Blue Moon, Redux

Submitted by MCalibur on August 24th, 2010 at 5:54 PM

[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:



Norm. Coefficients


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.]

The Dope with Turnovers

Turnovers are a bitch; most teams can deal with 1 or 2 especially since the opponent often returns the favor, but if they come in bunches, you’ve got a problem. Also, even 1 poorly timed turnover can obliterate an otherwise dominant performance. Most reasonable people would agree that luck is a factor, the disagreement occurs in regards to how big a factor it is.

There are people, many of them, who think that turnovers are highly, maybe even predominately, influenced by luck. Among those people is Phil Steele who includes an article entitled Turnovers = Turnaround in his popular annual football preview. Steele’s basic argument goes that turnovers are random enough that, if your turnover margin is low or high in a given year, chances are that the numbers will turn around the next year, and your win-loss totals will follow in kind. This idea applies the concept of mean reversion but in order for mean reversion to occur, there must be a clearly identifiable element of random variation / luck / football demigod malevolence in the data.

With that said, common football intuition would support the notion that players can take overt action to force the issue; players can cause turnovers. So, lady luck—hardnosed broad that makes you fight, for your right, to paaartay; or fickle, stone cold, heartless dame that takes out one of your 2 most critical players during preseason training on a freak, non-contact, season ending injury? Oh yeah, I was talking about turnovers, let’s see what we see.

Rosie and the Diva

To answer this question, I pulled data from the NCAA stats archives for all available teams for the 2000 – 2009 football season, almost 1200 data points. Let’s cut straight to the chase, see—go, go, gadget chart.

TurnOver Mean Regression

This chart shows lumped average (dark blue dots) as well as the number of observations (red circles) at each level of turnover margin. The average year-end total turnover margin is +0.3305, essentially zero, with an observed range of +25 to –26. Mean reversion is clear as day—the further from average you go, the more likely you are to go back the other way. HOWEVA, this is a classic “see what you want to see” situation. Allow myself to fisk myself—go, go, gadget different chart:

TurnOver Mean Regression Scatter

Schizophrenic statistics—what do they mean?

Like double rainbows and wingless helmets, schizophrenic statistics can be difficult to condense into meaning. Focusing on the lumped averages allows us to look past the variation and focus on central tendency for each level of proficiency. The high R-squared value for the y_lumped trend line indicates that the trend is not a fluke. At first blush it looks like the lumped averages are a cherry picked values, but it’s actually the exact opposite.

The R-squared value for the y_scatter trend line is half as large as for y_lumped where you collapse each column into a single point.  People who don’t thoroughly understand/remember what R-squared signifies might point to the lumping maneuver as a nefarious deed and say, “when you look at the actual data, there’s too much variation to determine what the real trend is.” This would be a fallacy that only a phallus would deploy; don’t buy it. A slope that large in relation to the magnitude of the independent variable is a real trend—it’s almost one-for-one.

The lumped average trend is our the best shot at synthesizing a projection if that’s your game. By considering all the values at a particular observation level we neutralize the observed variation. But, you can’t just ignore variation, especially when it’s that large (the observed range at the 0 point is –15 to +20!). Moreover, the fact that you might currently lack an explanation for said variation, doesn’t mean the variation is completely random.  You should do everything in your power to understand what might be causing the variation and use that information to improve your estimate.

Turnover Reversion Drivers

So, what might the source of the very real variation we see in turnover reversion?

Offensive Driver-QB Play: In previous diaries I’ve discussed how a QB progresses depending on his recruiting profile and level of experience. There is a clear trend of improving interception rates. Previously charted for your viewing pleasure.

INT Rate

Offensive Driver-Improved Ball Security: From making QBs take hits in spring practice to coaching RBs to transfer the ball to their outside hand or clutching the ball higher on their torso (Tiki Barber), ball security is something that can be improved via coaching and drilling. No charts, just reasonable football intuition.

Defensive Driver-Ball Stripping: This is another technique that can be coached and drilled, but a forced fumble does not always equate to a turnover you need some luck for that to happen.

