The Big Ten Recruiting Rankings returns after a two-week hiatus. Outside of Penn State's class continuing to fall apart, little of note occurred since the rankings were last posted; look no further than Indiana picking up the highest-ranked recruit in that span for evidence. Changes since the last rankings:
8-5-12: Minnesota picks up Jalen Myrick.
8-6-12: Wisconsin picks up Alex James.
8-7-12: Illinois picks up Reggie Spearman. Dorian Johnson and Zach Bradshaw decommit from Penn State.
8-8-12: Nebraska picks up Zach Hannon. Indiana picks up Myles Graham.
8-9-12: Nebraska picks up Jonathan Cook. Indiana picks up Antonio Allen.
8-10-12: Illinois picks up Martize Barr. Northwestern picks up Godwin Igwebuike.
8-11-12: Penn State picks up Jordan Smith.
8-12-12: Iowa picks up Matthew VandeBerg. Indiana picks up Chase Dutra.
8-18-12: Illinois picks up Miguel Hermosillo.
8-20-12: Purdue picks up Dwayne Johnson.
8-25-12: Michigan State picks up Demetrius Cooper.
|Big Ten+ Recruiting Class Rankings|
|Rank||School||# Commits||Rivals Avg||Scout Avg||24/7 Avg||ESPN Avg||Avg Avg^|
^The average of the average rankings of the four recruiting services (the previous four columns). The figure is calculated based on the raw numbers and then rounded, so the numbers above may not average out exactly.
NOTE: Unranked recruits are counted as two-star players.
To eliminate any confusion about how the rankings are determined (to be honest, they used to be arbitrary), team order is determined by multiplying the number of commits by star average.
On to the full data after the jump.
If you don't have time to watch the whole preview, scroll down for clips of Hoke, Mattison, Borges, Denard, Kovacs and Lewan.
EDIT: I added the FS Detroit preview and changed the title.
BTN Preview (full broadcast):
BTN Preview Torrent:
FS Detroit Preview:
Good morning from the West Coast, my fellow MGoBloggers. As I started composing replies to several comments on the HAIL Fail post, I found my long-winded ways would be best suited for a diary. I'd like to address both the HAIL program itself, as presented and as I think it should evolve, and some suggestions for current students from a '12 grad, and yes, BlueLotCrew, I do have a big girl job.
HAIL: (Honoring Attendance, Involvement and Loyalty!)
Yes, it's currrently a Meh on the Otter scale of Ennui
Silly acronym aside, I'm actually kind of jealous that I graduated before this was implemented since I pretty much lived at Michigan Stadium and Yost. Nice to get rewards for stuff you already do and all. This program isn't targeted towards the already obsessed though, the goal is to get more butts in seats. I do agree with Brian, a free shirt and $5 at Mujo's ain't gonna cut it.
But, still a promising move forward. Why?
It shows that the athletic department is trying to answer a key issue (and yes it's an issue, deal with it, ya drunks). We've bitched about it, they're responding. Let's accept that this is mostly a "test year" where they figure out the technology, implementation, etc before rolling out a long-term incentive program.
At the risk of using some coporate speak, it's promoting a more devoted student culture. For those of you who had already graduated pre-Horror, that game really kicked off a climate change in the student section. I've heard from many alumni, both on the board here and in real life, that they weren't really college football fans at all until their first game in the Big House. Well, you can't deny that the experience hasn't been quite the same in the past few years, and we're all glad to leave that behind us, but we've still cultivated a good 3 years of students whose first football experience was less than inspiring. Understandably, these people who would have normally dove headfirst onto the bandwagon now have to get a little bit of a push, and an incentive program could be that push.
The best incentive? Earning better seats. That would be easily the best direction this program could go in, especially if they could guarantee your seats by your earned point percentile and seniority.
Also, a lot of people have mentioned general admission as a solution. At first blush, that seems like a cool plan until you have people camping out a la Paternoville. If they don't let you line up before gameday, you'll still have huge lines, and if hockey's "not-really-assigned-seating' is any indication, people will cram into the best seats a la phonebooth stuffing and leave the less desired seats very empty. Brian Cook will then take a picture of the empty nosebleeds and tweet it, asking more people to show up on time. The people who got there early will try to tweet back, but their arms are pinned to their sides by a mass of highlighter yellow humanity.
Now, about that key issue, and what you can do about it, ya drunk:
Current students, I know our generation has been called a lot of unflattering things. Lazy, entitled, spoiled, you name it, it's been written in a half-assed trendpiece, and Michigan football is no place for you and your buddies to be reinforcing these stereotypes. Time to get it together and prove to the alumni and yourselves that you can in fact be both a loud, raging fanbase and get your drunk ass in a seat on time like any fan of respectable devotion.
