Malzahn and Nightmare Fuel: Part Two

What a waste of talent. - Butch Dill

Installment two of a three-part series skinny dipping in data on the Gus Malzahn offense. Heedless conclusions are drawn, and wild assumptions are made: Fun for the whole family (or, if in Auburn, "fambly").

RECAP AND PREVIEW:

Part One of the instant examination began with a cursory overview of the Malzahn offense. The conclusions drawn were that his spread is not necessarily so much innovative, rather it is the speed in which he runs it that poses problems. Such innovations as they exist are his synthesis of several concepts, its speed, and the popularization of the Wildcat (which, at its heart, is a power set).

Here’s Gus explaining that for ya’.


Okay, he make look like a Nazi extra from Indiana Jones, but it's cool listening to him talk offense.

Part Two will look closer to the data: Specifically, what patterns –if any, are revealed when teasing out the results, and, does the offense "work" (an admittedly nebulous concept).

THE NUMBERS:

For data analysis, I chose to use the numbers crunched at Football Outsiders, generally considered to be one the most comprehensive sites around (and occasional home of SBNation’s own Bill Connelly). FO analyzes possessions based upon the FEI. For those unfamiliar with FEI, it is rife with a comprehensive Phil Steele-ian set of acronyms, but the general output is commonsensical enough:

Fremeau Efficiency Index (FEI) considers each of the nearly 20,000 possessions every season in major college football. All drives are filtered to eliminate first-half clock-kills and end-of-game garbage drives and scores. A scoring rate analysis of the remaining possessions then determines the baseline possession efficiency expectations against which each team is measured. 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.

The acronyms used below are:

  • OFEI: Offensive FEI, the opponent-adjusted efficiency of the given team's offense.

  • OE: Offensive Efficiency, the raw unadjusted efficiency of the given team's offense, a measure of its actual drive success against expected drive success based on field position.

  • FD: First Down rate, the percentage of offensive drives that result in at least one first down or touchdown.

  • AY: Available Yards, yards earned by the offense divided by the total number of yards available based on starting field position.

  • Ex: Explosive Drives, the percentage of each offense's drives that average at least 10 yards per play.

  • Me: Methodical Drives, the percentage of each offense's drives that run 10 or more plays.

  • Va: Value Drives, the percentage of each offense's drives beginning on its own side of the field that reach at least the opponent's 30-yard line.

  • OSOS: Offensive Strength of Schedule, the likelihood that an elite offense (two standard deviations better than average) would have an above-average OE rating against each of the defenses faced by the given team.

Given the above, here is a quick ranking of Malzahn’s offenses under both the OFEI and S&P* methodology. (H/T to RoscoeOfAlabama for trying to steal my thunder).

2007 ( Tulsa OC): #19 Off. S&P, #21 OFEI
2008 (Tulsa OC): #17 Off. S&P, #9 OFEI
2009 (Auburn OC): #38 Off. S&P, #25 OFEI
2010 (Auburn OC): #1 Off. S&P, #1 OFEI
2011 (Auburn OC): #40 Off. S&P, #47 OFEI
2012 (Arkansas State HC): #22 Off. S&P, #31 OFEI

Meanwhile, here are the complete data under the FEI, and its factors:

OFEI


OFEI
Rk


Team


Year


FBS
Rec


FEI
Rk


OE


OE
Rk


FD


FD
Rk


AY


AY
Rk


Ex


Ex
Rk


Me


Me
Rk


Va


Va
Rk


OSOS


Rk


.311

21

Tulsa

2007

10-4

54

.627

2

.767

5

.566

4

.227

2

.097

102

.484

11

.208

75

.435

9

Tulsa

2008

10-3

39

.820

5

.839

2

.646

3

.273

1

.105

93

.592

3

.282

91

.252

25

Auburn

2009

7-5

32

.068

50

.652

64

.454

50

.135

46

.092

106

.359

71

.047

22

.857

1

Auburn

2010

13-0

1

.665

4

.783

10

.593

9

.232

6

.123

76

.545

9

.018

2

.096

47

Auburn

2011

7-5

66

-.142

80

.624

85

.396

93

.113

68

.090

109

.350

71

.019

4

.231

31

Arkansas State

2012

9-3

51

.529

8

.738

27

.553

17

.148

53

.205

15

.509

11

.256

97

HYPOTHESIS-FREE OBSERVATIONS:

Before applying the data to the hypotheses tomorrow (8th grade science class, holler!), there are several surprising things about Malzahn’s offense. Particularly striking are:

  • Explosive plays and the necessity for an elite QB: What a mess. There is zero consistency with respect to Malzahn’s teams making big, explosive plays. And, really, only one thing anecdotally correlates with the highly discrepant returns: Quarterback play; specifically, elite QB play. See, it doesn’t matter how efficient the quarterback even is. For instance, last year Ryan Aplin at ArkansasState was 17th in passing efficiency. Still, explosive plays occurred less than 16% of the time, a rather pedestrian 53rd overall. Chris Todd in 2009? 20th in passing efficiency, but Auburn ranked just 50th in explosive plays.
  • However, at Tulsa in 2007-2008, first Paul Smith, then David Johnson –elite and highly efficient guys, devoured opposing secondaries for huge plays (and huge yards/TDs). Johnson was 2nd in efficiency in 2008, and Tulsa was 1st in explosive plays. In 2007, Smith was 5th in efficiency, and Tulsa was 2nd in explosive plays. In 2010, Auburn had the benefit of Cam Newton accounting for explosive plays with both his feet and his arm (the latter bolstered mainly by his incredibly good play action, already considered among the best in the NFL). In addition to being the SEC’s leading rusher Newton was also the 2nd most efficient passer. As expected, the offense was dynamic, with Auburn ranking 6th in the fireworks department.
  • Moving the Chains Quickly, Accumulating First Downs You’d think moving at light speed, working the chains and getting first downs would lead to a methodical offense; one that puts together successful drives. You would be incredibly wrong applying these assumptions to Malzahn. Look at the columns above labeled ME and ME rank. These refer to the percentage of drives that run 10+ plays. Surprisingly, for an offense that is so sporadic regarding explosive plays, you’d think the scheme would build-in ways to maximize plays when the home run is not there. The results are to the contrary: Malzahn’s teams just simply donot string together drives.
  • His teams epitomize feast or famine; a home run or nothing. His most methodical team, the ’12 Red Wolves, were 15th in putting together longer drives (approximately 20% of the time). Prior to that, every other Malzahn team ranked 76th or lower, with even the 2010 Auburn offense only stringing together drives 12% of the time…every other Malzahn team was batting about 10% or lower.
  • On the flipside, when the offense is actually moving, it is usually good at accumulating first downs. On four occasions Malzahn teams have been in the top quartile (and three times, they were in the top 10 in accumulating first downs). This is particularly borne out by the VA metric, value drives –those which begin on the offense’s side of the field and reach at least the opponent’s 30 yard line. Only one Auburn team was remotely good at that: The 2010 version. Both 2011 and 2009, Malzahn’s teams were in the bottom half for value drives. However, he had great success at Arkansas State and Tulsa, finishing 11th or better four times, and Value Drives occurring at least 50% of the time every year.
  • Some Food for Thought: Putting the above data together, a picture begins to emerge. A "typical" Malzahn team will move the chains in healthy, but generally not explosive, increments. As it is doing so, it will be gaining first downs and significant yardage, and at least half the time it will be knocking on opponent’s red zones (or at least be in field goal range). Depending on how good the quarterback is, you can expect a home run every 6-10 plays –about once a drive.
  • From there, drives either peter out, since the offense is not predicated on meticulous, grinding execution –or you’ve just been scored upon. But, all is not lost if you’re an Auburn fan. Even if no points are scored, the value driving offense has the other effect of flipping the field: If Gus teams are racking up 35-50 yards per, they’ve put opposing offenses in a hole. It is in essence punting via offense, and is a very aggressive way to win the field position war.
  • Finally: Given the actuarial results from years of D-I teams, you can’t help but wonder if Ted Roof et al wasn’t placed in a somewhat compromising position. Sure, the value driving can help the defense by making offenses play the full length of the field, but that’s not the whole story. When your offense is moving with elbows-and-assholes speed, and is in return either scoring or getting off the field after usually very short drives, all the scheming in the world can’t help your defense. Eventually, you are wearing down your own guys, particularly if they are playing the LSUs , Alabamas and Floridas of the world –teams that will string together 12-15 play, 8-minute drives. To an outside observer, then, the need for elite depth –especially on the defensive line, and careful attention to conditioning would seem to be a prerequisite for a defense that doesn’t implode down the stretch. Conversely, perhaps the best way to counter the offense is to do what has always worked: Pound the ball, keep the defense on the field and make their asses quit.

Tomorrow’s Part Three: Putting it all together and testing some hypotheses. In the meanwhile, please feel free to chime in.

*I’m not as big a fan of the S&P+, since it only factors in "competitive" conditions and disregards "garbage time" (defined as "not within 28 points in the first quarter, 24 points in the second quarter, 21 points in the third quarter, or 16 points in the fourth quarter.") While it is a useful tool, the arbitrary cutoffs don’t seem to be as fully reflective of many offenses which always push for yards, first downs, and to move the chains. This is just a data preference on my part.

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