Defensive Driver – Be Good at Defense: This is the battle cry for the “residue of skill and preparation” crowd. It’s legit. Put pressure on the QB, cover receivers well, punish the ball carrier. The chart below shows Southern Cal’s positive turnover since 2000. The five-year run beginning in 2001 is the residue of skill and preparation.

USC Positive Turnover Chart

Plain Old Dumb Luck: It can’t be denied, being in the right spot when a pass deflects off of one (or six) players or having an oddly shaped ball bounce into your arms instead of your opponent’s has nothing to do with skill or preparation. The mean reversion chart shows this fact and it shows that the effect is strong. Specific teams might be able to resist the effect for several years, but sooner the talent disparity needed to sustain is something that few teams can and do achieve.

Shine Down on Michigan

Offensive Interrogation Point: Last time I figured that the Offense would improve to the 425 – 450 yards per game level. Regardless of whomever the QB is. Denard will not start unless he can displace a very good Tate Forcier. If someone gets injured we have a capable back up. The offensive line will be much better and can even sustain an injury or two without becoming a total disaster. The wide receivers are good and deep, and Stonum might even break out now that he can see. The only question mark is the running back situation, but the only reason its a question mark is because we don’t know who going to be the guy(s). I don’t think its appropriate to assume that we won’t be able to plug in one of our 4-5 talented recruits and pick up where Minor and Brown left off. We might even be better off if the new guys can stay healthier than Minor and Brown. I see no reason to modify my initial expectation.

angry_Michigan-hating_footbal_demi-godDefensive Interrogation Point: Here’s where things get dicey because of little baby predator’s angry-michigan-football-hating demigod’s desire to eliminate Woolfolk from Michigan’s 2010 roster. In April I surmised that its possible that Michigan’s defense undergo modest improvement from allowing 393 ypg to 375 – 350 ypg citing Northwestern, Minnesota, and Purdue from 2009 as proxies for the estimate; still bad, but better. With Woolfolk out a more thorough discussion is necessary.

The Defensive Line loses Brandon Graham, who will definitely be sorely missed. But, one guy is easier to neutralize than 3 (or 4). Martin, and Van Bergen will be better (incrementally at least) and Will Campbell should be available to contribute more than he did last year. Last year, teams could double or triple team Graham and let their other guys go up against talented but less mature competition. This year I think its more likely that the guys who don’t get doubled will be able to make more hay than they were able to make last year.

Linebackers, another area for concern based off of last season. Roh was great and should take a big step forward this season but, Mouton and Ezeh and the rest of the 2 deep were uninspiring and downright frightening at times. But is it reasonable to assume that Mouton and Ezeh will not be better at all? Even if they just get a little better due to being in the same system for the first time in their careers as starters, it’s still better than last year.

Defensive Backs, son of a bitch. It was bad when we lost Warren, now that we’ve lost Woolfolk also, it’s hella-bad. I have no delusions that this wont be the weakest link but how bad will they be?

  • Cornerbacks. Floyd should be better than last year however incremental his improvement might be. May not be faster though, so not a whole lot of consolation there. Cullen Christian should be better than Floyd ‘09, or anyone else who was trotted out there, and probably no worse than Cissoko.
  • Safeties. Why wont this sub-unit be better than last year (again, however incremental). There’s at least more athleticism available, and more familiarity with the scheme.
  • The scheme is designed to protect vulnerable secondaries, if only we give up fewer bombs…that’s a big improvement.
  • Proxies: Northwestern, Purdue, and Minnesota don’t recruit better than what Michigan has on its roster right now even after Woolfolk. Michigan State’s secondary was WORSE than Michigan’s last year, yet their overall defensive production was significantly better. A weak secondary is very unsettling but it’s only part of the defense, it doesn’t necessarily mean DOOM! Though, it could.

Having said all that, I’ll back off my range to 375 – 400; Why would the loss of Woolfolk legitimately make us worse than Illinois or Indiana or Notre Dame or Michigan from 2009? I’m really asking.

Lady Luck - Pin Up Turnovers: This is an area where Michigan should improve once more. There were reasons why Michigan ended up –12 on the year last year but not the ones I expected to find. In 2009 Michigan’s offense coughed up 28 turnover (13 fumbles, 15 interceptions), that’s only 4 above average. It was the defense that killed the turnover margin; Michigan’s D only generated 16 turnovers in 2009.