"But CMR, I'm on deck at the pong table and I need to take more picturessss, please advice!"
This is where I'd like to offer my expert advice.
- Four glorious years as an active sorority member, including my junior year where I served as a Rho Omega (rush officer, and yes that's during football season, and yes, at least one rushee called me in a panic at 2am asking what to wear for next set.)
- BSE Aerospace Engineering. DANGER ZONE.
- Attended every home football game from 08-11 without missing a kickoff and without leaving early. Don't ask about Northwestern, my toes are still thawing.
Now, the advice, in list form because everyone knows that's how this generation writes:
- Don't overdo it the night before. Whether you're at a mixer or the Dude, make sure you hydrate (yes, with water, ya damn drunks) and get some quality sleep. Do not be like me and fall asleep at 3am before OSU in 09, only to awake at 5am. I was in top drinking form as a sophomore and ready for Rage 2.0, you probably won't be.
- Because you need to wake up early. There, I said it. If it's a noon game and you need to get your drink on, you need to at least wake up by 6am. How much time it takes you to get ready should be factored into this as well.
- DON'T FORGET YOUR DAMN TICKETS. I may or may not have written this on my arm in Sharpie during sophomore year. This is not a run you want to make, and you need to remember to include "tickets, Mcard," in your phone-wallet-keys patdown.
- Make a pregaming plan with your amigos. This was absolutely essential, because gameday communication is LOLtastic at best. Figure out breakfast, where/when you're meeting who, if you need to stop by to say hi at your parents' tailgate relatively sober, and give yourself a half hour from leaving a State St. pregame to get to the stadium.
- Stick to the plan. Believe me, your cameras will still work for group pictures at the stadium. Also, unless there is a medical emergency, stragglers should get one warning before being left to their own devices. I MEAN IT, LINDSAY!
- DON'T STAND IN THE LONGEST LINE AT THE STADIUM. Yes, the Hoover entrance will probably be closest, and yes, you will be sitting there for some time, especially if it's Parents Weekend. Go around to the ones near Crisler or on Main Street. Just because the student section is in that corner on Hoover doesn't mean you have to enter there.
With that, I welcome your
scathing disagreements thoughtful comments, though I may not be able to reply for a while because I have to be early to my flag football game on the beach to maintain my priority points. I think I can get used to this California place.
ANN ARBOR-- The fashion world is abuzz with enthusiasm after images of the 2012 Fall MGoShirt line were leaked last night. Less than twenty four hours after MGoBlog member and reported WikiLeaks contributor JeepinBen* published the images, UGP and designer Six Zero are proud to unveil the offerings with this official press release.
Without further ado, then, please welcome the MGoShirt 2012 Fall Collection (To get a closer look, or to order a shirt, please click on the corresponding image):
A bold and stylish ode to culinary delight, this tee celebrates the hunger we all feel as the season draws nearer... and the feast we shall all enjoy starting September 1st. Available in S-3XL.
The Flow, Brunettes, and more after THE JUMP!
(Click the image to view full size)
Yeah, so you might not want your boss to catch you chuckling at this one too much. Good luck to everyone in their grand illusions of productivity for the next eight days. That's right-- ONLY EIGHT MORE WORK DAYS until Season 133.
On Thursday Desmond parts ways with his filthy no-good Buckeye girlfriend.
THE BLOCKHAMS™ runs (typically) every Tuesday here at MGoBlog,
and at least every Thursday on its official home page. Also, don't forget to
check out Friday Roughs, a spontaneous low-end comic based on trending
Michigan events, available on Twitter and Facebook every Friday.
(tl;dr? Skip to the Conclusion at the bottom)
After a lot of discussion on this site about how random turnovers are, I decided to look at them in more detail. My hypothesis was that, while turnovers as a whole may appear very random, individual components of turnovers might be much less random. For example, as has been discussed before, once a fumble is on the ground it appears to be very random who recovers it. But what if causing a fumble is not random at all? The randomness of recovering the fumble might still obscure that fact if you only look at turnover margin.
I decided to look at five components of turnover margin: interceptions gained, interceptions lost, fumbles when on offense, fumbles when on defense, and fumble recovery rate.
I used whole-year statistics and compared the change from one season to the previous, using a total of 6 seasons worth of data. In college football there are, of course, many factors that change from year-to-year, but if there’s very little luck involved, I would still expect to see a decent correlation from year to the next. For simplicity, I assumed a linear relationship between stats from one year and the following year, so the analysis used linear regression, a simple but reasonably robust model.
The R-Squared statistics (simply the correlation squared) gives us an understanding of how much the variability is accounted for by our model. In simpler terms: how much is success in the stat from one year accounted for by the success from the year before?
