Troy Woolfolk

[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

Gollum & the Ring 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
 
DeltaWinDistribution
 
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.]