The average year end fumble total is 12.8, I’ll go with 13 since you can’t gain par of an interception. The average year end fumble total is 10.6, I’ll use 11.  All turnovers are zero sum, meaning that for every turnover lost by one team there is a turnover gained by its opponent; therefore, average fumbles gained and lost are the same number. Likewise for interceptions.

According to the regression above, Michigan should expect to come back to –2 in turnover margin, let’s see if we can reasonable explain why that would happen.

  • Interceptions Lost: Last year Michigan threw 15 interceptions with a true freshman passing the ball. Previous work has shown that we should expect that to improve (if Denard is throwing picks he wont be playing QB). Therefore, it’s reasonable to expect Michigan to return to average. Projection: –13.
  • Interceptions Gained: Last year Michigan had 11 interceptions, two less than average. We’re probably worse off in pass defense this year so, let’s leave that where it is, maybe even one lower. Projection: +10.5.
  • Fumbles lost. Last year Michigan lost 13 fumbles, two more than average. I subscribe to the notion that fumble recoveries are very random, so I think it’s safe to assume that Michigan will be an average team in this area. Projection: –11.
  • Fumbles Gained: This is where Michigan got killed last year, recovering just 5 fumbles versus an average of 11. Again, I say recoveries are random and we can expect to get back to average here. Projection: +11.

Doing the arithmetic yields an expected turnover margin of –2 or –3.

Acquiring target: Using the worst and best case estimates describe above, Michigan should still be able to make a bowl and end up with 6.6 to 7.9 wins out of 13 games. Heaven forbid we get a lucky break or two along the way.


Woolfolk’s injury hurts, but I don’t think its a death knell. In full disclosure, it would be reasonable to break the season into OOC and Big Ten play and re-project each portion, but I’ll leave that for others to do. Also, the estimates I’ve discussed above are just my own opinion, I’d love to hear where others think  I’ve been overly optimistic.

As usual comments and criticisms are welcome.


Marley Nowell

August 21st, 2010 at 5:33 PM ^

Then went and made a diary 100x better than mine.  I also appreciate that you found an optimistic outlook.  I didn't realize (blacked out) how many turnovers we had last years and our own lack thereof.  Hopefully a more experienced offense can bring us back in the normal range.



August 21st, 2010 at 5:36 PM ^

what I've been saying for a while here, I would like to offer M fans some advice: tamper the irrational exuberance, and be happy if we do six or seven wins and get a bowl. Odds are that is what we are likely to get, from heckamany points of view. More would be gravy, but a sober look at the schedule suggests six-seven wins. Brandon KNOWS THIS, TOO, which is why I don't see Rich Rod fired unless the team is tanking.


August 24th, 2010 at 7:00 PM ^

If I tamper with my excuberance I am back to 10 wins. Anyway, this is another great post that has refocused my reasons for loving this site.

As an aside to the OP's post, the expectations have been set to 7+/- 1 wins for the season.  However, Iowa last year showed that there are outliers to this where we could potentially be at +3. I wrote a post yesterday why we can potentially win any game and get to 10 wins. I am all for being realistic, but with that, keep it in the back of your mind that we can still over achieve this year.  

kevin holt

August 21st, 2010 at 5:38 PM ^

all the weird-ass pictures? not complaining, since pictures and charts? charts definitely spice up a good diary. allow me to further peruse this when I have some more time, it looks great.


August 21st, 2010 at 7:03 PM ^

You should know better -- mathematicians don't digress, they regress. So there.

I like the analysis, but especially the outcome: 7 wins +/- 1. More particularly, I appreciate the quantitative look at the turnover margin. Last year's -12 was epically bad. I believed (based on flimsy evidence) that just getting back to a median value would probably mean a game or two in our favor.

Again, much appreciated. Thank you.


