Advanced Scouting...By Accident

After five years of living in Texas I finally made it to my first high school football game last Friday night. As luck would have it the game allowed an early glimpse of a future Husker (perhaps, maybe, we'll see how things shake-out). Anyway, as I was saying I attended the Baytown Robert E. Lee homecoming battle against Port Arthur Memorial H.S. Port Arthur's star player just happens to be one David Whitmore who is currently committed to the Huskers.

So how did I find myself at said contest? Well, my lovely fiance is a proud Baytown Lee Gander (seriously their nickname is the Ganders), as is pretty much her entire family. Kind of like my family full of Rockets from Lincoln Northeast. But I digress...

Now onto the scouting:

From what I could see Whitmore has a lot of developing to do before he contributes in any meaningful manner. He is SKINNY and that means a lot coming from me. That's sort of like Mark Mangino calling someone fat, if you catch my meaning. Whitmore's legs look like they should be holding up popsicles rather than a future DI football player. He does, however, have plenty of height which will certainly come in handy amongst the 6-4 receivers that now dot the Big 12 landscape.

Whitmore wasn't thrown at much on Friday. It was difficult to tell if this was by design becuase Baytown's QB play was spotty at best. Two plays do standout though.

On the first, Whitmore was beaten on a hitch move. This obviously caused an automatic cringe from Jeffie Husker, given Nebraska's recent struggles with this route. What I liked, however, was Whitmore's ability to close on the reciever while the ball was in the air. In fact after making up a large cushion, Whitmore actually put himself in position to intercept the pass on a perfectly timed turn to look back at the ball. Unfortunately, the refs called pass interference on Whitmore for using his hands to gain the advantage while in the air. I thought it was a terrible call based on what the official thought was going to happen, rather than the way Whitmore pulled it off.

On the second play Whitmore had to defend a bubble screen type pass thrown to his side. Despite showing initial hesitancy, Whitmore fended off a block from another receiver and made a pretty nice open field tackle. In fact, Whitmore made in my mind a prototypical CB tackle by simply getting low enough to take out the reciever's legs (or pins - for you Jim Rose fans). That play occurred right in front of me, and I couldn't help but give him a one-man standing ovation. Had it occurred at Memorial Stadium I would have been joined by 85,000 fans as it was clearly a better tackle than any of us have seen this season.

One thing that surprised me, however, was I didn't see Whitmore take even one snap on offense. I know Texas football is different than Nebraska high school football, but the fact that he doesn't crack the offensive starting lineup seems a bit worrisome to me. Overall, I'd say Whitmore has a lot of athleticism and good potential. He showed me plenty of speed and good hips (not the Eva Mendes type), meaning he is already less stiff than Andre Jones. In addition, I came away extremely expressed with his ability to close on receivers and make a play on the ball in the air. You just can't teach those skills.

So we'll see now if Whitmore winds up in Lincoln and if so, how well my attempt at a scouting report pans out.

Marlon Lucky and Nebraska on Third Down

Who knows what the Missouri game will actually come down to, but Nebraska's ability to convert on third down will certainly be key. Thus far, Nebraska is converting 45.83% of their 3rd down attempts, which ranks us 20th nationally in this statistic. On the road, however, we've been absolutely brutal, converting just 3/15 attempts (20%)at Wake Forest. That's just not going to cut it in Columbia.

An important component of 3rd down success is the emergence of big play guys who step up when it's time to move the chains. If you think back to 2006, the go-to guy on 3rd down was Maurice Purify. In 2006, Nebraska threw to Purify 23 times on 3rd down resulting in 14 receptions. Of those 14 completions, 11 garnered first downs and three resulted in touchdowns. It's early in 2007, so we're still waiting for our 3rd down weapon to emerge...or are we?

I took a closer look at Marlon Lucky's numbers for the year and was surprised by what I saw from him, especially on 3rd down. In the table below we have Lucky's rushing statistics on 3rd down for 2007.


What jumps out immediately is the eye-popping average yards per carry. Did anyone realize that Lucky is averaging 7.77 yards per carry on third down? That's pretty impressive. By digging a little further I was able to put that figure into perspective.

In this table we have the nation's Top 10 players in average yards per carry on third down plays (with a minimum of 10 carries).


Here we see that Lucky's 7.77 yards/carry rank 4th nationally, ahead of such stars as P.J. Hill, Ray Rice and Darren McFadden. Color me impressed.

But yards per carry is really only way to look at third down backs. Another and perhaps more important variable is the running back's ability to convert on 3rd downs. Once again I looked at the statistics and found that Lucky has turned 8 of his 13 third down carries into first downs. That's a third down conversion percentage of 61.54%.

So how does that stack up nationally? Below we see the Top 10 nationally for running backs in terms of 3rd down conversion percentage (Again minimum of 10 carries). Currently Lucky sits 9th nationally in this category.


These numbers tell me that Lucky's contributions are being overlooked by many of us (myself included). He's proven so far that he can come up big when the offense needs yards and we haven't even talked about his ability to catch passes out of the backfield. To help illuminate this part of his game I also examined his receptions on third down.


I have to admit, I was surprised to see how infrequently we've thrown to Lucky on third down. However, he has had some success proving that he must be accounted for on every down, and is always a danger to move the chains for the Husker offense.

Zone Blocking and Nebraska’s Running Game – Pt. II

Here is the second part of my look at Nebraska’s zone blocking schemes and their impact on our running game. If you missed part one, just look down the page, you idiot!

Our Bread and Butter

For all of Bill Callahan’s offensive acumen and 1,200-pound playbook, his playcalls in the running game are decidedly unimaginative. If you’ve watched any Nebraska games over the past few years you have been inundated with the stretch play. The stretch play is a major component of a zone blocking scheme. With the stretch play you are trying to force the defensive front to flow and to stretch horizontally so you can create seams. The idea is that the running back will generally head off-tackle looking for a seam between the tackle and the tight end or even outside of the TE depending on the style of defense you’re facing. For this to work the offensive line must again be in tune with the goal of getting bodies on the second level of defenders to help spring the running back.

The tightend (or tightends in Nebraska’s case) are key to the success of the stretch play. The TE must recognize the type of defense end he is facing and adjust his blocking accordingly. In some cases, he will merely attempt to seal the edge, forcing the running back to bounce aggressively the outside. This is especially useful when facing a strong, tough DE. If the DE is aggressive, quick and committed to getting up field, the TE may let him go that way while forcing him far to the outside. This allows the RB to cut up right off of the block of the tackle.

Here’s a diagram of the stretch play with blocking assignments included.


Again you can see that the RB is going to need patience to see where the lane develops and how the TE blocks the defensive end. As you’ve probably noticed, the stretch play is fairly useless when the running back is forced to run up the backs of his offensive linemen, or worse yet when the offensive linemen are forced back into the back’s running lane. For good examples of both see the USC game.

Why Stick With It?

You might wonder why Nebraska remains so committed to the stretch play even when it fails to produce consistent gains and often looks poorly executed. Callahan has a very good reason for this. Take a look back at the diagram and see what the QB is starting to do after handing off the ball to the running back. If you’re paying attention you’ll see the makings of a nice play-action bootleg. And that’s the true value of the stretch play to Nebraska’s playbook.

If you’ve ever watched the Indianapolis Colts a major part of their passing game is the bootleg off the fake stretch play. After taking the snap, Peyton Manning takes a couple of steps to his right or left and then starts to work his magic. A master of execution, Manning either gives the ball to the back or pulls it back, hides it and works a play-action pass. Nebraska has been doing more and more of this with Sam Keller and the stretch running plays set it up perfectly.

By setting the bootleg up with the stretch play you are trying to make the linebackers somewhat hesitant. If things go as planned, the linebackers sell out for the run which opens up a lot of space for Maurice Purify or Terrence Nunn on crossing routes. But for this to occur, you again need everyone on the same page. The quarterback needs to help set up the play action by carrying out the bootleg even on the stretch running plays. He also needs to master the sleight of hand necessary to fool the defense and giving himself time to throw. The offensive line also plays a key role, because defenders should be watching them instead of the QB in order to determine if the play is a run or a pass. As a result, if they sit back on their heels immediately to pass block, all of the faking in the world, isn’t going to convince the D that a run is coming. On the other hand, if they show the same zone scheme (while avoiding going downfield) it improves the run fake and helps to keep the hands of the defensive linemen down preventing tipped passes.

Here we see examples of some pass patterns that can emerge from the bootleg action set up by the stretch play.


Notice the options the QB has off of this play. If an aggressive set of safeties gets too far upfield, Keller can throw over the top of them to Purify or Sean Hill. If the linebackers bite on the run, he’ll have Phillips crossing over the middle into the space they vacated. If he needs an outlet or only a few yards (think 3rd and short) he’ll have Nunn out in the flats. Notice that sending Nunn in motion into the formation sets up the run even more.

