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Diaries

Inside the Boxscore - Team 133, Game 13

By ST3 — January 2nd, 2013 at 3:01 PM — 14 comments
Filed under:
  • boxscore
  • Denard Robinson
  • football
  • Jeremy Gallon
  • south carolina
  • Weekender Pants

    I will start my final diary of this season by thanking Dave Brandon for another "Wow" moment. He really went retro with the throwback uniforms, to a time before jerseys had numbers. Wait, there were numbers on those uniforms? One of the first things you learn when you start preparing powerpoint charts is don't use a yellow font color on a white background. (Another thing is make your fonts large enough for your audience to see them - and yes, this is a reference to the mini-numbers on the front of the UTL jerseys.)I would have thought that a marketing genius would know that. Maybe if they had made the blue border a little wider, the number would have stood out, or at least been visible. I think the problem was getting into business with Adidas in the first place. My wife bought me a couple pair of sweatpants for Christmas, because it gets cold at the Badminton Club in January. They were made by Adidas and the tags called them, "Weekender Pants." I tried on a pair and had a strange urge to move to Florida and start playing shuffleboard. In keeping with the SitCom theme of the season, I'll share a quote from Seinfeld regarding sweatpants, "You know the message you're sending out to the world with these sweatpants? You're telling the world, 'I give up. I can't compete in normal society. I'm miserable, so I might as well be comfortable.'" That sums up Adidas and our "wow" jerseys.

Link: http://www.mgoblue.com/sports/m-footbl/stats/010113aaa.html

Burst of Impetus
* I didn't take notes during the game, so I was sitting here trying to remember what big plays Michigan made to grab the momentum. Then it hit me, we didn't make any. All the big plays were made by South Carolina. Ojemudia did force a fumble, but that was about it. Wile's 52 yard field goal was a nice shot in the arm and set us up for a dramatic fourth quarter. Our longest run was 19 yards and our longest reception was 26 yards. Meanwhile, both USC QBs had passes greater than 50 yards and one had a 64 yard run.

Malachi Crunch
* Subtract the three long plays and our defense held SC to 236 yards on 50 plays. (Subtract the punt return and our Special Teams were pretty good as well.)
* Quoting me after game 1, "We held Bama to only 431 yards. They may be the best offense we face all year. If we can hold everyone else under 431, I’ll be happy." USC gained 426 yards. Am I happy? No, because we lost the game.
* We had been playing with fire all season against shaky B1G QBs. We saw what competent QBs can do against 2nd string CBs, and even then, we almost pulled it out. One more bobble on the Sanders TD and that comes back and then who knows?
* So the question is, why did we give up the big plays when we had been so good at avoiding those all season? Was it really the poor B1G QBs? Or was it the loss of JT Floyd?
* Gordon led us in tackles with 6. Ryan was next with 4. The defense was not on the field very much and the stats reflect that.
* We did manage 7 TFLs on USC's 53 plays. I'll take more of that next season.
* Demens only had 1 tackle. Campbell had 0 (did he play?) and Floyd didn't play. That's three of our five defensive leaders contributing one tackle total.

Ermahgerd Dehrnerd
* Denard carried 23 times for 100 yards. He threw once incomplete. It was nice of USC to respect his passing ability (except for the 2nd failed 2pt conversion attempt.) Did they even bother to scout us? He also caught one pass for 7 yards.
* I don't really read Bill Simmons or Grantland anymore. But one of his "things" is the Ewing Theory. In brief, it states that teams can surprise you by winning AFTER the major star leaves the team. Think of Tennessee winning the National Championship with Tee Martin after Manning graduated. Secretly, in a tiny portion of my brain, way back where my repressed memories lie, I'm hoping that Denard is the next Ewing Theory example and Gardner leads us to the promised land next season.

Ermahgerdner
* Let's hope Gardner develops some chemistry with another receiver besides Gallon. Might I suggest Funchess? Half of Gardner's 18 completions went to Gallon.

Bunches of Funchess
* Gallon had 9 receptions for 145 yards and 2 TDs. He would have been the player of the game had Michigan made a stop on USC's final drive.

And Justice for Rawls
* I noticed one of SC's O-linemen had a tattoo that read, "Justice IV All." Justice Hayes ran twice for 3 yards. Rawls didn't carry the ball.

Norf and Souf
* Norfleet returned one kick for 32 yards and made a tackle. I like his enthusiasm, but I'm worried one of these days he's going to get hit with an unsportsmanlike conduct penalty. One of the bigger questions of this off-season is going to be what they do with him, position-wise. Vincent Smith needs to be replaced.