August 21st, 2010 at 7:34 PM ^

i'm still feeling like it will be, but i'm back to trying to tell myself otherwise.

is there any chance that the random two and three star d-backs that NW and Indiana pull are relatively better than ours?  there's probably more variance, since I assume that any one Michigan recruit will get more eyeballs than any one NW/Indiana recruit.  as long as they have less attrition than us (said the same way, more total recruits at a given position), they could be better.  i kind of assume big ten schools with mediocre recruits are pretty good at retention.  the degree and simply being on the team matter more than getting a worse education and more playing time.

none of that explains Notre Dame's suckfest, of course.

another way of thinking about Woolfolk's absence is wins above replacement.  let's say on average the worst team in college football wins 1 game.  to be average, you need 5 WAR.  football outsiders breaks wins down using a 40/40/20 rule iirc which seems pretty reasonable.  40% of wins are attributable to defense, 40 to offense, 20 to special teams.  so an average defense will be worth 2 WAR.  if each player is about as important as the other (probably true on defense), then an average defense will feature a unit of ~.2 WAR players.  even if Woolfolk was good, he probably wasn't worth a full or even a half win as long as we have actual replacement level players.

that isn't the most thorough method, but it should at least yield a useful scale.  i'm not sure about the distribution but i'm guessing it's only the very best players that are worth a full win in themselves.  you could get closer figuring out yards convert to wins.  200 ypg (best) to 500 ypg (replacement level) seems like the approximate range of outputs for total defense, with 350 as average.  so that's 150 yards to average from replacement, or ~15 yards per player per game.

all told, i think it's obvious why teamwork and being team-oriented is stressed so much.  the difference between good and average and bad is just not that big.  except, probably, at quarterback.


August 24th, 2010 at 9:07 PM ^

as described here, it's more like 43/43/14, special teams being one-seventh rather than one-fifth. (Their college stuff is a few years behind the pro stuff and not done to the same degree yet, but it's probably as good a starting assumption as any to use the same factors.)

It doesn't change your point much; an individual player is worth a touch more in your example, better players perhaps worth a touch more than that ...

but the real question is about the backups. If Woolfolk is worth .2 WAR (I think wins would be positive even though we're talking defense; positive means "above replacement" and negative means "below replacement"), then the loss of Woolfolk costs Michigan .2 wins if and only if the corner who replaces him is replacement-level.

A more detailed analysis would be something like this: to account for the injury properly, you really need to follow it all the way down the chart. Multiply the change in WAR by the percentage of plays in which the player at that level of the chart participates to find the overall impact. Obviously one problem that arises from a season-ending injury is when a team replaces an excellent player with a replacement-level (or worse) player, but if, say, your #2 and #3 corners are 0 WAR and everyone else is about -.5 WAR, you start seeing the effects as soon as the nickel package trots onto the field.


August 25th, 2010 at 1:54 AM ^

I think it's even more complicated than that.  Unlike baseball, where you can aggregate stats because many aspects of hitting are random, football is less so.  You can target a certain players more than others once you identify their weakness, unlike trying to hit a sacfly only to left because you know that guy has a weak arm.


I think you'd have to break the defense down into units and not individual players for WAR to be taken into account.  It does you no good to have a 0.5 WAR LB and DL, but a -0.5 WAR secondary.  


August 22nd, 2010 at 10:10 PM ^

I clicked on this assuming it was referring to that crappy bar on Main St, and wondered if it was going to be a "You won't believe what happened to me at the bar last night!" story.  It turned out to be much, much higher-quality content than that. 

EDIT: Wait, that place is Full Moon, not Blue Moon.  Never mind.


August 22nd, 2010 at 1:36 AM ^

Great diary. Should be on the front page. A few thoughts

Good to see a mathlete taking look a deeper, more pragmatic look at turnovers, rather than the black and white this is lucky and this is unlucky methodology. They are tricky, tricky rascals to categorize, but you've got some good categories going.

Steele doesnt necessarily think TOs are totally random, just that big numbers +/- in the margin department is random enough that it probably wont happen a second year in a row and the team record will increase or decrease accordingly. If you are +10 or better, your record will go down the following year. If you are -10 or worse, your record will improve the following year. Its a tad bittersweet, but this worked for Michigan last year. If it works again, we're in a bowl.