Now remember, each time you see this particular bootleg play-action pass have success, you can take heart in knowing that all of those stretch plays for short gains did have a purpose.

Zone Blocking and Nebraska's Running Game - Pt. I

With a big game coming up this weekend Nebraska fans seem more than a little concerned about the Husker running game. After a quick start against Nevada, Nebraska has been extremely inconsistent picking up yardage on the ground. This has put a lot of pressure on Sam Keller and the passing attack. The ineffective running game has also helped to account for the amount of time the defense has spent on the field. When you’re not chewing up yards and time with a power rushing game, you’re not going to control the ball. And let’s face it, while time of possession is generally a useless statistic, a TOP advantage does mean a rested defense.

One of the first things that sticks out with the running game under Callahan’s WCO is the use of zone blocking schemes. While I’ve heard people banter about the relative utility of such schemes, I’ve rarely heard the topic discussed intelligently among Husker fans. Let’s try to change that if we can. So here is my faithful attempt at introducing you to zone blocking and how it might impact Nebraska’s running game.

Drive Blocking

First off let’s start with a standard for comparison. Teams that don’t utilize zone blocking schemes instead rely upon “man” or “drive blocking”. In this scheme a lineman is responsible for an individual, and the play is designed for a running back to hit a particular hole. So as a lineman your job is pretty simple: If you have a man on you drive him off the ball. If you don’t have a man on you block down on the first man inside. Add pulling guards for trap plays and sweeps, and you essentially have something similar to what Nebraska’s option offense did for decades.

Zone Blocking

Zone blocking is a different animal. This scheme involves a lineman blocking an area instead of a designated defensive player. If multiple linemen are blocking an area one can then break off and block into the second level. Generally a lineman in this system blocks the man on them if they are covered, and if you don’t have a man on you, then you double team with the person next to you on the play side of the formation. One of the key tenets of zone blocking is lateral movement of the offensive linemen as a unit. This should create some natural seams or gaps in the defense for the running back then to exploit.

As Bob Davie explains:

“Zone blocking in the running game is when two or three offensive linemen work in tandem as opposed to each offensive lineman having a specific, predetermined man to block. Zone blocking involves the center, guard, tackle and tight end working in combination to block an area with an emphasis on double-teaming the defensive linemen who are aligned on the line of scrimmage.

The concept is for two adjacent linemen to come off in unison and attack a defensive line to the play side or to the side the ball carrier is going. The advantage, as opposed to man blocking, is that you create a double-team with two players blocking one defensive lineman. This allows the offensive linemen to be aggressive because he knows he has help if his defensive lineman was to pinch inside. It also provides movement at the point of attack, which can open creases for the running back.

Zone blocking initially starts out as a double team at the point of attack on the down defensive linemen, but the beauty of it is that one of the offensive linemen will leave to attack the linebacker while one stays to take over the defensive lineman. The key is for the two offensive linemen working in unison to double-team the defensive lineman to decide who and when one of them will leave to block the linebacker.”

Keys to Zone Blocking

In addition to moving laterally or horizontally, it is also crucial that the offensive linemen keep their shoulders square to the line of scrimmage. If they open up their shoulders at all, it can create a seam for the defense to get penetration and disrupt the play before it starts. This is where I’ve really seen breakdowns in Nebraska’s offensive line. Often times it is just a matter of getting beaten off the ball even slightly that results in the shoulder turn and subsequent lane for defenders. Another key is the communication and teamwork that must occur between the offensive linemen. For one, the linemen don’t know who they will block prior to the snap. Instead, they choose who to block after the play begins. Therein lies the difficulty of zone blocking. Each lineman must work in unison to pick out the right players to block in the few lightning-fast seconds during which a play takes place. Since they are completely dependant upon one another, a missed block by just one offensive lineman often causes the play to fail. This is where injuries, position swapping or a lack of quality practice time can really hurt an O-line.

But the offensive line isn’t the only key to a successful zone blocking scheme. A lot of responsibility also falls on the shoulders of the running back. Remember that with zone blocking, the offensive lineman all are moving laterally. This movement should create lanes or gaps for the running back. But because the linemen are working in unison the hole may open up anywhere along the line of scrimmage. This can work to give the running back multiple options, but relies strongly on his ability to pick the best running lane from these options. Here’s where I notice some problems with Marlon Lucky. It is clear that he has struggled at times to find or pick the right running lane. As a preseason article noted:

“He [Lucky] encountered a difficult time adjusting to school, to being far away from home, to the Huskers’ complex West Coast offense. He especially had trouble learning the blocking schemes, pass routes as well as the “zone” running plays, said Brad Ratcliffe, his former high school coach.”

It's extremely important for Lucky to continue to stay patient and let the zone develop, but it's also necessary that as soon as he sees a crease – to accelerate through it. Here’s where we often see Lucky hesitate. And that hesitation is costly. A zone blocking scheme relies on the running back taking what he can get — he can’t dance around waiting for a hole to open. He needs to be agile, authoritative, and possess good instincts. Nothing fancy, just try to gain positive yardage. Lucky can also improve on finding the elusive cut-back lane. Often times the open lane is created on the backside of the play, allowing the running back plenty of room to cut back away from the pursuit of the defense. But if the running back misses this lane, the chances for a big play diminish. Brandon Jackson was a master at finding and exploiting the cutback lanes on zone running plays. We desperately miss that type of natural ability. Overall, these types of plays take a lot of repetition in practice to run well, and the reps then should help the running back understand when and where to expect those creases to open up.

Perhaps surprisingly, the quarterback also plays a key role in a zone blocking scheme. His job is to get the ball to the running back as deep and as quickly as possible. The quicker and deeper the QB gets the ball to the running back, the better angle he will have for any potential running lanes or gaps in the defense.

So there's your introduction to zone blocking. Stick around for some additional information later this week.

2007 Offensive and Defensive Efficiency

Might as well take a quick look at how Nebraska is stacking up in terms of our offensive and defensive efficiency, thus far in 2007.

Remember offensive efficiency is measured by way of the Scoreability Index. The Scoreability Index is obtained by dividing a team's total yards by total points scored, yielding Yards Per Point Scored. A team that ranks high on the Scoreability Index has the offense that scores most efficiently, marching off a relatively small number of yards for every point it scores.

Nebraska currently has a Scoreability Index of 13.68 which ranks 56th nationally. That means Nebraska is currently scoring one touchdown for every 82 yards of offense they generate. To put this in perspective, a year ago we scored on TD for every 81 yards of offense we generated, so we can call that a wash.

When looking at how the Big 12 stacks up, you might be surprised.

1. Oklahoma
2. Texas A&M
3. Kansas
4. Kansas State
5. Texas
6. Texas Tech
7. Missouri
8. Nebraska
9. Oklahoma State
10. Baylor
11. Colorado
12. Iowa State

Nebraska has just the 8th most efficient offense in the conference. Interestingly that puts the Huskers just one spot below the high powered offense of Missouri. Things should be interesting in two weeks.

Defensive efficiency is measured by way of the Bendability Index. This is the first stat that chronicles the phenomenon of the "bend-but-don't-break" defense. The Bendability Index is obtained by dividing a team's total yards allowed by total points allowed, yielding Yards Per Point Allowed. A team that ranks high on the Bendability Index has the defense that opponents must work hardest to score upon.

You can probably guess how ugly this one is. Nebraska currently has a Bendability Index of 14.03. So far, Nebraska's opponents have had to march just 84 yards to score the equivalent of a single touchdown. A year ago the Blackshirts forced teams to generate 108 yards of offense to score the equivalent of one TD. For those claiming this is the "worst Husker defense I have ever seen" you'd be almost right in terms of defensive efficiency. Cosgrove's 2004 defense was actually worse. That team had a Bendability Index of 13.72 and opponents needed just 82 yards of offense to score the equivalent of one TD. This year's totals would, however, rank as the second least efficient defense since the Osborne Era began.

When looking at the Big 12, things are darn right ugly. All I can say is thank God for Iowa State.

1. Kansas
2. Oklahoma
3. Missouri
4. Texas
5. Kansas State
6. Baylor
7. Texas A&M
8. Colorado
9. Oklahoma State
10. Texas Tech
11. Nebraska
12. Iowa State

But after looking at these numbers I actually feel better about the defense and worse about the offense. While Sam Keller and the offense are racking up yards, we aren't putting up enough points to show for all of that work. That type of inefficiency will come back to haunt us in conference play. Especially if we are going to have to outscore everyone.

Defensively we are obviously bad, but most of the teams going all the way back to the Osborne era had a game or two where the defense imploded. Those games impacted the overall defensive efficiency of the team, but didn't necessarily result in losses. At the very worst, if the defensive numbers continue at this rate we should finish somewhere between the 2002 team and the 2004 team. In other words, we could expect about six wins. Ouch.

Not this again...