Zonkeys
* OK, I do have a section devoted to the referees, so I guess I have to comment on our 9.99 yard first down. There are only three possible explanations. One, the chain is 10 yards, so the ball only needs to get to the end of the chain, not the linky thing on the yard-marker. Two, the official thought the yard marker was leaning out of the way and if it had been upright, it would have touched the ball. (I'm really straining as a Michigan homer to justify that call.) Three, it was a glitch in the Matrix. Did you all check the back of your necks for the data ports like I did after that play? Slight tangent, if the Matrix had been made today, I think they would be able to replace all those huge connectors with one fiber optic cable up your nose, or possibly a wireless link. Man, how technology has evolved over the years.
* I really couldn't understand the refs, and then it hit me, half of the group had bet on Michigan to cover the spread, and half had bet on USC to win outright, so they compromised and worked it out so that SC could win by 5. What else could explain the head referee COVERING HIS MOUTH while he discussed a play with the other refs. I felt like I was watching the WWE. What are you hiding?

Moar Numberz
* We had 24 first downs to their 17, and 38 minutes TOP to their 22. This was like the Indiana game a few years ago, except we were Indiana. We were grinding it out, 10 yards at a time. The problem with that is you need to be perfect. Any little holding penalty or hands-to-the-face penalty stops your drive.
* Time of possession was 10+ minutes for Michigan in the 1st, 2nd, and 3rd quarters, but only 6:31 in the 4th quarter. Instead of tiring out their defense, I guess our offense got tired.
* Net yards rushing, M: 141, SC: 85. That usually correlates with a victory, but being -1 in TO margin and giving up the punt return TD negates that advantage.
* Clowney had 4 tackles, two TFLs, and the hit that SportsCenter is showing on a continuous loop. It must suck being an O-linemen. You stop a guy for 81 plays, have a miscommunication on the 82nd, and the D-linemen ends up on all the highlight shows and gets picked first overall in the draft next year. I'm sure Lewan and Clowney will meet again at the next level. Those are two outstanding football players. I wanted Muppets, but all I got was Bozo the Clowney.

Thanks to everybody who clicked on my Diary this season, even if it was just to get a handy link to the boxscore. Happy New Year, MGoFriends.
-ST3

  • ST3's blog
  • 14 comments

Ups And Downs: Season-To-Season And Historic Production Changes

By LSAClassOf2000 — January 2nd, 2013 at 11:31 AM — 4 comments
Filed under:
  • football

“A HIGH-LEVEL LOOK AT OVERALL PRODUCTION”

After an afternoon of disappointment followed by reflection, I decided to take a look at the last ten years of Michigan football and conduct a little “then and now” look at it. I had most of this data already, so it was reasonably convenient for me.

I added the South Carolina data into the figuring of seasonal averages for rushing offense and defense, passing offense and defense and scoring offense and defense. I then split the ten seasons into “the previous eight” versus “the last two” and provided separate averages for these. Granted, an average of two numbers isn’t exceedingly meaningful, but it aids in approximating a few other items. More specifically, increases or decreases in productivity between the two periods. Recognizing the dangers of the “average of averages”, given that there are so many data points involved, I will accept the summary statistics as a decent approximation and a good basis for discussion.

So you can see the trends between the first two seasons with this coaching staff, I figured out the percent change along the six metric between the two years, but then I also did this for the “Hoke Era”, if you will, versus the previous eight years so it is possible to see, at a high level, some of the effects of the change.

DATA AND RESULTS:

 

SEASON

Mich Rushing Off. - Avg. Yds

Mich Passing Off. - Avg. Yds

Mich Rushing Def. - Avg. Yds

Mich Passing Def. - Avg. Yds

Mich Scoring Off. - Avg. Pts.

Mich Scoring Def. - Avg. Pts.

2003-04

172.9

270.8

116.6

180.5

35.4

16.9

2004-05

153.6

232.9

133.3

202.9

30.8

23.3

2005-06

164.6

222.7

137.3

202.8

28.8

20.3

2006-07

175.5

195.2

43.4

224.9

29.2

15.9

2007-08

164.9

220.2

156.9

178.9

27.2

21.4

2008-09

147.6

143.2

136.9

230.0

20.3

28.9

2009-10

186.2

198.3

171.9

221.4

29.5

27.5

2010-11

238.5

250.2

188.9

261.9

32.8

35.2

2011-12

221.9

182.9

131.7

190.5

33.3

17.4

2012-13

182.2

199.1

151.7

169.7

29.8

19.8

10 Year Average:

180.8

211.6

136.9

206.4

29.7

22.7

Avg. (Previous 8 Seasons):

175.5

216.7

135.7

212.9

29.3

23.7

Avg. (Last 2 Seasons):

202.1

191.0

141.7

180.1

31.6

18.6

% Change (Prev. 8 Seasons to Last 2 Seasons):

13.2%

-11.9%

4.3%

-15.4%

7.3%

-21.4%

% Change (2011-12 to 2012-13):

-17.9%

8.1%

13.2%

-10.9%

-10.5%

12.1%

 

DISCUSSION:

There shouldn’t be too much in here that you didn’t already surmise.

