defense

The 4-3 Under: Think 3-4 personnel and recruiting makes sense

[Ed-S: Festivus Bump!]

In modern football, there are 2 popular base defensive sets. Most teams run either a 3-4 Base or a 4-3 Base.

The quick explanation of these defenses is that the first number (“3” in a 3-4) is your number of Down Linemen (literally people who line up with their hand on the ground in a 3 or 4 point stance on the line of scrimmage) and the second number (“4” in a 3-4) is your number of linebackers (people who line up in a 2 point stance, behind the down linemen).

This diary will discuss the 4-3 Under, its similarities to a 3-4 set, and make sense of our defensive line recruiting. For the purposes of this diary I’m ignoring the secondary. You need corners and safeties. They’re all similarly sized players, get fast ones. The front 7 is where you need guys over a 100lb range and some more major differences show up.

Here’s a base 4-3:

Here's a base 3-4:

Both of these defensive base sets have advantages and disadvantages, and both lend themselves to different styles of players. When it comes to what Michigan is running as a base defense, the 4-3 Under, recruiting starts to make sense if you look at it as a 3-4 defense.

The 4-3 Under:

First, look at the D Line from the middle out. In a 4-3 Under you have a defensive tackle on the Nose, in a 0 or 1 Technique (NT) (Technique definitions:

)

You then have 2 players lining up at the 3 tech (DT) and 5 tech (SDE). Then you have 2 players further out on the line, at a 7 tech (WDE) and 9 Tech (SAM). Finally, you have 2 linebackers off the line of scrimmage (MIKE and WILL).

Now, compare these positions to the 3-4 Base. You still have a huge space-eating Nose Tackle (NT) who lines up at the 0 or 1 tech, 2 Defensive Ends over the guards, tackles, or in between (4 tech... hmmm, just a slight shift from the 3 or 5 tech...) and 2 people outside of them near the line of Scrimmage (OLBs). Finally you have 2 linebackers off the line of scrimmage (MIKE and WILL).

If you look at these two defenses, the only main difference is one of your 3-4 OLBs has his hand on the ground. That’s it! There are minor shifts on the line and other intricacies, but big picture the 4-3 under has personnel requirements very similar to a 3-4.

For the 4-3 Under OR the 3-4 in your front 7 personnel you need:

1.) A Space eating Nose Tackle (or at least one who can stand up to double teams)

2011: Mike Martin

2012 Recruit: Pipkins

2.-3.) 2 players with good size who can go against guards or tackles, defend the run, get penetration and rush the passer. (3-4 DEs or 4-3 Under 3 and 5 Techs)

2011: Heininger and RVB

2012 Recruit: Strobel, Wormley, Godin

4.-5.) 2 players with speed who can set the edge, keep contain, rush the passer, and drop into coverage occasionally (3-4 OLBs or 4-3 Under WDE and SAM. In the 4-3 Under 1 will rush the passer more often, 1 will drop into coverage more often, but both do both)

2011: Craig Roh and Jake Ryan

2012 Recruit: Ojemudia and (I can’t remember which LB projects here)

6.-7.) 2 players who make tackles. Always flow to the ball, can shed blocks, cover, and make plays (MIKE and WILL)

2011: Demens and Morgon/Hawthorne/Herron Combo

2012 Recruit: Ross, Bolden, RJS and Ringer (whoever doesn’t project to SAM)

In pass rush situations, most 3-4 Teams will run their NT off the field for an extra DB, and rush 4 with their 2 DEs and their 2 OLBs. Most 4-3 teams will sub a linebacker for a DB.

Michigan subbed Heininger (not the NT, but Martin is a better pass rusher than a prototype NT) for Avery and put Ryan on the line, just like 3-4 teams do. My guess is this continues next year, we run off a DL and let Ryan put his hand down.

As far as speculation that Michigan is loading up on linebackers, SDE types, and WDE types without taking 2 huge DTs in the class because we might switch to a 3-4 base... we kind of already have a package that uses 3-4 base type personnel. In the 4-3 Under, like a 3-4, you want flexibility in your defense. The following positions are relatively interchangeable in a 4-3 Under, don’t get caught up on DT vs. DE or DE vs LB:

3-Tech DT and SDE (5-Tech)
WDE and SAM

Michigan is recruiting the right numbers for the scheme they run. These are 17-year-old guys we’re discussing with recruits. Some will get bigger, some are maxed out. Some of the WDE/SAM types will be better at coverage and will play SAM. We saw Frank Clark and Beyer make this switch this year, one was a LB, one a DE in High School, and they switched at Michigan. Some will be better pass rushers and will drop into coverage less at the WDE.

The “Glut” at SDE doesn’t exist since the 3-Tech DT is a very similar position in the 4-3 Under, so some of these guys will play there. The coaches know what they need to run the 4-3 under, and hopefully this diary provided some insight into the personnel requirements so we can somewhat understand the method to the madness.

(Note competence)

Blue Moon, Redux

MCalibur •

[Ed: bump!]