Well, we're back to this again where I become Callahan’s biggest defender on a fourth down playcall. What is so hard to understand? There was no doubt in my mind that we were going to go for it. Callahan is a gambler when it comes to fourth down. He is going to take a risk if he feels the payoff outweighs the potential costs of such a move. Perhaps he is familiar with the idea, presented once again for clarity by the Football Commentary folks that coaches punt way too often on fourth down, even when going for it would have been in their best interest.

The best their tables provide is the opponent’s 40-yard line with 3 minutes to go and a 3-point lead. Again we were on the 35 with 2 minutes to go. Anyway, the table tells us that Callahan should have believed the play would have a 60% probability of picking up the first down in order to come to the conclusion that we go for it rather than punt. So if he felt 6/10 times in that situation we pick up a first down – we go for it.

One more thing to consider we needed two yards for the first down. On fourth and two a year ago we went for it, and ran the ball twice. Both of those attempts led to first downs. Don’t think that Callahan isn’t aware of that success benchmark from 2006.

I know what you would have done in that situation. You would have punted. Callahan won’t. Just come to terms with that please people.

Nevada Game Analysis - Part I

Ed. Note - Here is the first part of my Nevada breakdown. For a nice season opening comparision, be sure and check out the Louisiana Tech breakdown from 2006. Part II of the analysis will include personnel and formation tendencies as soon as I have a chance to watch the game again.


Date – September 1, 2007
Location – Memorial Stadium, Lincoln, NE
Final Score – Nebraska 52 – Nevada 10

Key Stats Check

Category	Nebraska	Nevada
First Down (+4) Efficiency	30/46 (65.2%)	9/23 (39%)
Red Zone Efficiency	7/8 (88%)	1/1 (100%)
Rushing Explosive Plays (+12)	8	3
Passing Explosive Plays (+16)	6	4
Turnover Margin	0	0
Passing Efficiency	131.18	59.53
3rd Down Efficiency	7/15 (47%)	1/13 (8%)
4th Down Efficiency	1/2 (50%)	1/1 (100%)
Total Offense	625	185

Nebraska was extremely efficient on first down against Nevada. They gained 4+ yards on 65.2% on their first down plays. This goes a long ways toward keeping the team on schedule with regards to down and distance. In contrast, Nevada managed 4 or more yards on 1st down just 39% of the time. As always, the better success you have on first down the fewer 3rd and long situations you will face.

On third down, Nebraska converted 7/15 (47%) third down opportunities against the Wolfpack. That is just slightly above the 2006 season average of 45% and far better than 2005 when the Huskers converted just 33% of the their 3rd down chances. The Husker defense shut down Nevada on 3rd down holding them to a dismal conversion rate of 7.7%. Only Penn State had a better defensive third down efficiency rating in week one.

The Huskers did an amazing job in the red zone converting 7/8 (88%) opportunities. The one trip inside the twenty Nebraska didn’t convert concluded with a QB kneel to end the game. In other words, they were as good as you can get in the red zone. Nevada converted a field goal in its only visit to the red zone.

The Nebraska offense produced 14 explosive plays. On the ground, the Huskers produced 8 gains of 12 yards or more. Marlon Lucky accounted for five of those runs, while Cody Glenn, Major Culbert and Roy Helu each had one run of 12 yards or more. The passing game produced 6 explosive plays. Six different Nebraska receivers caught passes of 16 yards or more in the opener including freshman Mike McNeil. Overall, the Huskers outgained the Wolfpack 625 to 185. The 625 yards of offense was the third highest total of week one behind Oklahoma and Louisville. Quarterbacks Keller and Ganz combined for passing efficiency mark of 131.18. Coach Callahan will want that number to improve as the season progresses. Nebraska will be looking to improve over their 2006 turnover numbers, which saw them lose 17 of their 25 fumbles. Unfortunately the turnover margin against Nevada was a wash, but Sam Keller’s lone interception was returned for the Wolfpack’s only touchdown.

Drive Summary

Drive Starting Point	Drives	Points	Comments
-1 to -10	1	7	Series B - 12 Plays/94 Yds – Lucky 16 yd pass from Keller
-11 to -34	6	14	Series A – 3 Plays/1 Yd – Punt Series C - 3 Plays/1 Yd – Punt Series D – 7 Plays/42 Yds – INT Series G – 3 Plays/7 Yds – End of Half Series K – 6 Plays/87 Yds – Castille 2 yard run Series M – 9 Plays/84 Yds – Culbert 17 yard run
-35 to +35	7	31	Series E – 9 Plays/39 Yds – Lucky 1 yard run Sereis F – 9 Plays/54 Yds – Castille 1 yard run Series H – 7 Plays/65 Yds – Lucky 17 yard run Series I – 5 Plays/54 Yds – Lucky 3 yard run Series J – 7 Plays/28 Yds – FG Series L – 5 Plays/19 Yds – Turnover on Downs Series N – 12 Plays/47 Yds – QB Kneel/End Game
+34 to +11	0	0
+10 to +1	0	0
Totals	14	52	14 Drives, 7 TDs/1 FG Avg. Scoring Drive = 8 Plays/63.1 Yds

Nebraska got off to a bit of a slow start with two punts and an interception returned for a TD in the Huskers first four drives. After a 3 and out on the first drive of the season, Sam Keller led NU on a 12-play/94 yard drive capped off with a 16-yard completion to Marlon Lucky. After then finding themselves behind 10-7 the Nebraska offense got rolling in the second quarter. After a 46-yard Cortney Grixby kickoff return, Lucky scored his second TD of the game on a 1-yard run that ended a 9 play/39 yard drive. Just a few minutes later Quentin Castille scored his first career TD to give Nebraska a 21-10 advantage.

After 3rd quarter struggles doomed the Huskers in 2006, the Nebraska offense exploded in the third stanza against Nevada. The Huskers put together drives of 65, 54, 28 and 87 yards to bury the Wolfpack for good. The 28-yard drive was capped by a sight for sore eyes, in the way of a 46-yard field goal from true freshman Adi Kunalic.

Overall Nebraska scored TDs on 8/14 drives in the game. The average starting position for Nebraska’s drives was their own 32-yard line. Louisiana Tech’s average starting position was their own 25.

Run/Pass Split

Plays	Number	Yards	Avg.
Run Plays	70	413	5.9
Pass Plays	26	212	8.2
Total Plays	96	625	6.5

I didn’t know what to expect from Callahan’s gameplan for Nevada. I figured he might try to keep the ball on the ground, but wondered about the durability of our running backs. No way, no how did I imagine us running the ball 70 times in any game during Callahan’s regime. The 70 carries led the nation for the first week of the season and was 10 more than Air Force, which ranked second nationally in rushing attempts. Nebraska's 413 yards led the nation in week one. Seventy carries, an option or two and leading the nation in rushing? It feels like 1995 all over again.

Amazingingly Nebraska ran 96 plays against Nevada, which tied the Huskers with Memphis for the most plays run during the opening week. Led by Marlon Lucky, Nebraska averaged 5.9 yards per carry against the Wolfpack, which was the 20th best rushing average during week one. The Huskers averaged more than 5 yards a carry five times in 2006. The 8.12 yards per passing attempt was lower than I would like to see, but was still good enough for 28th nationally after the first game.


Play Selection By Down and Distance

Down	Distance	Runs	Pct.	Yds.	Passes	Pct.	Yds.
1st	& 10	30	65%	193	16	35%	139
2nd	& 1-3	5	83%	13	1	17%	15
	& 4-6	11	92%	90	1	8%	6
	& 7+	13	81%	62	3	19%	23
3rd	& 1-2	2	50%	3	2	50%	-6
	& 3-6	4	67%	14	2	33%	29
	& 7+	4	50%	13	4	50%	15
4th	& 2-3	1	100%	1	0	0	0
	& 4+	2	100%	10	0	0	0

As previously stated, Nebraska had great success on first down. Many coaches believe first down is the best down to keep an opponent off-balance by varying run and pass calls and keeping defensive coordinators guessing. Even with a heavy emphasis on the run in the game as a whole, Callahan still managed a 65%/35% run/pass split on first down. Surprisingly that is only slightly higher than the overall 2006 run/pass split on first down of 63% run/37% pass.

Nebraska ran the ball almost exclusively on second down against Nevada. Rushing plays accounted for 85% of the second down play calls against the Wolfpack. A year ago Nebraska ran the ball 58% of the time on second down and just 48% of the time on 2nd and 7+.

Third and short is another situation that Callahan attempts to keep the defense guessing. See the end of the 2006 Texas game in case you have forgotten. You’ll notice a 50/50 run/pass split on 3rd and 1-2 yards against Nevada. A year ago that split was 64% run/36% pass. That might be something to keep an eye on this year.

Nebraska 2006 - Dropped Passes

Well, I’ve finally finished charting all of the plays from the 2006 season including formations, personnel, shifts/motions, etc. I still haven’t figured out exactly how I want to utilize and share the information, however.