For one thing, in some of the numbers anyway, you will clearly note what has been called “The Denard Effect” around these parts when it comes to offensive production, particularly rushing and scoring offense.  Between this season and last, the 17.9% decrease in average rushing can be explained by injuries and by role and scheme changes in the offense. It will be interesting to revisit this analysis next year for this reason. The other thing that will not shock anyone is the drop in passing overall during the current regime, but the uptick from last year to this year, mainly due to “the Gardner effect”, if you will.

An interesting statistic to me as well is that, despite appearances, the pass defense did get better this year compared to last despite what I would term the absence of pure pass rusher, at least in my opinion. The rush defense actually took a step back statistically, although you watching the games makes that difficult to believe for me sometimes.

There are plenty of springboards for discussion in this, I believe, but I am interested in what the MGoCommunity thinks.

ADDENDUM (at the request of Blue In Seattle - excellent idea, BTW):

 


SEASON WINS LOSSES OC  DC
2003 10 3 Terry Malone Jim Herrmann
2004 9 3 Terry Malone Jim Herrmann
2005 7 5 Terry Malone Jim Herrmann
2006 11 2 Mike DeBord Ron English
2007 9 4 Mike DeBord Ron English
2008 3 9 Calvin Magee Scot Shafer
2009 5 7 Calvin Magee Greg Robinson
2010 7 6 Calvin Magee Greg Robinson
2011 11 2 Al Borges Greg Mattison
2012 8 5 Al Borges Greg Mattison

FOR THOSE OF US SUFFERING THROUGH WINTER:

  • LSAClassOf2000's blog
  • 4 comments

Adjusted Open Field Yards Adjusted OL Stats for the 2012 FBS

By TSS — December 31st, 2012 at 3:33 AM — 1 comment

It turns out Michigan led the nation in adjusted open field rushing yards (AOFY) in 2012. What I mean by that is whenever a team got their RB 10 yards past the line of scrimmage on any given play – Michigan on average had more added yards than any other team in the nation. Unfortunately Michigan wasn’t very good at getting ball carriers 10 yards past the LOS. Here’s the run down for the entire FBS up until the bowls.

