

2006: 23%

2007: 30%

2008: 26%

2009: 32%

So, there's a small chance we can get "slightly below average" or better, and a reasonable chance we can improve somewhat.

I posted a more detailed

I posted a more detailed breakdown of RR's teams below, but Denard has already gotten in 5 games as good or better than what 2005 Pat White did for the whole season.

Denard has 1008 passing yards on 96 attempts (10.50 YPA) compared to Pat White's 828 yards on 114 attempts (7.26 YPA).

Denard has 905 rushing yards on 98 attempts (9.23 YPC) compared to Pat White's 952 yards on 131 attempts (7.27 YPC).

For total offense Denard has 1913 yards on 194 plays (9.86 YPP) compared to Pat White's 1780 yards on 245 plays (7.27 YPP).

Comparison of RR's Offenses

I just registered to post this (after lurking for a while), so I'm adding it as a comment rather than starting a new thread/diary.  I apologize for some screwy formatting in the tables - I couldn't figure out how to remove it.

I wanted to look at the breakdown of Rich Rodriguez's previous offenses, and in particular the main QB's run-pass balance and the fraction of runs by the QB.  I'm only looking at RR in Div 1A (so Tulane OC, Clemson OC, WVU and Michigan), and I'm skipping the mess that was the 2008 offense.  Data comes from the year-end statbooks for each team.

Here is the overall production chart.  QB is the main QB (from what I could tell) - in 1999 Brandon Streeter got a lot of playing time (mostly passing), and in 2001 Rasheed Marshall got a decent amout of playing time.

Year Team QB Pass Plays Pass Yards Rush Plays Rush Yards Total Plays Total Offense QB Pass QB Pass Yardsards QB Rushess QB Rush Yards Total QB Offense
1997 Tulane Shaun King 366 2608 425 2012 791 4620 363 2577 124 511 3088
1998 Tulane Shaun King 375 3615 520 2483 895 6098 364 3495 156 633 4128
1999 Clemson Woody Dantzler 423 3019 497 1812 920 4831 201 1506 146 588 2094
2000 Clemson Woody Dantzler 296 2311 557 2600 853 4911 212 1691 172 947 2638
2001 West Virginia Brad Lewis 357 1811 475 1992 832 3803 237 1339 54 41 1380
2002 West Virginia Rasheed Marshall 279 1753 714 3687 993 5440 259 1616 173 666 2282
2003 West Virginia Rasheed Marshall 252 2034 600 2762 852 4796 215 1729 101 303 2032
2004 West Virginia Rasheed Marshall 259 1993 590 3034 849 5027 171 1426 130 684 2110
2005 West Virginia Pat White 193 1398 625 3269 818 4667 114 828 131 952 1780
2006 West Virginia Pat White 233 2059 590 3939 823 5998 179 1655 165 1219 2874
2007 West Virginia Pat White 265 2067 628 3864 893 5931 216 1724 197 1335 3059
2009 Michigan Tate Forcier 329 2380 494 2234 823 4614 281 2050 118 240 2290
2010 Michigan Denard Robinson 119 1203 228 1622 347 2825 96 1008 98 905 1913
2010 Proj Michigan Denard Robinson 285.6 2887.2 547.2 3892.8 832.8 6780 230.4 2419.2 235.2 2172 4591.2
                           

Denard has already had more passing yards and almost as many rushing yards as 2005-era Pat White.  If he averages just over 100 yards passing per game for the rest of the season he'll have more passing yards than any of RR's QBs other than Shaun King.  If he kept on his current pace (unlikely), he'd end up with almost as many yards as 1997-era Shaun King.  If he averages just over 60 yards rushing per game for the rest of the season he'll have more rushing yards than 2007 era Pat White.  For total offense he would need to average just over 160 yards per game to best Pat White's best season, and just over 315 to match Shaun King.  At this point it looks like Denard is the best all-around QB Rodriguez has had to date: almost as good a passer as King and as good/better a runner as Pat White.

Next I want to look at the breakdown of plays and yards between run and pass, and in particular the QB's share of production.

 

Year Team QB % Rush Playsays % Rush Yardsrds % Runs QBB % Rush Yards QBrds qB % QB Total Playsl Plays % QB Total Yardsl Off QB Rush  % of TotalTot % QB Rush Yards % of Total
1997 Tulane Shaun King 54% 44% 29% 25% 62% 67% 25% 17%
1998 Tulane Shaun King 58% 41% 30% 25% 58% 68% 30% 15%
1999 Clemson Woody Dantzler 54% 38% 29% 32% 38% 43% 42% 28%
2000 Clemson Woody Dantzler 65% 53% 31% 36% 45% 54% 45% 36%
2001 West Virginia Brad Lewis 57% 52% 11% 2% 35% 36% 19% 3%
2002 West Virginia Rasheed Marshall 72% 68% 24% 18% 44% 42% 40% 29%
2003 West Virginia Rasheed Marshall 70% 58% 17% 11% 37% 42% 32% 15%
2004 West Virginia Rasheed Marshall 69% 60% 22% 23% 35% 42% 43% 32%
2005 West Virginia Pat White 76% 70% 21% 29% 30% 38% 53% 53%
2006 West Virginia Pat White 72% 66% 28% 31% 42% 48% 48% 42%
2007 West Virginia Pat White 70% 65% 31% 35% 46% 52% 48% 44%
  Low 54% 38% 11% 2% 30% 36% 19% 3%  
  Median 69% 58% 28% 25% 42% 43% 42% 29%  
  High 76% 70% 31% 36% 62% 68% 53% 53%  
2009 Michigan Tate Forcier 60% 48% 24% 11% 48% 50% 30% 10%
2010 Michigan Denard Robinson 66% 57% 43% 56% 56% 68% 51% 47%
2010 Proj Michigan Denard Robinson 66% 57% 43% 56% 56% 68% 51% 47%
                       

The first two data columns are the percent of all plays and all yards that come from all runs.   The third and fourth are the percent of all runs and rush yards that come from the QB.  The fifth and sixth are the percent of all plays and all yards that come from the QB.  The seventh and eight are the percent of the QB's total plays and yards that come from his runs.

RR has historically varied a fair amount in how much of his offense comes from running the ball - this year we're about average for what he's done in the past, and less run-oriented that for example 2005 West Virginia.  However, our rush offense is by far the most QB-based of any previous offense, far outstripping the one-man show of 2000 Woody Dantzler, and 2007 Pat White.  If we look at total offense, this year's team is more QB-focused than any of the Clemson or WVU teams, but actually on par with the Tulane teams.  Looking at Denard's run-pass balance he's actually right around Pat White's typical split, though he is certainly more run-focused in his production than any of RR's other quarterbacks.

This is just a high-level overview.  I can't break down the kinds of running or passing plays RR is using from this data.  The offense certainly feels very different than the Pat White-era WVU teams in formation and play style, and the YouTube highlights of Woody Dantzler I've seen have the QB iso type feel that we're seeing a lot from this year's team.  I think the main message is that even within his system RR will adapt his style, both at a high level and at the formation/play level, to match his talent - which is what he should do.