Until then I thought I’d start with an easy, but rarely tracked variable – dropped passes*.

First, the good news, as a team the Huskers had just 20 drops by my count. With 411 total passing attempts, that’s not bad at all.

Now for the scoreboard:

Frantz Hardy – 4
Brandon Jackson – 4
Terrence Nunn – 4
Mo Purify – 3
Nate Swift – 2
Todd Peterson – 2
Marlon Lucky – 1
JB Phillips - 1

I was surprised Hardy didn’t have more, as his seemed to stick out more and conventional wisdom around Husker Nation seems to paint him as our least sure-handed WR.

When I looked at which down the drops occurred on, Hardy’s drops became more noticeable. As a team, Nebraska had 7 drops on 3rd down plays. Those are absolute drive-killers, obviously and 3 of Hardy’s 4 drops just happened to occur on 3rd down. Ouch.

Next we have a breakdown of the drops by game:

Louisiana Tech – 3
Texas – 3
Oklahoma State – 3
Oklahoma – 3
Texas A&M – 2
Colorado – 2
Missouri - 2
USC – 1
Kansas – 1
Auburn – 1

Three losses at the top of the list, is I guess not surprising.

Now we have drops by quarter:

1st Quarter – 2
2nd Quarter – 3
3rd Quarter – 8
4th Quarter – 7

And just a little reminder Nebraska’s 2006 scoring by quarter:

1st 117
2nd 135
3rd 49
4th 120

So, there’s that.

Anyway, I’ll be trying to post interesting findings from now until the 2007 season realy gets going. Let me know if there are issues you are interested in from a year ago and I will try to see what the data shows.

*A note on “drops” – My job was a lot like the official scorer at a baseball game deciding between a hit and an error. Solid contact from a defender generally eliminated the scoring of a “drop”. Overall, I was probably fairly conservative in my decision-making.

Returning QBs and Preseason Favorites

The consensus seems to be that Missouri will win the Big 12 North, as most have them pegged as the preseason favorites. I tend to agree with this assessment for the time being. When I look at both teams on paper and examine the schedules I see Missouri as having a slight advantage over the Huskers.

One of the key areas I focused on in my assessment of the two teams was the quarterback position. Don’t get me wrong, I’m elated to have Sam Keller in the scarlet and cream. However, we have to remember that the guy has just eight career starts and has appeared in just 20 games. Missouri on the other hand, has Chase Daniel who although only a junior, has already started 13 games in his career. Daniel knows what it takes to QB a Big 12 team. While Keller was busy garnering the Scout Team MVP, Daniel was earning 2nd-Team All-Big 12 from the coaches.

I’m not the only one to use the QB position as a key measuring stick for my prognosticating. Coach Callahan addressed that very issue Monday at the Big 12 Media Days. He said:

“Well, my understanding is that the Big 12 writers essentially pick the team to win the division predicated on a number of factors. And the first factor is the quarterback. And since they have a starting quarterback that’s established in their program that's been productive, I can see where that's going.

Personally, no, I don't agree with it. But I love our football team and I think they're capable of doing some great things. And I understand how it all works and why people make the decisions and do the things that they do. And motivation -- we've got plenty of motivation with Nevada, you know, in the opening game. during the regular season. During the 9-3 season we did do a good job like I said with the one faltering -- we faltered against Texas late in the game.”

But before I put all of my preseason prediction eggs in one basket, I wanted to determine if a returning quarterback really mattered in college football. Thankfully, I didn’t have to do the analysis myself. Matt at Statistically Speaking had already done that for me.

I’ll try to briefly describe what he found.

First,

“Teams with a returning experienced quarterback had a collective record of 375-357 (.512) in 2005. When their experienced quarterbacks returned in 2006, their combined record jumped to 469-337 (.582). That's an increase of roughly 7 percentage points in winning percentage.”

Likewise,

Teams who lost their quarterbacks after 2005 had a collective record of 341-309 (.525) in 2005. When they lost their quarterbacks, they regressed to a combined 316-384 (.451) in 2006. That's a decrease of roughly 7.4 percentage points in winning percentage.

You’ll obviously notice that the gain in winning percentage among teams that returned their quarterback is almost equal to the losses in winning percentage of teams that lost their quarterback. What a coinky-dink.

In Part II of his QB analysis Matt stripped away some riff-raff by limiting the teams’ performances to conference play.

Here are the highlights of those findings:

The teams (62 total) that returned an experienced quarterback in 2006:
Went a collective 238-248 in conference play (.490)
Equates to just under a 4-4 record in a standard 8-game conference schedule.

In 2006, those same teams improved to 269-223 in conference play.
This is a winning percentage of .547 and equates to a 4.37-3.63 record in a standard 8 game conference season.
This is an improvement of roughly 1/2 game in the conference standings.

The teams (53 total) that did not return an experienced quarterback in 2006:
Went a collective 214-204 in conference play in 2005 (.512).
Equates to a conference record of 4.10-3.90 in a standard 8 game conference season.

In 2006, those same teams regressed to 188-234 in conference play.
This is a winning percentage of .445 and equates to a conference record of 3.56-4.44 in a standard 8 game conference season.
This is a regression of a little more than 1/2 game in the conference standings.

He also looked at the percentage of teams that improved/declined by a certain number of games. He found:

Of those teams returning an experienced QB:
21 teams (33.9%) improved by at least 2 games in the conference standings.
8 teams (12.9%) improved by at least 3 games in the conference standings.
13 teams (21%) declined by at least 2 games in the conference standings.
5 teams (8.1%) declined by at least 3 games in the conference standings.

Of those teams not returning an experienced QB:
10 teams (18.9%) improved by at least 2 games in the conference standings.
5 teams (9.4%) improved by at least 3 games in the conference standings.
21 teams (39.6%) declined by at least 2 games in the conference standings.
10 teams (18.9%) declined by at least 3 games in the conference standings.

Matt concludes by noting:

“I will say this, it appears that it may not be as valuable to return your starting quarterback (12.9% that returned theirs improved by at least 3 games and 9.4% that did not improved by at least 3 games) as it is damaging to have him leave (more than double the chance--18.9% to 8.1% of declining by at least 3 games).”

Now, I know Sam Keller is considered by many to be a returning quarterback even after sitting a season out and entering a new system. While I agree that his situation doesn’t exactly fit with this model, we have a talented QB who is new, and raw in Callahan’s version of the WCO. The bottom line is that we just don’t know how it will play out. And frankly that’s what makes this upcoming season so great – all of the unknowns. But for now, I stand my preseason selection of Missouri to win the Big 12 North. And I’ll continue to stand by that pick for at least the next few days.

Nebraska and Offensive Efficiency - Part III

Today we’ll look briefly at the historical data concerning Nebraska’s Scoreability Index over time. You can see the entire spreadsheet here. Have fun.

Here are the Top 10 seasons since the Osborne era began in terms of offensive efficiency.

1. 1988 - 9.68
2. 1996 - 9.90
3. 1980 - 10.00
4. 1983 - 10.51
5. 1986 - 10.66
6. 1997 - 10.91
7. 2000 - 11.09
8. 1993 - 11.10
9. 1992 - 11.29
10. 1999 - 11.45

Interestingly only one of our National Championship teams makes the list. This is due in part (I think), to the ways in which certain Nebraska teams dominated their competition. If we consider the 1995 team, which blew out pretty much everyone, you get to a point where that team was just racking up yards with its scrubs, but then taking knee and refusing to put up points. That would certainly hurt its efficiency as calculated by this method. That’s at least my best guess to explain this.

Now we have the worst ten seasons since the Osborne era began in terms of offensive efficiency.

1. 1973 - 17.70
2. 1977 - 15.67
3. 1995 - 14.53
4. 2004 - 14.53
5. 1979 - 14.05
6. 2003 - 13.93
7. 1981 - 13.79
8. 2002 - 13.64
9. 1994 - 13.62
10. 2006 - 13.56

First thing that jumps out at me is that we see both 1973 and 2004 on the list. What do these two seasons have in common? Breaking in a new head coach. We also see that the last two seasons of the Solich era also make this list. This should surprise absolutely no one who was actually paying attention.

Is anybody surprised to see that 2006 made the Top 10 in least efficient offensive performances? In some ways it is unexpected but our performances against teams like KSU, and ISU involved pretty big chunks of yardage and not a lot of point production. That adds up pretty quickly when we use this methodology.

Nebraska and Offensive Efficiency - Part II

In the first part of this series I introduced to the concept of the Scoreability Index. I explained the value of this statistic as a measure of offensive efficiency and attempted to prove that it was worthwhile to track in college football.

In Part II, I will take a closer look at the national rankings in this statistic, with particular attention paid to Nebraska’s offensive efficiency.

First, you can check out the entire Scoreability Index spreadsheet here. This should give you access to how this statistic is calculated and what the rankings look like for all 119 Division I-A teams.