You've laid out some compelling factors and numbers to back the Michigan TO margin predcition this year. But dont you think if we hit that close to even steven in the TO margin that the team will probably sky past the 7-win prediction? I think it would. Last year, the team would have won  8 games had the TO margin been that good.

Tell me again why Michigan's INT numbers against will improve, but Iowa's wont?

 One of us is going to be right about Iowa this year. If its me, I'll win all year. If its you, I;ll just win from October on.



August 22nd, 2010 at 10:50 AM ^

Just kidding (at least a little). Here's the same treatment I gave Michigan's turnover situation for Iowa:


Fumbles Recovered: Iowa had 9 fumble recoveries, 2 under the 10-year NCAA average of 11. From what I can tell there were only 20 forced fumbles by Iowa last year, thus they recovered about half of them, exactly what you would expect. I don’t know how many forced fumbles should be expected, but coming up 2 recoveries shy of average doesn’t seem out of whack to be. They should stay right there in the average-ish zone.

Balls Intercepted: Iowa had 21 interceptions last year, WAY above average. It’s conceivable that their awesome D-line made QBs rush their throws and they had pretty good DBs back there, specifically Sash and Spievey, mopping things up.  Spievey is gone, and while the D-line will still be great (barring injury) , I wouldn’t bet on them coming up with 21 INT’s again. I’ll give them above average, say, 15-17 on the year. I think that’s fair and generous.

Fumbles Lost: Iowa’s offense only coughed up 8 fumbles last year, 3 under average. They lost 2 NFL offensive tackles, one of them a first rounder, from last year’s team. I don’t think it’s a strech to think that they’ll come back to average in fumbles lost.

Interceptions Thrown: Iowa’s 2 QBs combined to throw 20 interceptions (Stanzi 15, Vanderberg 5). Assume Stanzi starts the whole year. Even though he’s entering his third year as starter, which would indicate that he’ll improve in the INT department, he was a RS-Junior last year; I have to believe he was at or near his ceiling by then. He threw INT’s at a 4.9% clip and he loses both of his starting tackles both of which, again, were NFL players. He’ll probably be better, but I still think he’ll be on the bad end of the spectrum. Assume that Iowa passes 300 times again this year; I’d think that Stanzi throws 11 or 12 picks. That’s better than average but bad for a 5th year senior in his 3rd year as starter.

Add it all up, Iowa's year end turnover margin as projected by me: +3 to +6. Not too far above average. Keep in mind I’ve given their defense the benefit of the doubt that they’ll maintain an above average interception rate, and I ‘ve given Stanzi the benefit of the doubt that he’ll throw interceptions at a much lower rate (3.5% to 4%). Really, I’d just expect them to be neutral-ish in net turnovers, just like last year.


August 22nd, 2010 at 11:50 AM ^

Interesting. Iowa was +2 in the turnover department a year ago. And, you're projecting them to be better in that department.

Doesnt sound like a death knell to their season at all.

On the INT issue, Iowa has avergaed about 16-17 INTs a season and until last year, their QBs had never really been consistently INT prone. Stanzi only threw 9 the year before. He threw a half dozen more picks a year ago in only 50 or so more attempts. 4 returned for a score.

I think you're underestimating the luck involved in that kind of spike in INTs, combined with the scoring results of some of them, in your critiques specifically of Stanzi.

But, otherwise, I dont think you're off the mark on this TO margin breakdown for the Hawks.

Also, you keep talking about talent lost to the NFL. They still have 6-8 possible NFL draft picks in their starting lineup, including the entire defensive line, two safeties, two Wrs and, yes, their QB

You are a year too soon with your dire predictions.



August 22nd, 2010 at 3:07 PM ^


You and I aren’t that far off on our expectations. I don’t think they’ll suck by any means; I just don’t give them as much love as they get from most people. I don’t mean to diss your opinion or Iowa. I’m just stating my case in direct and unambiguous terms.  I think in a different thread regarding Iowa you said you think they’d go 9-3, I say 8-4. My beef is when people start talking about Iowa winning 10 or 11 games; I don’t see it. The truth is probably somewhere in between us. Set the line at 8.5 wins and live off the vig.