Adjusted Open Field Yards - FBS 2012

Team Conf AOFY AOFY AOFY Rate AOFY Rate
    AVG RNK % RNK
Michigan Big Ten  16.31 1 10.84% 74
Utah State WAC  15.72 2 12.57% 52
Houston  USA 14.26 3 11.20% 67
Kent State MAC  13.53 4 15.59% 27
Texas A&M SEC 13.25 5 14.73% 19
Georgia SEC 12.82 6 14.25% 56
Oregon Pac-12  12.59 7 16.21% 3
Wisconsin Big Ten  12.52 8 16.83% 14
San Diego State MWC  12.51 9 12.63% 9
California Pac-12  12.28 10 14.40% 25
Miami (Florida) ACC  12.28 11 11.08% 100
New Mexico MWC  12.17 12 14.19% 11
Eastern Michigan MAC  12.04 13 11.31% 38
Purdue Big Ten  12.00 14 12.50% 51
UCLA Pac-12  11.93 15 13.71% 21
Oklahoma Big 12  11.90 16 11.43% 94
Texas State WAC  11.88 17 16.00% 13
Florida SEC 11.60 18 14.12% 69
Tulsa  USA 11.59 19 11.44% 84
UCF  USA 11.42 20 13.42% 64
Wake Forest ACC  11.39 21 6.80% 105
Nebraska Big Ten  11.37 22 15.60% 4
Northern Illinois MAC  11.14 23 14.59% 6
LSU SEC 11.14 24 9.44% 85
Michigan State Big Ten  11.06 25 8.10% 117
North Texas Sun Belt  11.00 26 9.86% 109
UNLV MWC  10.80 27 10.70% 80
Texas Big 12  10.71 28 12.47% 50
Vanderbilt SEC 10.63 29 10.36% 104
Louisiana-Lafayette Sun Belt  10.52 30 15.56% 34
Notre Dame IND 10.51 31 12.53% 26
Mississippi State SEC 10.49 32 10.98% 92
Louisiana-Monroe Sun Belt  10.45 33 12.56% 86
Middle Tennessee Sun Belt  10.44 34 12.01% 101
San Jose State WAC  10.39 35 7.80% 120
TCU Big 12  10.30 36 9.57% 87
Florida International Sun Belt  10.27 37 10.84% 91
Hawai'i MWC  10.18 38 7.98% 121
Northwestern Big Ten  10.17 39 13.29% 47
USC Pac-12  10.16 40 15.49% 28
Georgia Tech ACC  10.16 41 13.17% 29
Indiana Big Ten  10.16 42 9.58% 107
Tennessee SEC 10.15 43 11.33% 36
Cincinnati Big East  10.11 44 14.78% 59
Central Michigan MAC  10.08 45 11.80% 39
Nevada MWC  10.07 46 12.85% 55
Florida State ACC  10.04 47 18.44% 1
Marshall  USA 9.98 48 12.59% 76
North Carolina ACC  9.91 49 13.75% 33
Western Kentucky Sun Belt  9.90 50 14.04% 83
Baylor Big 12  9.79 51 12.94% 37
Fresno State MWC  9.70 52 11.79% 53
West Virginia Big 12  9.65 53 16.80% 10
Kansas Big 12  9.59 54 12.53% 93
Virginia Tech ACC  9.53 55 10.77% 88
Arizona Pac-12  9.42 56 17.51% 15
Oklahoma State Big 12  9.41 57 13.82% 18
Western Michigan MAC  9.34 58 12.13% 40
Louisiana Tech WAC  9.32 59 13.50% 12
UTSA WAC  9.25 60 12.36% 60
Boston College ACC  9.24 61 12.13% 96
Arkansas State Sun Belt  9.22 62 13.36% 8
Alabama SEC 9.16 63 15.80% 2
Iowa Big Ten  9.15 64 9.73% 114
Ohio MAC  9.11 65 13.43% 63
Ohio State Big Ten  9.09 66 17.55% 7
Bowling Green MAC  9.07 67 11.29% 65
Rutgers Big East  9.07 68 8.26% 119
Rice  USA 8.97 69 12.01% 62
Idaho WAC  8.96 70 8.00% 122
Temple Big East  8.94 71 16.13% 41
Army IND 8.89 72 14.74% 22
Ball State MAC  8.85 73 12.18% 32
Oregon State Pac-12  8.84 74 10.98% 82
Boise State MWC  8.80 75 14.02% 75
South Alabama Sun Belt  8.77 76 8.41% 90
Missouri SEC 8.50 77 9.77% 58
Air Force MWC  8.46 78 11.85% 49
UTEP  USA 8.46 79 11.27% 66
Pittsburgh Big East  8.45 80 11.24% 106
Navy IND 8.44 81 12.13% 24
South Florida Big East  8.33 82 12.73% 57
Colorado State MWC  8.32 83 10.57% 77
Akron MAC  8.32 84 11.22% 54
Troy Sun Belt  8.26 85 11.99% 45
Toledo MAC  8.21 86 14.58% 5
Stanford Pac-12  8.20 87 11.92% 72
Wyoming MWC  8.19 88 8.51% 97
Florida Atlantic Sun Belt  8.10 89 8.75% 113
Memphis  USA 8.08 90 9.39% 99
SMU  USA 8.05 91 13.27% 23
Auburn SEC 7.98 92 12.61% 35
Utah Pac-12  7.97 93 9.02% 103
Colorado Pac-12  7.94 94 9.91% 110
Clemson ACC  7.86 95 13.60% 71
Texas Tech Big 12  7.81 96 15.38% 17
Maryland ACC  7.79 97 8.21% 115
Kentucky SEC 7.74 98 12.19% 79
BYU IND 7.69 99 10.95% 46
Connecticut Big East  7.66 100 7.51% 124
Syracuse Big East  7.61 101 9.49% 73
East Carolina  USA 7.42 102 9.84% 61
New Mexico State WAC  7.41 103 9.32% 95
Southern Mississippi  USA 7.27 104 12.47% 20
Penn State Big Ten  7.09 105 7.05% 108
Washington Pac-12  7.02 106 12.43% 31
Buffalo MAC  7.00 107 11.27% 44
Virginia ACC  6.81 108 12.00% 81
Mississippi SEC 6.75 109 14.29% 48
Iowa State Big 12  6.68 110 13.12% 89
South Carolina SEC 6.60 111 11.69% 68
Duke ACC  6.59 112 9.09% 111
Louisville Big East  6.55 113 12.84% 70
Kansas State Big 12  6.53 114 14.12% 43
Arkansas SEC 6.50 115 11.39% 30
Illinois Big Ten  6.43 116 11.17% 42
Arizona State Pac-12  6.20 117 12.77% 16
UAB  USA 6.08 118 14.24% 78
Washington State Pac-12  6.06 119 9.52% 118
Miami (Ohio) MAC  5.94 120 12.18% 102
North Carolina State ACC  5.56 121 7.42% 116
Massachusetts MAC  5.36 122 9.52% 112
Minnesota Big Ten  4.79 123 10.86% 98
Tulane  USA 4.21 124 5.62% 123

These are conditionally formatted – Blue to Red with the hue indicating the spread of these numbers. Michigan is the clear leader in this contrived stat.