Let’s start by looking at the Top 10 teams in the Scoreability Index:

1. Boise St. 10.60
2. Texas 10.90
3. Ohio St. 11.11
4. Virginia Tech 11.42
5. Rutgers 11.59
6. Oklahoma St. 11.63
7. Pittsburgh 11.72
8. SMU 11.80
9. West Virginia 11.88
10. Nevada 11.89

Right away, you will notice a few surprises, including Pittsburgh, SMU(?) and Nevada. However, all of the teams in the Top 10 had a .500 record or better and combined for an overall record of 94-34 (.734).

Overall, Boise State had the most efficient offense in 2006. The undefeated Broncos scored one touchdown for every 64 yards of offense they generated. You can watch their proficient offense at work in these Fiesta Bowl highlights.



The least efficient offense in 2006 belonged to the Golden Panthers of Florida International. FIU managed just one touchdown for every 146 yards of offense they generated. That’s exactly how you go 0-12. No wonder they was always fightin'.

Now let’s turn our attention to the Huskers. Nebraska finished a modest 43rd nationally in the Scoreability Index, obviously meaning they were the 43rd most efficient offensive unit in 2006. The Huskers produced 428 points, and 5804 yards. This produced a Scoreability Index of 13.56. Thus, the Huskers scored one touchdown for every 81 yards of offense they generated.

If we look at this statistic on a game-by-game basis (this is a less exact science), we can see our offensive efficiency in each match-up. Let’s start with our least efficient offensive performance. I managed to guess this one, and I have a feeling you might have as well. That cold night in KC for the Big 12 Championship, turned out to be our least efficient offensive performance and by quite a margin. In that game, the Huskers generated just 7 points off of 366 yards. That equates to a Scoreability Index of 52.29. In other words, Nebraska needed to produce 314 yards for the equivalent of one TD (six points) against the Sooners. Our other inefficient offensive performances came against USC (21.10), Texas (17.00), KSU (16.95), and Auburn (16.43).

Nebraska’s top three offensive efficiency performances came against non-conference opponents Nicholls St. (8.89), Troy (10.66), and Louisiana Tech (11.92). The Huskers’ most efficient offensive effort in conference play came against Missouri (12.32). The only odd finding overall related to the Scoreability Index came in the Kansas State game. That was the Huskers least-efficient offensive performance in which they managed a win. If we think back to the findings for the Bendability Index, we will notice that the KSU game just happened to be our most efficient defensive performance of the year. See how these statistical measures interplay?

We can put the performance of Nebraska in perspective by examining how the Big 12 shakes out in terms of the Scoreability Index in 2006.

1. Texas 10.90
2. Oklahoma St. 11.63
3. Oklahoma 12.17
4. Kansas 12.90
5. Baylor 13.36
6. Nebraska 13.56
7. Texas Tech 13.80
8. Kansas St. 13.84
9. Missouri 14.15
10. Texas A&M 14.27
11. Iowa State 16.88
12. Colorado 17.84

There are a few surprises here, but first things first. When discussing the Bendability Index, I noted that while Nebraska had a more efficient defense in 2006, the Sooners still won the head-to-head matchup. Now we know a little more about why. Overall, the Sooners offense (even with a WR at QB) was more efficient than that of the Huskers. In addition, see above for an explanation of just how awful our offense was in the Big 12 Championship Game.

Another surprise is Baylor listed ahead of us. That stings obviously, but don’t be too quick to discredit the Scoreability Index as a viable measure. If we look at the teams ahead of us (and that we played in 2006) on this list, you’ll notice that we lost to all but one of them. The one game we won against a team with a better Scoreability Index was Kansas, and we needed OT to sneak by the Jayhawks at home. That trend actually applies to our entire 2006 schedule, as every team Nebraska lost to in 2006 had a more efficient offense than the Huskers.

Still think this Scoreability Index doesn’t matter?

In Part III of this series I will again take a look at Nebraska’s historical performance as it relates to the Scoreability Index.

Nebraska and Offensive Efficiency - Part I

Earlier I introduced to the Bendability Index, a measure of defensive efficiency and one of the "Stats That Matter" at Cold, Hard Football Facts. Today I want to switch sides of the ball and look at offensive efficiency. Cold, Hard Football Facts has a stat for that as well. This is measure is known as the Scorability Index.

According to the site:

Scoreability Index – This is the offensive counterpart of the Bendability Index. The Scoreability Index is obtained by dividing a team's total yards by total points scored, yielding Yards Per Point Scored. A team that ranks high on the Scoreability Index has the offense that scores most efficiently, marching off a relatively small number of yards for every point it scores. This effort is more important than total offense and, in many cases, more important than scoring offense. The Scoreability Index is not purely an offensive yardstick. It is, instead, a great barometer of team success. It is a function of many team-wide factors, including general offensive strength, defense and special teams proficiency, turnover differential and Red Zone offense.

To help explain how this variable works in the NFL, Cold, Hard Football Facts uses the incompetence of the Raiders offense:

Pity poor Oakland. The Raiders will not only go down as one of the most inept offenses in modern NFL history, scoring just 10.5 PPG and averaging a dreadful 4.4 yards everytime they dropped back to pass, they also wasted a lot of effort this season moving the ball up and down the field for no reason.

Oakland needed to generate 23.45 yards to score a single point this season. That's more than twice the effort expended by division rival San Diego, which needed just 11.87 yards to score a single point.

To put it in more concrete football terms, the Chargers scored one touchdown for every 71 yards of offense they generated. The Raiders scored one touchdown for every 140 yards of offense they generated.

As a result, one team has the best record in football. The other team has the worst record in football.

That’s a pretty telling statistic in the NFL, but what about in college football? To find out, I again constructed a spreadsheet ranking NCAA teams in terms of the Scoreability Index for 2006. Next I used SMQ’s methodology for determining the relevance of a particular statistic in CFB. This meant finding the winning percentage of the Top 20 teams in the Scoreability Index category, as well as the winning percentage of the Bottom 20 teams in the Scoreability Index.

According to SMQ this is important because:

“…the relevance of a statistic shouldn't be measured only by the relative success of teams that perform well in a given category, but also by the relative failure of those that don't.”

Next, I calculated what SMQ sees as the most relevant measure of this analysis, the relationship between the winning percentages on the high and low ends of the Scoreability Index. In other words, I subtracted the winning percentage of teams in the Bottom 20 of the Scoreability Index from the winning percentage of the teams in the Top 20 of the Scoreability Index to determine the relative disparity between these two groups. From a statistical standpoint, the greater the level of disparity, the more relevant the particular statistic. Or as a SMQ noted:

“the ‘most important’ category, it would follow, would be the one with the best records at the top, the worst records at the bottom and, therefore, the greatest disparity."

SMQ’s analysis (along with my own additional calculations) found the most relevant offensive statistics based on disparity to be:

Third Down Efficiency +.477
Total Offense +.473
Scoring Offense +.472
Yards/Pass Attempt +.389
Passing Efficiency +.377
Rush Offense +.360
Fourth Down Efficiency +.350
Pass Offense +.182
Time of Possession +.164

Calculating the disparity margin of the Scoreability Index produced a figure of +.485. This means that the Scoreability Index produces the most relevant offensive statistic in terms of winning percentage.

So, just to clarify again:

The Scoreability Index is obtained by dividing a team's total yards by total points scored, yielding Yards Per Point Scored. A team that ranks high on the Scoreability Index has the offense that scores most efficiently, marching off a relatively small number of yards for every point it scores.

This is another interesting statistic and I believe it makes sense to think about teams in terms of how hard they are working to put points up on the board. We also have some evidence that this statistic is relevant in CFB. In fact, it looks to be more important than some of the statistics folks around Nebraska continue to harp on way too much - most notably, Time of Possession and Rushing Offense. These two statistics just didn’t matter in college football in 2006. But the Scoreability Index did. In Part II of this series I will look at how the teams ranked nationally in terms of the Scoreability Index. I will also examine where Nebraska fits in with regard to this statistic.

Nebraska and Defensive Efficiency – Part II

In the first part of this series I introduced to the concept of the Bendability Index. I explained the value of this statistic as a measure of defensive efficiency and attempted to prove that it was worthwhile to track in college football.

In Part II, I will take a closer look at the national rankings in this statistic, with particular attention paid to Nebraska’s performance on this variable.

First, you can check out the entire Bendability Index spreadsheet here. This should give you access to how this statistic is calculated and what the rankings look like for all 119 Division I-A teams.

Let’s start by looking at the Top 10 teams in the Bendability Index:

1. Ohio State (21.96)
2. BYU (21.72)
3. Wake Forest (21.00)
4. Auburn (20.99)
5. Wisconsin (20.96)
6. Virginia Tech (19.95)
7. Boston College (19.81)
8. Penn State (19.78)
9. Louisville (19.65)
10. USC (19.52)

Teams in the Top 10 in this statistic had a combined record of 109-22 (.832). They won five conference championships and played in four BCS bowls. In their bowl games these teams then went 7-3 (Louisville and Wake played each other). Clearly this statistic has some clout.