I agree with your take on the NFL worthiness of the players coming back for Iowa. However, the defense was already awesome last year; there is no room for improvement. Clayborn was already an All-American level player, it doesn’t get better than that. If he matches his level of play from last year, he’ll be…All-American, again.  I think their defense can’t lose Angerer and Spievey and be better; if anything they’ll be a little worse. A little.

Offensively, DJK and McNutt are very good but Stanzi reduces their effectiveness. Meanwhile, they lost both of their tackles to the NFL so, Stanzi’s protection is going down  and his outlet is gone to the NFL, too.

Regarding Stanzi, I think he’s more a liability than he is an asset and I’ve seen nothing so far in his playing career that makes me think otherwise. He’s constantly over/under throwing his receivers and I think the INTs reflect that. The Donovan Warren Rick-Six comes to mind; who the hell was he throwing to? There was no pressure, he was in his second year as starter, and was in his fourth year out of high school.  Even his first year accuracy was crap. Sorry man, I think he blows, and I don’t think he suddenly becomes your typical third year starting 5th year senior. He does come up with some clutch play, I’ll give him that, but I think DJK and McNutt bail him out plenty. Whichever NFL team drafts him will be torching a pick and a pile of money.

In my opinion, Iowa was fortunate to win 11 games based on their overall level of play. Ten years of NCAA data supports that opinion. I don’t think they’ve gotten better and they’ve probably gotten a little worse. Unless Stanzi shows ridiculous amount of improvement or Wegher is the new Shonn Greene (maybe, probably not), they’ll be a distant third in the Big Ten at best.


August 22nd, 2010 at 4:24 PM ^

The O/U for wins per the oddsmakers is 8.5. And i dont think we need any metric in order to say boldly that an 11-win team is likely to lose more games the following year. It aint easy reaching double digit wins, let alone 11. Not many programs are able to repeat that.

Anyway, I commented on it a few weeks back on the JCB. (sorry Geaux Blue, feel free to give me as many negs as you want)

Whats interesing now is the -180 juice on the Over. So, most people are right now taking the Over, so they're making it a more expensice play (bet 180 to win 100) to be Iowa.

Under is +150. Or 1.5 to 1 odds. Bet 100, win 150

Yeah, I'm still thinking 9-3. Maybe if I thought Penn State was a bit better situated this year. Or had this bizarre notion that it was lock MICH will beat Iowa the way many have talked themselves into around here. Or if I trusted Wisconsin, which has always had trouble home or away against Iowa. I still think they lose at Arizona, split the Wisco/OSU showdowns at home and drop one random game somewhere on the slate and the league comes down to the Iowa/OSU game. 9-3 overall, 6-2 in the league

Also, worth noting: I want to understand all this math stuff you and others throw at us. The only way to do so is ask HARD EDGE questions and challenge the assertions made. I just cant say "YES, I KNEW THOSE FAWKERS WERE LUCKY OR DIDNT DESERVE TO WIN THANKS FOR THE DIARY" the way 75 percent of the posters do. Its certainly nothing personal, and I know you know that.....but I wonder if some of the other folks lurking out there do?

Keep the good info coming, we've got a long season ahead of us to breakdown.


August 25th, 2010 at 7:29 AM ^

Every team is lucky. Trying to prove who is luckier is futile and left to the biases of whomever is doing the math and their mythical formulas

Iowa was, first and foremost, a damn strong team last year, and not many teams in the land have been better in big games the last two years.

They've had 6 losses to last two years by 22 points. If that had happened to us, we'd be talking about all the unlucky breaks costing us a title.


August 25th, 2010 at 9:08 PM ^

They also won 6 games over the last 2 years by 14 points.  Two of those wins were over Northern Iowa and Arkansas State.  Five of the six were at home.  Five of the six were against opponents where Iowa as the home team, were they truly elite, should have been favored by 10-12 points.

You're right of course, and that's why luck is best left to observation and intuition.  I've seen the NI, Michigan, and Sparty games... they were not much better than any of those teams.  And if Indiana had a bit of their own luck (or trace of fortitude), they'd have beaten Iowa at home by two TD's.  Geogia Tech was the ideal BCS match-up.