To see Michigan leading the nation in any offensive stat was a surprise to me – and I thought I’d share it. It’s not an official stat by any means but it’s one that I came upon while looking to quantify Offensive Line (OL) performance. What I wanted to see was an offensive line performance stat/summary for 2012 based on the metrics Football Outsiders (FO) uses for the NFL.

What I’m finding is not what I wanted with respect to OL work but I’ll share some of that since it explains the table above.

Scheme is by far the more telling factor in rushing success in the FBS than NFL caliber OL talent or all-American status. Triple option teams do extremely well but without the boss hogs or broad reach blocking lineman of the primo run spread teams that I expected to dominate these stats. I don’t want to take anything away from any of these teams however. What they have done in rushing stats – doesn’t happen if the OL is not playing like a team.

Here’s the standard rushing yards per game with some minor tweaks. There are interesting differences between this and the OL stats I pulled and present later on…

Standard Rush Stats 2012

(minus sacks and FCS games)

 

Team Conf % Rush Plays % Pass Plays Rush /G Rush Yds/G Rush Yds /G Rush Rush
    % % AVG RNK RNK AVG STD
Army IND 86.65% 13.35% 383.27 37 1 5.60 7.85
Oregon Pac-12  63.53% 36.47% 333.36 4 2 6.32 10.13
Air Force MWC  83.68% 16.32% 317.82 53 3 5.05 6.74
Georgia Tech ACC  78.88% 21.12% 305.00 49 4 5.41 7.73
New Mexico MWC  80.18% 19.82% 304.17 93 5 5.82 9.24
Navy IND 77.87% 22.13% 277.00 82 6 5.28 6.89
Wisconsin Big Ten  65.11% 34.89% 261.92 55 7 6.08 10.10
Nebraska Big Ten  59.57% 40.43% 261.33 25 8 5.89 9.75
Northern Illinois MAC  59.54% 40.46% 258.00 16 9 5.94 9.24
Ohio State Big Ten  63.32% 36.68% 257.67 42 10 5.83 8.54
Nevada MWC  59.93% 40.07% 256.55 13 11 5.26 7.54
Texas A&M SEC 49.76% 50.24% 252.10 3 12 6.09 9.17
Kent State MAC  60.69% 39.31% 248.92 61 13 6.05 10.32
San Diego State MWC  61.53% 38.47% 239.73 59 14 5.65 9.15
Tulsa USA 57.76% 42.24% 236.92 33 15 4.93 8.51
Northwestern Big Ten  59.56% 40.44% 234.18 67 16 5.27 8.14
Alabama SEC 59.77% 40.23% 232.50 36 17 6.04 7.65
Louisiana Tech WAC  48.48% 51.52% 231.75 2 18 5.44 7.70
Baylor Big 12  52.41% 47.59% 231.09 1 19 5.31 7.96
Arizona Pac-12  48.38% 51.62% 230.73 9 20 5.85 8.70
UCLA Pac-12  51.72% 48.28% 224.08 15 21 5.55 9.17
Ohio MAC  55.70% 44.30% 223.27 30 22 5.07 7.67
Kansas Big 12  61.80% 38.20% 222.64 96 23 5.03 7.82
Ball State MAC  52.15% 47.85% 220.00 19 24 5.19 7.26
Rice USA 57.31% 42.69% 219.58 41 25 4.87 7.11
Clemson ACC  53.47% 46.53% 217.18 7 26 5.00 6.87
Florida SEC 61.74% 38.26% 216.64 103 27 5.43 8.89
Toledo MAC  52.75% 47.25% 215.36 24 28 5.48 7.21
Florida State ACC  51.68% 48.32% 215.09 22 29 6.15 9.16
Arkansas State Sun Belt  53.45% 46.55% 211.27 20 30 5.35 7.59
Notre Dame IND 56.14% 43.86% 210.00 51 31 5.35 8.16
Temple Big East  63.67% 36.33% 204.80 112 32 5.08 8.22
Oklahoma State Big 12  49.59% 50.41% 204.27 5 33 5.26 7.86
Georgia SEC 54.45% 45.55% 201.75 26 34 5.66 9.48
Arizona State Pac-12  52.98% 47.02% 200.55 29 35 4.77 6.04
Cincinnati Big East  54.87% 45.13% 199.20 50 36 5.35 8.49
Michigan Big Ten  59.95% 40.05% 197.33 77 37 5.35 9.88
Louisiana-Lafayette Sun Belt  53.33% 46.67% 197.09 32 38 5.53 8.90
LSU SEC 57.49% 42.51% 196.36 72 39 4.85 7.30
North Carolina ACC  48.54% 51.46% 196.00 18 40 5.39 8.25
California Pac-12  49.54% 50.46% 195.73 70 42 5.74 9.79
West Virginia Big 12  44.64% 55.36% 195.73 8 41 5.56 8.97
Texas State WAC  49.09% 50.91% 195.00 86 44 6.13 9.42
Western Kentucky Sun Belt  57.36% 42.64% 195.00 84 43 5.19 7.59
Kansas State Big 12  62.27% 37.73% 194.45 62 45 4.87 6.22
Utah State WAC  49.67% 50.33% 193.55 31 46 5.69 10.54
UCF USA 53.47% 46.53% 190.15 60 47 5.35 8.84
Middle Tennessee Sun Belt  58.20% 41.80% 189.91 68 48 4.82 8.28
Texas Big 12  54.29% 45.71% 188.58 38 49 5.04 8.84
Marshall USA 40.79% 59.21% 182.55 6 50 4.96 8.21
Mississippi SEC 53.51% 46.49% 181.55 47 51 4.68 6.68