Overall, Ohio State had the most efficient defense in 2006. The Buckeyes forced opponents to march 132 yards to score the equivalent of a single touchdown. The least efficient defense in 2006 belonged to Turner Gill’s Buffalo squad. Opponents needed to gain just 65 yards to score the equivalent of a single touchdown on the Bulls. Is it any wonder the team went 2-10 last season?

Now let’s turn our attention to the Blackshirts. Nebraska finished a respectable 15th nationally in the Bendability index, obviously meaning they were the 15th most efficient defensive unit in 2006. The Huskers surrendered 256 points (2nd highest total in the Top 20), and 4646 yards. This produced a Bendability Index of 18.15. Thus, the Blackshirts forced opponents to march 109 yards to score the equivalent of a single TD last season.

If we look at this statistic on a game-by-game basis (this is a less exact science), we can see our defensive efficiency in each match-up. Let’s start with our least efficient defensive performance. Any guesses? My first thought was Oklahoma State and our implosion in Stillwater. Close, that was our second least efficient game. The least efficient defensive performance actually came in the Cotton Bowl against Auburn. The War Tigers managed 17 points on just 178 yards. That equates to a Bendability Index for the game of 10.47. In other words Auburn needed to drive just 63 yards for the equivalent of a single touchdown in the Cotton Bowl. Clearly the outcome was also decided by Nebraska’s offensive inefficiency and the dreaded fake punt call. As I said other inefficient defensive performances came against OSU (BI = 12.1), USC (14.3), OU (14.62), and Texas (15.82). All losses.

Nebraska’s most efficient performance came against Kansas State. Rojo actually made mention of this on HuskerPedia. The Wildcats put up 294 yards, but managed just 3 points. That works out to an incredible Bendability Index of 98.00! Again, if we extrapolate from that figure we find that it would have taken KSU driving 588 yards to put up the equivalent of one TD. Quick note – the Troy game had to be taken out, as the shut out made calculating the Bendability Index unpossible (stupid zeros and division). Most of our other efficient defensive performances came against non-conference opponents. In the Big 12, the defensive was particularly proficient against ISU and Colorado. The rest of the Big games involved performances that were less efficient than the season average (BI < 18.15).

We can put the performance of the Blackshirts in perspective by examining how the Big 12 shakes out in terms of the Bendability Index in 2006.

1. Nebraska 18.15
2. Oklahoma 16.61
3. Missouri 16.39
4. Texas 16.24
5. Texas A&M 15.71
6. Colorado 15.32
7. Kansas 14.83
8. Kansas State 14.54
9. OSU 14.21
10. Texas Tech 13.30
11. ISU 12.76
12. Baylor 12.53

Not surprisingly the two teams that met in the conference championship game fill the top two spots in the conference in Bendability Index. The order might be somewhat surprising to some, given the salty reputation of OU’s defense and their success in the head-to-head match-up. If I had to guess the reason for this discrepancy, I would say that Oklahoma enjoyed a more efficient offense in 2006 than did Nebraska. Again this might surprise you, but stay tuned and I’ll address this is in a later post.

The next level of teams includes three more you would expect in Missouri, Texas, and Texas A&M. Texas had problems in the defensive backfield, which accounted for a lot of yards, but their ranking is about what I expected. Missouri, despite the attacks on Pinkel, actually put up defensive numbers that were quite comparable to Nebraska’s a year ago. The team with the better defense between these two schools in 2007 will likely win the North (really going out on a limb there!). The biggest surprise is 2-10 Colorado at 6th in Big 12. But don’t forget that the Buffs’ defense was pretty stingy in our match-up a year ago. We relied on some key trick plays to account for both yards and points. Their offense, however, was absolutely horrible and was one of the least efficient in the nation. Oklahoma State and Texas Tech were two other teams that relied more on high-powered offenses which allowed for less efficient defensive play. Iowa State and Baylor round out the conference. They are, well, Iowa State and Baylor.

Ok, I think I’m starting to ramble a bit. Can you tell my summer teaching duties are over? Very nice. Part III of this series will put Nebraska’s defensive efficiency into historical context. How much history is yet to be decided. I don’t like to give people data that allows them to compare across the various coaching staffs. So I might just focus on the three years of the Callahan regime. We’ll see.

Nebraska and Defensive Efficiency - Part I

As you can probably tell, I am fascinated by the world of sports statistics. I spend many evenings banging out spreadsheets filled with stats and variables related to Nebraska football and college football as a whole. I am constantly searching for some way of quantifying success/improvement or of determining which statistics matter and which don’t.

Recently I’ve been thinking more about the defensive side of the ball. On Monday I noticed that the poster Rojo had started a thread at both HuskerPedia and the Red Sea Scrolls about Nebraska’s Pass Defense. As always, Rojo presented some great information. This post actually led to very little meaningful discussion on HuskerPedia, although I was surprised it didn’t quickly become a Pelini – Sanders – McBride- Cosgrove – Elmassian debate. Side note – HuskerPedia currently has a poll question asking who fans would rather have as their DB coach and over 70% support Marvin Sanders. That’s a lot of support for a guy who is currently out of work. But I digress.

Anyway, Rojo opened his post with this statement:

Let’s be clear: The most important thing for a defense is keeping the other guys out of the end zone.

Technically, the most important thing is winning, but I agree that keeping the other team out of the endzone goes a long way towards this. While I enjoyed Rojo’s information, I was thirsty for more. That brought me back to some data I had put together some time ago. This data related to the "Stats That Matter" analysis at the Cold, Hard Football Facts, an NFL site. One of the most interesting statistics they track is the Bendability Index. According to the site:

Bendability Index – This is the first stat that chronicles the phenomenon of the "bend-but-don't-break" defense and provides a measure of defensive efficiency. The Bendability Index is obtained by dividing a team's total yards allowed by total points allowed, yielding Yards Per Point Allowed. A team that ranks high on the Bendability Index has the defense that opponents must work hardest to score upon. This effort is more important than total defense and, in many cases, more important than scoring defense. The Bendability Index is not purely a defensive yardstick. It is, instead, a great barometer of team success. It is a function of many team-wide factors, including general defensive strength, offense and special teams proficiency, turnover differential and Red Zone defense.

This is exactly what I was looking for, a measure of defensive efficiency. In their discussion Cold, Hard Football Facts notes that this statistic is quite telling in the NFL.

“NFC North champion Chicago not only gave up the fewest points (202) in football last year, it topped the Bendability Index, too. The Bears forced opponents to march 134 yards to score the equivalent of a single touchdown. Chicago boasted more than a tough defense; they fielded a ferociously efficient defense.”

In addition, if we measure teams by the Bendability Index:
The top seven defenses made the playoffs.
9 playoff teams ranked in the Top 10 (and 10 in the Top 11).
The playoff teams ranked from No. 1 to No. 17 – the narrowest spread.

But before I got too excited, I needed to determine if the statistic carried as much weight in college football. To do this I first constructed a spreadsheet ranking NCAA teams in terms of the Bendability Index for 2006. Next I used SMQ’s methodology for determining the relevance of a particular statistic in CFB. This meant finding the winning percentage of the Top 20 teams in the Bendability Index category, as well as the winning percentage of the Bottom 20 teams in the Bendability Index.

According to SMQ this is important because:

“…the relevance of a statistic shouldn't be measured only by the relative success of teams that perform well in a given category, but also by the relative failure of those that don't.”

Next, I calculated what SMQ sees as the most relevant measure of this analysis, the relationship between the winning percentages on the high and low ends of the Bendability Index. In other words, I subtracted the winning percentage of teams in the Bottom 20 of the Bendability Index from the winning percentage of the teams in the Top 20 of the Bendability Index to determine the relative disparity between these two groups. From a statistical standpoint, the greater the level of disparity, the more relevant the particular statistic. Or as a SMQ noted:

“the ‘most important’ category, it would follow, would be the one with the best records at the top, the worst records at the bottom and, therefore, the greatest disparity."

SMQ’s analysis found the most relevant defensive statistics based on disparity to be:

*Scoring Defense: + .546
Passing Efficiency Defense: + .467
Rush Defense: + ..448
Total Defense: + .396
Third Down Efficiency Defense: + .375
Fourth Down Efficiency Defense: + .253

*SMQ did not actually calculate the relevance of scoring defense. I was able to throw it together and come up with this figure.

When I calculated the disparity margin for the Bendability Index, I was surprised to discover it was + .522. In other words, Bendability Index actually appears to be a more relevant defensive statistic in terms of winning percentage than all but scoring defense.

So, just to clarify again:

“The Bendability Index is obtained by dividing a team's total yards allowed by total points allowed, yielding Yards Per Point Allowed. A team that ranks high on the Bendability Index has the defense that opponents must work hardest to score upon.”

