Mason NEEDS this, Pistons, after all you've put him through
Pitt at Cincinnati.
Munchie Legaux is the starting QB for Cinci! Leviticus Payne is a backup CB.
And Cinci runs out to a quick lead...
EDIT: Apparently, Ray Vinopal (#9) is starting at S for Pitt, Cullen Christian (#24) in the two deep at CB.
<I've had it with the RR to FLA threads>
DAYS UNTIL CULLEN CHRISTIAN UNCHAINS HIS INNER TWOLF!
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:
- 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|
FWIW Sporting News just unveiled their final top 100 guys for the 2010 class
Recruits of Note:
We actually have 3 top 100 guys already according to Sporting News. I found it interesting that SN is still high on Miller unlike Rivals/Scout/ESPN.
Man, can't remember a year with only 2 players ranked in the top 250, and none in the top 98. I don't like to delve too much into rankings, there are outliers etc...but overall I want more higher ranked players!
Cullen Christian 99
Devin Gardner 132
How he goes from #1 overall QB to #8 is beyond me. I have only heard good things about him in the all star games. Yeah, maybe he wasn't lights out, but to drop him this much seems like alot.
Torrian Wilson dropped out
Dior Mathis 177
As mentioned earlier Gholston got fifth star and is 21 overall.