Back in April, I wrote a diary called Blue Moon in my Eye in which I developed a regression model that could be used to develop a projected win total assuming that reasonable estimates had been used as inputs. At the time I thought that the team would be capable of winning at least seven, probably eight, and maybe even nine out of thirteen games this season. Since then, things have, uh, how do you say … changed. With the loss of Woolfolk, how do those numbers change?

The New Blue Moon

Before I get to that, there’s a good reason to update the model. In April, I mentioned that turnover margin is meaningful factor in regard to outcomes, but I lacked enough data to break it out specifically and therefore decided to leave it as a lumped parameter; turnovers were doomed to fade into the ether that is Intercept. No more, the NCAA has finally included turnover data in its database and now there is enough data to mix into the model. The new model has an improved R-squared value (0.752 as improved from 0.675) using just three end-of-year factors: offensive yards per game, defensive yards per game, and total turnover margin. Last time I didn’t include the model because it was mine, my own, my … preciousss. That was incredibly lame and nerdy (both with holding the coefficients and referencing LOTR) but we’re talking stats here so no one should be surprised. Another reason for divulging the goods is, now that there are four dimensions, a chart would be useless. Behold, the Blue Moon Model coefficients:

	Coefficients	Norm. Coefficients	P-value
Intercept	0.579253998	0.515607437	3.79693E-55
OffYds/G	0.001753298	0.107573121	7.5351E-118
DefYds/G	-0.001981349	-0.112371575	2.1098E-122
TrnOvrMgn_Total	0.007973783	0.065213954	5.75637E-50

I left the P-Values in there for those who know what that is. For the rest of you, it suffices to say what I said last time: that ish be money, yo.
The second column (Normalized Coefficients) is there to demonstrate the relative importance of each factor; in short, defense is a skosh more influential than offense and turnover margin is a little over half as important as both.
The use of the model (first column) is simple, start with the intercept then multiply the other the coefficients with their interrogation values and add everything together. Use it to gamble at your own peril. Until such a time as you can accurately predict end of year stats for these categories, the model is only good for using as a platform to base sophisticated guesses off of.
Probable influential factors that are embedded in the 25% of the variation not explained by the model (1 – R_squared) are:
- Return Teams effectiveness. Good return teams will establish good field position thus reducing OffYds/G.
- Coverage Teams effectiveness. Bad units will allow the other team to establish good field position thereby reducing DefYds/G.
- Field Goal Kicking effectiveness. If you get into field goal position and miss, you’ll have a lot of yards but nothing to show for them.
- Penalties. Penalty yardage will increase/decrease your production depending on if they’re called on you or them but doesn’t necessarily change how effective each team is at controlling field position.
In round terms, factor influence on winning percentage breaks down to 30% Offense, 30% Defense, 15% Turnover Margin, and 25% Other Things.

Shine Down on the Big Ten (and it’s self-absorbed neighbor)

Below is 2009 Big Ten Data and Blue Moon Model expectation (BMM Expect).

Team	OffYds/G	DefYds/G	TrnOvrMgn_Tot	2009 Wins	BMM Expect.	Delta Wins
Ohio St.	364.8	262.5	17	11	11	0
Penn St.	412.5	277.1	6	11	10	1
Iowa	330.8	286.7	2	11	8	3
Wisconsin	415.8	310.4	3	10	9	1
Northwestern	386	344.3	4	8	8	0
Michigan St.	407.1	364.3	-6	6	7	-1
Minnesota	295.8	364.3	-1	6	5	1
Notre Dame	451.8	397.8	5	6	7	-1
Purdue	391.3	376.6	-5	5	6	-1
Michigan	384.5	393.3	-12	5	5	0
Indiana	365	401	7	4	6	-2
Illinois	393.5	403.3	-4	3	5	-2

The distribution of Delta Wins, Actual Wins minus BMM Expect, is shown in the chart above. Note Iowa 2009. I defy them to go +3 again. They were a good team, they weren’t a great team. In fact, Northwestern performed better over the course of the year and—what, what?—apparently the head to head match-up agrees! The Wildcats actually won that game. Surely, Iowa wouldn’t begrudge anyone who leverages a +3 (or better, ahem) turnover margin into a narrow victory, would they?

The chest thumping bit that Iowa fans have developed is unbecoming. Like them, I’ll take 11 wins by any ethical means. Celebrate good times, come on, and all that jazz. But, this notion that they’ll be there again is based on what happened last year. How have they improved for this year? Any improvement that can be reasonably expected will be incremental in nature do to player development. Meanwhile, they’ve lost some really excellent players to the NFL (Bulaga, Moeaki, Angerer, Spievey, Edds, Calloway); is Iowa suddenly a recruiting powerhouse? Do they have more first-four-round NFL prospects just waiting to step in without skipping a beat? Poppycock. They’re regressing, and if they’re unlucky, it might not be so pretty.

Oh my, I’ve digressed.

[How bad the Woolfolk thing is after the jump.]