I like this statistic and think we have some proof that it matters in CFB. In addition, it seems to add to the statistic of scoring defense by accounting for overall defensive efficiency or the number of yards necessary for a team to put up points on a defense. In Part II of this series I will look at how the teams ranked nationally in terms of the Bendability Index. I will also examine where Nebraska fits in with regard to this statistic.

Nebraska and Home Field Advantage

An interesting take on the concept of home field advantage at The Straight Dope of all places. The Straight Dope is a question and answer site run by Psuedonymous columnist Cecil Adams. If you have a question about just about anything, chances are The Straight Dope have attempted an answer.

Regarding home field advantage (HFA), The Straight Dope says:

What explains HFA? Several possibilities are often cited, including familiarity with home turf, no travel stress, and what football fans call "the 12th man," the home crowd. But establishing what's most important isn't easy. Take familiarity — one study of 7 baseball, 17 basketball, and 13 hockey teams that moved to new stadiums (without changing cities) between October 1987 and April 2001 showed a significant reduction in HFA in the season following the move. However, other studies purport to show that MLB teams do better in a new stadium. One clear-cut case of HFA arising from venue familiarity is the Colorado Rockies, who consistently display the largest differential between home and away records of any MLB team. All agree that's because only the Rockies are acclimated to high-altitude Coors Field.

Crowd effects are easier to demonstrate, at least in some sports. A study of more than 5,000 English soccer matches found that teams scored an average of 1.5 goals at home vs only 1.1 on the road, with the difference growing by 0.1 goals per 10,000 spectators. The researchers attribute this to cowed refs' giving the visitors more penalties. Schwartz and Barsky thought crowd effects explained why HFA for baseball and football was lower than for hockey (in the 70s anyway) and basketball — the latter two sports are invariably played indoors, where the noise is more intense. Travel stress is probably a minor factor, since HFA persists even among teams that are geographically close.

Whatever the reason, a home field advantage certainly exists in Lincoln.

Nebraska was 7-1 at home in 2006 and has won at least six home games in 17 of the past 19 seasons.

Nebraska is 116-11 at home in the last 18 seasons (since 1989), including a pair of losses against teams that went on to win the national championship–Colorado in 1990 and Washington in 1991.

Since 1986, only seven different schools have left Memorial Stadium with a victory (Colorado, Kansas State, Oklahoma, Southern Miss., Texas, Texas Tech, Washington).

During Nebraska’s run of success at home in the past 25 years, Nebraska has had three home winning streaks of 20 or more games.

Nebraska had a school-record 47-game home winning streak from 1991 to 1998, a 26-game home streak from 1998 to 2002 and a 21-game win streak in the early 1980s.

Nebraska has not been shut out at home since a 12-0 loss to Kansas State in 1968 (245 games), and has posted 40 unbeaten and untied home seasons.

All-time Nebraska is 481-129-20 (.779, 630 games, 117 years) in Lincoln.

The Huskers are 356-106-13 (.763, 475 games, 84 years) in Memorial Stadium (since 1923).

Ranking the Coaches Based on...Um, Coaching

I'm sure many of you remember Tom Dienhart's attempt at ranking all of the BCS coaches. Like most of Dienhart's columns the piece seemed to be based on little other than personal opinion. That's fine as he gets paid to have an opinion, but there had to be a more scientific approach to the endeavor.

Well, it turns out there was a better approach, like the one taken by LD at the The Corporate Headquarters of the San Antonio Gunslingers.

LD based his rankings on several key factors:

Longevity
National Titles
Conference Titles
Winning Percentage
Winning Percentage As Against School's Historic Winning Percentage

I've said it before, but this is another example of how the mainstream media gets outdone by bloggers. Anyway, you can see the spreadsheet of LD's rankings here.

Here are some of LD's comments related to Nebraska and Bill Callahan

Winning Percentage As Against School's Historic Winning Percentage:

Biggest upgrade by Dienhart from where a coach would be rated by this objective category: Bill Callahan (from 50th up to 21st).

Coaches upgraded by Dienhart by more than 10 spots (my guess at a reason, and here I don't consider a bad program as a good reason since it's already accounted for): Hawkins (small sample), Bobby Johnson (???), Bill Callahan (???), Mark Mangino (???), Greg Schiano (???), Jim Leavitt (Shouldn't be listed here - he's the only coach at the program, so his comparison to history is neutral), Houston Nutt (???), Lloyd Carr (title), Kirk Ferentz (???), Tom O'Brien (???), Tommy Tuberville (???, near-title?), Frank Beamer (longevity), Nick Saban (title), Mack Brown (title), Rich Rodriguez (???), Jim Tressel (title).

Looking at the various objective criteria, I think Dienhart overrates and underrates a few coaches, based upon their accomplishments.

OVERRATED: Mark Mangino, Bill Callahan, Bobby Johnson, Rich Rodriguez, Kirk Ferentz, Tom O'Brien.

UNDERRATED: Phil Fulmer, Ralph Friedgen, Mark Richt, Charlie Weis, Jeff Tedford, Les Miles, Tommy Bowden, Bret Bielema, Tyrone Willingham, Karl Dorrell, Bill Doba.

A few more specific nits to pick considering all the categories discussed:

Houston Nutt at #20 isn't defensible. Guys behind him that best or equal him in every category: Tedford, Richt, Leach, Friedgen, Fulmer, Tiller, Bielema, Miles. Nutt's objective rankings put him right in line with Tommy Bowden, whom Dienhart ranks 47th (though, arguably he shouldn't be that low).

Matt at Statistically Speaking also introduced another variable into attempts at rating coaches. He created a formula that looks like this:

Win % Last Season (50%) + Win % 2 Yrs Ago (20%) + Win % 3 Yrs Ago (10%) + .500 (20%)

The four components are winning percentage for the previous three seasons; with each season decreasing in importance as the distance from the current season increases and the final component is a winning percentage of .500 as teams tend to trend towards .500. Including this component ensures we don’t penalize coaches coming off undefeated seasons because improving upon a 100% winning percentage is impossible. Additionally, we don’t reward coaches who go winless because we assume they will improve at least marginally. Next we just subtract the team’s expected winning percentage from their actual winning percentage. This number is the coach’s rating.

Here are the best and worst coaches in each conference according to Matt's formula:

Best

ACC
Jim Grobe (Wake Forest) +.389

Big East
Greg Schiano (Rutgers) +.340

Big 10
Bret Bielema (Wisconsin) +.235

Big 12
Dennis Franchione (Texas A&M) +.215

Pac 10
Mike Riley (Oregon State) +.208

SEC
Rich Brooks (Kentucky) +.309

Conference USA
Todd Graham (Rice) +.296

MAC
Frank Solich (Ohio) +.271

Mountain West
Bronco Mendenhall (BYU) +.372

Sun Belt
Larry Blakeney (Troy) +.166

WAC
Dick Tomey (San Jose State) +.392

Worst

ACC
Chuck Amato (NC State) -.294

Big East
Randy Edsall (Connecticut) -.203

Big 10
Pat Fitzgerald (Northwestern) -.205

Big 12
Dan Hawkins (Colorado) -.367

Pac 10
Walt Harris (Stanford) -.354

SEC
Mike Shula (Alabama) -.185

Conference USA
Tommy West (Memphis) -.427

MAC
Shane Montgomery (Miami, Ohio) -.467

Mountain West
Chuck Long (San Diego State) -.181

Sun Belt
Darrell Dickey (North Texas) -.127

WAC
Jack Bicknell (Louisiana Tech) -.329

Obviously neither of these systems is perfect, but they have to be better attempts than what Dienhart and most pundits provide.

SDPI - Another Interesting Statistical Variable

In my continuing quest to continue to help bring college football into the Moneyball era I've run across another interesting football statistic. This one comes to you from the fine work of Statistically Speaking.

This variable is the Standard Deviation Power Index. This index originates from Eddie Epstein’s book Dominance. It focuses solely on conference play and looks at a team's points scored and allowed relative to the league average and standard deviation.

Statistically Speaking later provides an example of how SDPI is calculated:

The mean points scored and allowed for all ACC teams in conference play (championship game not included) was 162 points. The standard deviation for points scored was 35.97. The standard deviation for points allowed was 51.18. Coastal Division champ Georgia Tech scored 213 and allowed 155 points. Georgia Tech’s offensive SDPI was 1.42 = ([213-162]/35.97). Their defensive SDPI was .14 = ([162-155]/51.18). Their total SDPI was 1.55 (not 1.56 because the other two were rounded). In the 2006 ACC, that was good for third best.

As part of his SDPI project, Statistically Speaking broke down the conferences in a historical manner. He examined the Big 12 from 1998-2006. This is what Nebraska's SDPI looks like in graphical form for those particular years.



This is what he had to say about Nebraska's historical SDPI in the Big 12.