Stanford Pac-12  55.43% 44.57% 180.38 88 52 4.74 6.98
Eastern Michigan MAC  56.86% 43.14% 180.00 105 53 4.97 8.58
Purdue Big Ten  47.12% 52.88% 179.09 65 54 5.24 9.61
Buffalo MAC  52.59% 47.41% 177.64 94 55 4.59 6.08
Boise State MWC  54.51% 45.49% 176.75 79 56 4.88 7.89
Syracuse Big East  50.23% 49.77% 175.91 21 57 4.48 5.79
Troy Sun Belt  45.76% 54.24% 175.50 11 58 4.76 6.77
Fresno State MWC  45.09% 54.91% 175.00 14 59 4.94 8.05
BYU IND 48.35% 51.65% 172.09 58 60 4.61 6.72
Southern Mississippi USA 56.76% 43.24% 171.92 108 61 4.59 6.91
South Florida Big East  48.77% 51.23% 167.55 91 62 4.89 7.22
Virginia Tech ACC  51.73% 48.27% 166.55 73 63 4.38 7.97
TCU Big 12  52.32% 47.68% 166.27 69 64 4.38 7.22
USC Pac-12  44.60% 55.40% 164.25 28 65 5.55 8.73
Vanderbilt SEC 56.01% 43.99% 163.82 83 66 4.34 8.12
UTEP USA 51.20% 48.80% 163.33 85 67 4.60 7.21
Florida International Sun Belt  52.68% 47.32% 163.17 71 68 4.33 7.65
Houston USA 38.11% 61.89% 163.08 17 69 5.22 9.51
Michigan State Big Ten  48.59% 51.41% 162.75 90 70 4.52 6.23
Tennessee SEC 44.20% 55.80% 162.64 23 71 4.94 7.46
South Carolina SEC 54.25% 45.75% 160.91 75 72 4.40 6.15
Bowling Green MAC  49.14% 50.86% 159.82 98 73 4.73 6.80
Penn State Big Ten  48.76% 51.24% 159.33 46 74 4.21 4.85
North Texas Sun Belt  53.89% 46.11% 159.27 87 75 4.21 8.14
Memphis USA 60.68% 39.32% 159.09 114 76 4.11 6.25
Louisiana-Monroe Sun Belt  42.81% 57.19% 157.58 34 77 4.85 7.73
Oklahoma Big 12  41.18% 58.82% 157.18 12 78 4.94 9.27
UNLV MWC  45.49% 54.51% 157.08 92 79 4.92 8.06
Western Michigan MAC  41.12% 58.88% 154.91 45 80 5.04 7.31
Pittsburgh Big East  51.15% 48.85% 154.90 66 81 4.35 6.92
Iowa State Big 12  48.17% 51.83% 153.64 97 82 4.44 6.31
East Carolina USA 45.98% 54.02% 152.73 52 83 4.59 5.75
UTSA WAC  48.59% 51.41% 151.63 80 84 4.68 7.67
Auburn SEC 56.58% 43.42% 151.09 122 86 4.66 7.10
Washington Pac-12  45.95% 54.05% 151.09 102 85 4.80 6.52
Missouri SEC 48.32% 51.68% 150.18 95 87 4.25 7.13
Illinois Big Ten  51.51% 48.49% 149.27 123 89 4.37 6.11
Miami (Florida) ACC  43.10% 56.90% 149.27 35 88 5.05 8.49
Minnesota Big Ten  55.93% 44.07% 148.64 116 90 4.13 5.17
Texas Tech Big 12  37.64% 62.36% 147.73 10 91 5.21 7.51
Colorado State MWC  49.79% 50.21% 147.64 101 92 4.64 6.71
SMU USA 39.51% 60.49% 146.36 89 93 5.21 7.02
Central Michigan MAC  46.33% 53.67% 144.36 78 94 4.93 7.72
Mississippi State SEC 46.81% 53.19% 144.27 76 95 4.71 7.72
South Alabama Sun Belt  48.09% 51.91% 143.50 104 96 4.14 6.29
Utah Pac-12  52.07% 47.93% 143.00 113 97 4.17 6.00
Wyoming MWC  47.59% 52.41% 142.55 54 98 4.17 6.19
Louisville Big East  47.35% 52.65% 142.27 43 99 4.28 6.56
Virginia ACC  43.42% 56.58% 140.82 74 100 4.43 6.04
Kentucky SEC 44.82% 55.18% 135.45 118 101 4.66 6.92
UAB USA 40.85% 59.15% 135.36 40 102 4.42 6.23
Indiana Big Ten  39.20% 60.80% 133.64 39 103 4.40 7.28
Colorado Pac-12  44.66% 55.34% 132.64 115 105 4.25 6.70
Oregon State Pac-12  42.55% 57.45% 132.64 44 104 4.33 7.03
San Jose State WAC  46.38% 53.62% 132.00 27 106 4.04 6.77
Duke ACC  42.05% 57.95% 131.55 64 107 4.11 5.71
Maryland ACC  55.83% 44.17% 131.18 120 108 3.59 6.29
Iowa Big Ten  46.95% 53.05% 130.09 121 109 4.22 6.27
Arkansas SEC 41.69% 58.31% 126.00 56 110 4.39 6.11
Akron MAC  35.61% 64.39% 125.64 57 111 4.56 7.26
Hawai'i MWC  45.82% 54.18% 124.27 119 112 3.89 6.13
Rutgers Big East  51.32% 48.68% 124.09 106 113 3.89 6.17
North Carolina State ACC  40.99% 59.01% 121.36 48 114 3.67 4.96
New Mexico State WAC  42.66% 57.34% 120.45 107 115 4.26 5.83
Florida Atlantic Sun Belt  45.01% 54.99% 118.18 100 116 3.79 6.13
Wake Forest ACC  44.30% 55.70% 116.73 117 117 3.80 6.68
Massachusetts MAC  44.26% 55.74% 108.67 124 118 3.45 5.39
Connecticut Big East  47.83% 52.17% 106.33 110 119 3.31 5.69
Idaho WAC  40.60% 59.40% 106.27 111 120 3.90 5.70
Miami (Ohio) MAC  35.42% 64.58% 104.55 63 121 4.24 5.76
Boston College ACC  36.56% 63.44% 103.55 99 122 4.19 8.60
Tulane USA 30.48% 69.52% 60.08 109 123 2.90 4.83
Washington State Pac-12  20.77% 79.23% 53.18 81 124 3.48 5.87