They are a tough team, no doubt.  But to my mind, also a lucky fawker team.

Enjoy Life

August 24th, 2010 at 6:42 PM ^

I debunked Steele's "theory" last year in a Diary titled "Turnover Analysis Part 2 - Do Turnovers Equal Turnaround."

In 2008, Michigan was -10 in TOM and ended up 3-9. In 2009, Michigan was -12 in TOM and ended up 5-7. Obviously a better TOM was not the cause of the “turnaround”.


August 24th, 2010 at 7:16 PM ^

Dude, he never says anything about a better TO margin the following year, in the percentages he is tracking. In fact, he doesnt say a single thing forecasting a better TO margin. He uses that stat as an indicator towards which teams will improve their record.

It's all about having a better overall record, not a better turnover margin. Which, the 2009 Michigan team did do over the 2008 club.

I think you've missed the point


August 22nd, 2010 at 12:21 PM ^

I believe there needs to be a few more stats that actually could be made into a program that "gamblers would buy". I am sure with a years worth of work to what you have done. If a "site" had raw data you could upload and plugged in. This would be a program that many would be interested in the NFL and NCAA. Might Market your big brains to become the next millionaire.

Things to give it better true data and I am just thinking off the top of my head.

1) Upper Class Leadership

2) Full Game starters Upper Class men

3) Full Game starters Under Class men

4) Players drafted from the team to the NFL and what position and draft pick

5) Returning starters from last year

6) Break downs of receiver drops/ yards after the catch / first downs

7) Running backs yards per play/ first downs/ fumbles 

8) Home Field advantage

9) Quarterback passer rating/ interceptions/ tips/ deflections

10) Number of true freshman starters

11) Number of walk on players

12) Injuries to players

13) Field goals missed/ made/ distance

14) Conditions of the field


August 22nd, 2010 at 3:51 PM ^

Doesn't the amount of fumbles forced by a team directly correlate with how many they recover? Using the idea that recovering fumbles is luck and will average out to about a 50% clip...a team that practices ball-stripping techniques or has players that are fumble forcing machines will generate more opportunities at recovering fumbles meaning they may or may not regress to the mean. I'd be curious to see if Michigan forced a lot less fumbles than normal last year.


August 22nd, 2010 at 8:01 PM ^

But the data is difficult to access in large enough quantities to do stats on it. I've got a little something cooking but it might be a while before I'm able to do anything diary-wise.

After I wrote this diary I went in and checked Michigan's forced fumbles (or what I think is FF) and see that they forced 14 and recovered 5; under 50% but only 2 under. That's not a major deviation to me on a small sample.  Since average is 11 recoveries you'd expect the average team to force 22-ish fumbles (assuming a 50% chance of recovery). That means to me that Michigan didn't force as many fumbles as most teams for one reason or another.

Maybe they were too focused on remembering what they were supposed to do that they didn't try and strip as many balls? If so, a second year in GERG's system should help them think less about their responsibilities and more about stripping the ball. I think Mike Martin talked about an emphasis on ball stripping in his countdown to kickoff video so, it sounds like the coaching staff is aware of the fact the we were low on forced fumbles last year.

I'm still giving them the benefit of the doubt that they'll be able to get back to average in terms of defensive fumble recoveries.


August 24th, 2010 at 6:35 PM ^

I agree with this and was about to make the same point.  To be a good, aggressive ball-stripping team you have to first be a good tackling team.  The tackle always has to be made first, then the attempted strip.  Other wise bad things happen, like broken tackles and long gains.  We've had our share of that but it should be sharply diminished this year.


August 24th, 2010 at 9:27 PM ^

but I wonder if there is a better relationship between fumbles forced and plays on defense rather than fumbles forced and games played?

Maybe there isn't enough of a difference for that to be significant. The average team was on defense for roughly 67 plays last season ... outliers range from Baylor at 75.6 (three of the four teams spending the most plays on defense are in Texas, hmm) to Georgia Tech at 59.4 (being good and running a lot cuts down on defensive plays, yes it does). About 8 plays either way, and with a fumble recovery happening roughly every 82 plays or so, it isn't like the Bears should have expected to see so many more fumbles from being on the field so many more plays. (It's a little weird to have to talk about recovered fumbles when we want forced fumbles, but hey, if the data isn't there ...)