Frank Solich kept the Huskers near the top of the college football world (though not quite the heights reached under Tom Osborne) for four seasons. The wheels came off in 2002, but Solich seemed to reverse the teams trajectory in 2003 before being fired despite a 10-3 record. Bill Callahan took over in 2005 and promptly guided the Huskers to their first losing season since 1961. The Huskers improved and were an average team in 2005. They improved yet again in 2006 and may be on their way to recovering their place in the Big 12 pecking order.

First Place SDPI Finishes: 2000

You'll first want to keep in mind, the SDPI does not adjust for schedule strength for conferences such as the Big 12 where each team does not play each other and it ignores special teams which can play a significant role in both points scored and points allowed. However, this seems again like an interesting statistic that appears to correlate with performance at least to some degree.

I just wanted to introduce it to you today. I plan on getting into at a deeper level in the future.

2006 Game Analysis - Louisiana Tech

Date – September 2, 2006
Location – Memorial Stadium, Lincoln, NE
Final Score – Nebraska 49 – Louisiana Tech 10

Key Stats Check

Category	Nebraska	Louisiana Tech
First Down (+4) Efficiency	26/42 (62%)	12/23 (52%)
Red Zone Efficiency	5/7 (71%)	1/1 (100%)
Rushing Explosive Plays (+12)	5	2
Passing Explosive Plays (+16)	8	4
Turnover Margin	+1	-1
Passing Efficiency	175.24	105.33
3rd Down Efficiency	11/16 (69%)	5/14 (36%)
4th Down Efficiency	1/2 (50%)	0/0
Total Offense	584	305

Nebraska did an excellent job of moving the ball on first down against Louisiana Tech. They gained 4+ yards on 62% on their first down plays. This goes a long ways toward keeping the team on schedule with regards to down and distance. The better success you have on first down the fewer 3rd and long situations you will face.

Speaking of 3rd down, Nebraska converted 11/16 third down opportunities against the Bulldogs. This was a vast improvement over 2005 when the Huskers converted just 33% of the their 3rd down chances. The Husker defense shut down La Tech on 3rd down holding them to a conversion rate under 40%.

The Huskers also did a great job in the red zone converting 5/7 opportunities. However, turnovers in the red zone prevented two more scoring opportunities. Louisiana Tech converted a field goal in its only visit to the red zone.

The Nebraska offense produced 13 explosive plays. In the passing game, the tight ends had a breakout performance and Mo Purify grabbed his first career pass gaining 28 yards on a first quarter completion. On the ground, Brandon Jackson showed a glimpse of what would become a great 2006 season with a 25 yard TD run. Overall, the Huskers outgained the Bulldogs 584 to 305 and quarterbacks Taylor and Ganz combined for an impressive passing efficiency mark of 175.24. The Huskers also won the turnover battle in the 2006 home opener, despite several fumbles and a Zac Taylor interception in the 1st quarter.

How Nebraska Scored

Drive Starting Point	Drives	Points	Comments
-1 to -10	0	0
-11 to -34	7	28	13 Plays - Lucky, Marlon 13 yd run 14 Plays - Glenn, Cody 1 yd run 6 Plays - Phillips, J.B. 6 yd pass from Taylor, Zac 7 Plays - Mueller, Josh 6 yd pass from Taylor, Zac
-35 to +35	5	21	8 Plays - Herian, Matt 13 yd pass from Taylor, Zac 5 Plays - Jackson, Brandon 25 yd run 6 Plays - Teafatiller, Hunter 29 yd pass from Ganz, Joe
+34 to +11	1	0	Drive started on 15 yard line ended with INT on tipped pass
+10 to +1	0	0
Totals	13	49	13 Drives, 7 TDs, Avg. Scoring Drve = 8.43 Plays

Nebraska got off to a slow start punting on their first two drives. The Huskers started their third drive at the Louisiana Tech 15-yard line following a muffed punt. Nebraska failed to capitalize, however, when Zac Taylor’s pass was tipped at the line of scrimmage and intercepted.

The Nebraska offense then got rolling and scored on its next four possessions. First, Matt Herian caught a TD pass late in the first quarter to get the Huskers on the board. The second quarter then saw TD runs from Marlon Lucky and Cody Glenn. Tight ends J.B. Phillips and Josh Mueller then caught a pair of 6-yard tosses from Zac Taylor in the second half. Nebraska closed out its scoring with a tough 25-yard run by Brandon Jackson and a TD pass from Joe Ganz to Hunter Teafatiller. Teafatiller became the fourth Husker TE to catch a TD pass in the game.

Overall Nebraska scored TDs on 7/13 drives in the game. The average starting position for Nebraska drives was their own 38-yard line. Louisiana Tech’s average starting position was their own 24.


Run/Pass Split

Plays	Number	Yards	Avg.
Run Plays	48	252	5.2
Pass Plays	36	332	9.2
Total Plays	84	584	6.95

Nebraska entered the 2006 season hoping to “pound the rock” and re-energize a running attack that had floundered in 2005. To that tune Nebraska ran the ball 48 times against Louisiana Tech. That would be more carries than Nebraska would have in all but one game during 2006.

Because Nebraska ran an astounding 84 plays in the game, it also balanced its attack with 36 passes. The Huskers completed 24 of those passes and also threw 4 TDs in the game. The Louisiana Tech game would mark the first of five games in 2006 that the Huskers would average more than 5 yards per rushing attempt. The 9.22 yards per passing attempt was the sixth highest total for the Huskers in 2006.

Play Selection By Down and Distance

Down	Distance	Runs	Pct.	Yds.	Passes	Pct.	Yds.
1st	& 10	21	60%	151	14	40%	61
	& 15	0	0	0	1	100%	18
	& Other	2	50%	0	2	50%	30
2nd	& 1-3	4	67%	12	2	33%	19
	& 4-6	6	67%	30	3	33%	3
	& 7+	8	67%	26	4	33%	57
3rd	& 1-2	4	50%	15	4	50%	39
	& 3-6	3	50%	-2	3	50%	34
	& 7+	0	0	0	3	100%	41
4th	& 1	0	0	0	0	0	0
	& 2-3	1	50%	7	1	50%	0

One of the reasons for Nebraska’s success on 1st down in the game was its ability to keep the defense guessing. Many coaches believe first down is the best down to keep an opponent off-balance, because the defense really has a difficult time knowing what is coming. By utilizing a 60/40 run/pass split on first down, Callahan and the Nebraska offense kept the Bulldogs guessing and set up several 2nd and 3rd and short situations.

On second down the Huskers ran 67% of the time. This is a number that would stay about that high throughout the season. When faced with a 2nd and short-to-medium, chances are Nebraska is going to run.

The most interesting item to note on third down is that the Huskers faced just three 3rd and long situations in the game. Interestingly Nebraska converted 2/3 of its 3rd and long opportunities against Louisiana Tech. One was the 28-yard completion to Purify and the other was a 13-yard completion to Hardy. The lone 3rd and long the Huskers failed to convert came on a drop by Hardy that would have gone for a first down.

Personnel Breakdown

Personnel	Runs	Pct.	Yds.	Passes	Pct.	Yds.
2 WRs	12	80%	112	3	20%	4
3 WRs	4	16%	17	21	84%	178
2 TEs	12	63%	28	7	37%	37
3 TEs	13	76%	69	4	24%	52
4 TEs	6	86%	19	1	14%	31
Totals	47		245	36		302

One of the strengths of the WCO is the ability to utilize multiple formations and personnel groupings. Often a single play can be run from any number of these groupings creating a playbook that seems almost endless. In the 2006 opener, Nebraska highlighted the flexibility of its personnel groupings. We see these represented in the table above. You can click on the formation names to see a screen capture of the formation as it appears pre-snap.

The biggest thing that jumped out while charting the Louisiana Tech game was the use of the 4 TE set. I honestly had not noticed the regularity with which we used this grouping until now. I was aware that we often had three TEs on the field, but hadn’t always noticed the fourth. I wasn’t alone. Several times during the play-by-play Jim Rose told the listening audience that we were aligned in a 3 TE set, when really all four were on the field. I know because I stopped the tape numerous types and recounted. You also might notice the arrows in the picture of the 4 TE set, just to ensure I wasn’t hallucinating. My hunch was that Callahan devised this “jumbo” package to help jump start the running game. Given that we threw just one time out of this formation against the Bulldogs (a play-action toss to Herian for a 31-yard gain), my hunch seems correct.

The other grouping that sticks out is the 3 WR set. While we see this personnel grouping used a lot against LATech, what is interesting is how it was used. Of the 25 times we used this personnel grouping, all but seven came from a shotgun formation. In addition, of the 17 plays with 3 WR from the shotgun seven came while Nebraska was in its 2-minute offense late in the first half. That 14-play drive saw Nebraska complete 7/9 passes, pick up five first downs and overcome a Kurt Mann personal foul. Cody Glenn capped the drive with a 1-yard TD run.