I formatted standard deviation in green – because I’m not sure what’s good in that regard. I would say looking at the data however that a reasonably high spread in general is a sign of success.  Std Dev is a tell for scheme and some of the OL stats I was breaking out when I came to Open Field Yards.

FO has done some good stuff with respect to offensive line performance. They contrived a few ways to tweeze out relative OL performance. Curiously I couldn’t find these methods applied to college ball. I gave it a quick whack in the first diary and came up with a gross reality check that pretty much matched my gut – OL performance was not good in that game and adjusted line yards were significantly lower.

Check the FO link and previous diary to define Adjusted Line Yards but here is a quick chart and definition of their derived stats for Adjusted Line Yards (ALY), Second Level Yards (SLY) and Open Field Yards (OFY) as compiled by FO.

image_thumb7_thumb

What’s going on here is they are taking yards per play and giving them value based on the outcome. The concept is simple – the initial yards are more relevant to OL performance. The second level yards less so. The open field yards…not so much.

Adjusted Line Yards (<=10 yards)– are conceptually on the offensive line – no block no gain

  • Losses: 120% value – because if you don’t block at all that’s a TFL

    0-4 Yards: 100% value
    5-10 Yards: 50% value
    11+ Yards: 0% value e.g. 10 yard gain is worth 7 yards… 20 yard gain is worth 7 yards…

Second Level Yards (6-10 yard gains) – are a combined ball carrier and OL stat

  • Losses – 5 yards: 0% value

    6-10 Yards: 100% value e.g. 6 yard gain is worth 1 SLY…
    11+ Yards: 0% value e.g. 10 yard gain is worth 5 SLYs… 20 yard gain is worth 5 SLYs…

Open Field Yards (11+) = are conceptually on the ball carrier

  • Losses – 10yards: 0% value
    11+ Yards: 0% value e.g. 11 yard gain is worth 1 OFY … 20 yard gain is worth 10 OFYs…
    Caveat 1 - I took out Sacks.
    Caveat 2 – I took out games involving FCS teams. Which is a gift to Mich since we played UMass.

Caveat 3 – I include QB rushing here. I did this because it’s college and … well… duh… Denard. Scrambles don’t make much difference in the overall here and the NCAA counts them as rushes so … be it.

I looked at this data and tried to make sense of it. It didn’t look good for Michigan. So I did what any good MGoBlog diarist does and adjusted it to suit my thesis.