Deep Under Cover

August 24th, 2010 at 7:13 PM ^

I came to MGoBlog to take a break from studying for my Stats final on Thursday here at OSU, and what do I discover?  OSU is teaching me to understand why we will be better next year.

Great diary.  I joined just so I could tell you so.


August 24th, 2010 at 7:31 PM ^

pretty well, following at least a good portion of what you were getting at (I expected it to be more about Woolfolk's loss than turnover margin, though, in the end, I realize that Woolfolk's loss is incredibly hard to gauge with statistics), and then I came across that dang baby predator picture and stared at it for 10 minutes till I forgot what I was doing.


August 24th, 2010 at 8:02 PM ^

Great analysis.  I agree with most of your assessments and most are probably on target.  The one area that I would suggest you may be a little conservative is in the Defense YPG.  You stated that you are projecting 375-400 this year after an abysmal 393 last year.

I get the loss of Warren, Graham, and Woolfolk but have several points to ponder:

1.  It was relatively easy for teams to neutralize Graham and the rest of the defense was horrible.  On offense, one incredible player can make and incredible play and change the game.  On defense, 10 player can do their job and one screws up and it costs you a game.  In other words, defenses are often only as good as their weakest link.  A single incredible player i more easily neutralized on defense because the oppositiion double teams them or runs away from them.  As a result, I believe the loss of Graham will not be as great.

2. If Warren was such a loss, why did he not get drafted and why was our turnover margin so poor.  I contend that we thought Warren was awesome when compared to our Freshman and walk on alternatives. 

3. The rest of the defense outside of Warren and Graham are better.  At nearly every position we have an improvement over 2009.  We have second year players instead of true freshman and walk ons.  We have Senior linebackers playing instead of underperforming Juniors.  We have another year in the system and another year of conditioning.   

If this makes sense, it would be interesting to know what happens to the overall probability of wins if you dial back the defensive underperformance to 365 YPG.  If Michigan performs at this level, it is still the 8th best in the Big Ten (based on last year) and only 3 teams are worse.  It might mean a 8 win year.

How great would 8 wins feel after the last two years?

All In.


August 24th, 2010 at 8:23 PM ^

1. It was NOT relatively easy for teams to neutralize Brandon Graham last year -- otherwise, he wouldn't have had the great individual season he had.

2. Being a very good college football player does not always translate to pro success. Charlie Ward is the extreme example (won the Heismann; didn't get drafted). Donovan Warren was either all-conference or second-team all-conference (I forget which); that wasn't imagined. He actually WAS that good. Not Charles Woodson, but an upper-echelon Division I cornerback by any measure.

3. The corrollary is that the rest of the defense is NOT better this year. In particular, Michigan is probably at least somewhat worse at four positions: those vacated by Warren, Graham, and Stevie Brown, plus that vacated by Woolfolk due to injury. How much worse remains to be seen, but one would expect those four to take a step backwards, to at least some degree.

Special teams were not mentioned in the analysis. Here too, one would expect to take a step backwards in at least punting, not because anything is wrong with Hagerup, but because you just don't replace a Mesko overnight. Placekicking is harder to tell, but there is certainly no evidence to suggest an improvement, as your guy on scholarship is the same guy who couldn't beat out a walk-on last year.


August 24th, 2010 at 8:10 PM ^

Something tells me one will not find this type of analysis on little brother's boards. They are adamant that winning the big ten is a foregone conclusion based on the level of furrowing of Mark Dantonio's brows and the intensity of his scowl. They have a system of projecting wins that is based on how long it takes for each player to fall to the ground after being tased by a state cop. I saw the taser drill on BTN during the MSU season preview.


August 24th, 2010 at 8:11 PM ^

Strong work. I've been running your model in Matlab to get some trend data (nothing you haven't already done) and see how much improvement in each area affects the win total. I'm excited to see if this year's data validates this model.