It still doesn’t look good for Michigan but this is what I did.

Adjusted Adjusted Line Yards AALY

  • I normalized the losses over 10 yards to –10 yards. I did a sampling and these were snap issues (still an OL issue but not what I’m concerned about) – reverse plays gone wrong or mis-tagged sacks*. (*There’s plenty of errors in the cfbstats.com data BTW – but I don’t think they are significant. Most of them appear to be due to NCAA/Scoring issues anyway.)

Adjusted Second Level Yards ASLY

  • I took out the plays that went for zero yards – in general you can’t hold it against the ball carriers if they didn’t get to the second level.

Adjusted Open Field Yards AOFY

  • Same as above – I took out plays that went for less than 11 yards to isolate these from the mean OFY totals.
    With these adjustments in mind I added two columns for SLY rate and OFY rate to represent the % of plays that a team sprang ball carriers for these distances.

Here’s a revised chart with these adjustments…the distributions are better and the model is better for what these derivative stats are intended to represent.

image_thumb28_thumbimage_thumb29_thumb

I added an ASLY % rate to the summary table to show how often teams got their rusher to the second level as well as an AOFY % rate. These are important and significant changes over the FO yards stat. Their NFL rates of 2nd level and Open Field plays are rolled into their summary yards.

Since I had the data summarized I added the FO convention for Success Rate % for all rushing plays defined as follows:

  • 1st downs that achieve 50% of yardage needed to convert or score
  • 2nd downs that achieve 70% of yardage needed to convert or score
  • 3rd/4th downs that convert or score
    Stuffed rate is defined as Percentage of runs where the running back is tackled at or behind the line of scrimmage. This includes QB runs minus sacks (this appears to be a press box discretion as there are negative QB runs that are not accounted as Sacks – I should look at this more closely but I don’t think it’s significant here.)

Finally I tallied Power Success straight up to the FO definition as percentage of runs on third or fourth down, two yards or less to go, that achieved a first down or touchdown. This also includes runs on first-and-goal or second-and-goal from the two-yard line or closer.

At this point I’m stultified by the challenge that OL statistical summarization presents wrt CFB (or any kind of football for that matter.)  If I had time I’d follow the FO path and normalize this data to FBS averages… look at the individual ball carriers…take out garbage time… but I also kind of want to watch some bowl games and MSS wants me to take down the tree... and little TSS wants to ski.  Let’s just say this is a work in progress.

Regardless of my problems… here’s the table that I was able to get up today…I added in Sack Rate (which I’m  very skeptical of in terms of an OL criteria as I have seen previously when comparing the different SRs for Denard, Bellomy and Devin.) I went to three letter acronyms for the conferences.  It is what it is.

OL Stats 2012 – FBS

Team Conf AALY ASLY  AOFY  Stuff Rate ASLY Rate AOFY Rate Power Success Rate Success Rate Sack Rate
    AVG AVG AVG % % % % % %
Alabama SEC 3.67 3.49 9.16 12.77% 39.61% 15.80% 6.49% 52.16% 7.40%
Army IND 3.56 3.48 8.89 10.89% 34.66% 14.74% 7.84% 49.54% 8.62%
Northern Illinois MAC  3.47 3.56 11.14 14.01% 37.43% 14.59% 8.25% 48.75% 3.11%
Navy IND 3.41 3.36 8.44 14.38% 34.49% 12.13% 6.93% 49.91% 10.98%
Toledo MAC  3.41 3.49 8.21 17.36% 37.50% 14.58% 6.94% 48.38% 5.43%
Air Force MWC  3.36 3.44 8.46 15.32% 32.08% 11.85% 7.51% 47.25% 5.19%
Ohio State B1G  3.36 3.61 9.09 16.23% 37.36% 17.55% 7.55% 51.70% 9.45%
Ball State MAC  3.35 3.37 8.85 13.16% 33.60% 12.18% 6.29% 46.95% 2.14%
Arizona P12  3.33 3.81 9.42 15.67% 35.94% 17.51% 7.60% 48.62% 3.89%
Texas State WAC  3.31 3.62 11.88 15.43% 36.00% 16.00% 5.14% 47.71% 7.71%
Florida State ACC  3.31 3.57 10.04 20.26% 40.26% 18.44% 3.90% 51.17% 7.22%
Oregon P12  3.30 3.66 12.59 18.97% 38.79% 16.21% 6.55% 50.69% 5.11%
SMU USA 3.29 3.44 8.05 16.83% 34.63% 13.27% 3.56% 44.98% 5.50%
Louisiana Tech WAC  3.29 3.37 9.32 17.03% 36.01% 13.50% 7.05% 52.25% 1.84%
Georgia Tech ACC  3.29 3.43 10.16 14.94% 34.02% 13.17% 8.58%