All data was obtained from www.teamrankings.com. Data was always rounded to the nearest tenth by the source—because interception and fumble frequency are fairly low, this rounding may have a larger-than-ideal impact on the results; if anything, I would expect that should in general impact the results negatively (make them appear more random).
I next look at those five components of turnover margin: interceptions gained, interceptions lost, fumbles when on offensive, fumbles when on defense, and fumble recovery rate. The R-Squared values are:
Interceptions Gained: 0.057
Interceptions Lost: 0.049
Fumbles on Offense: 0.016
Fumbles on Defense: 0.001
Fumble Recovery Rate: 0.003 (the correlation is actually negative)
The first result that jumps out at us is that interceptions appear much more repeatable/less random than fumbles. Interceptions gained and lost in the previous year account for about 5% of the success the following year, compared to under 2% for the number of fumbles on offense. Fumbles on defense and fumble recovery rate appear almost completely random.
(For those still unconvinced that fumble recovery rate is almost completely random, the best team from each year did decently at best the following year--Michigan was 1st in 2006 but 47th in 2007, which tied for the best performance by a returning #1.)
Providing Context by Analyzing the Optimum
The previous analysis tells us a lot about how repeatable results from one year are, but it doesn’t really tell us about how much is skill vs luck: after all, stats in a college sport ought to vary a lot from year-to-year: there is player development, new players, potential coaching changes, different strengths of schedule, and many other factors.
To provide an optimal baseline, I also looked at offensive and defensive yards per game. Intuitively, that’s a statistic that should be very greatly influenced by skill (though there are certainly amble sources of other influence, including luck). This will provide context by helping us understand what kind of change we should expect to see due to year-to-year variance (player or coaching changes, player development, changes in strength of schedule, etc.) instead of due to randomness.
For offensive yards per game, the R-Squared value is 0.243, while for defensive yards given up per game, the R-Squared value is 0.275.
Roughly 25% of success being accounted for by the previous year’s success is not very high, but that’s not a surprise—again, there is lots of change from one year to another. What this is helpful for is to provide context: even if turnovers are very skill-based, we would still only expect an R-Squared of .25.
There are two ways to view the turnover margin numbers: the first is viewing them in isolation. Even the best component of turnover margin, interceptions gained per game, is not very repeatable: success one year accounts for under 6% of success the following year.
The second way is to view them in comparison to the yards-per-game stats. With this perspective, interception rates on both sides of the ball are a little under one-quarter as repeatable as yardage. If we assume that yards-per-game is heavily impacted by skill, interception rates are likely fairly impacted by skill as well. I would hypothesize that within a given season, teams that are good with interceptions on either side of the ball will be likely to continue being good.
Fumbles seem to be much less skill-oriented. Fumbles lost is less than 1/15th as repeatable as yards-per-game. Fumbles forced on defense and the fumble recovery rate are almost completely random. (What this really says is that almost all teams are roughly equally good, not actually that there’s no skill in forcing or recovering fumbles.)
With total yardage, since 75% of success remains unaccounted for by the previous year’s success, we’d expect that it’s made up of two different things: randomness and other factors. If offensive yards per game is, indeed, not very random, that means outside factors (returning starters, returning coaches/schemes, different strengths of schedule) will have a large influence. This is important—we may be able to take some of these into account to improve the prediction we’d get based on just the previous year’s results.
Likewise, while interceptions are not very repeatable overall, they’re still about one-fourth as repeatable as our optimum. In a very rough estimate, we might then guess that outside factors also have one-fourth the strength with interceptions. Thus, if up to 75% of yardage success is outside factors, then up to 18% of success in interceptions is accounted for by those factors (this is very rough, since the factors may be quite different, or at least have different impact). That would leave roughly 76% of even the most skill-based category as random (100% - 6% based on previous year – 18% based on outside influences). The same rough calculation gives 5% of offensive fumbles based on outside factors, and 93% based on chance.
In summary, there is definitely some repeatability in three of the five turnover factors, but even the best of those still has under 6% repeatability, and by a very rough estimate, is still 76% random.
Implications for Michigan
In 2011, Michigan was 34th overall in turnover margin per game, with +0.4. That’s good, but not amazing, despite Michigan’s stellar fumble recovery rate.
There are three factors I’ve identified and tried to account for: repeatability based on the previous year, outside factors, and chance.
Statistical repeatability bodes poorly for the Wolverines, unfortunately: the two most repeatable categories were the two at which Michigan did worst: Michigan was 82nd and 89th in interceptions gained and interceptions lost, respectively. Michigan’s best two categories, fumbles on defense (28th) and fumble recovery rate (1st) are basically random. In the fifth category, fumbles on offense, Michigan was a decent 42nd.
The second factor is really a category: outside factors, which probably impact interceptions the most. This seems positive for the Wolverines: returning Denard and the defensive backs, plus a coaching staff (an outside factor that would have pulled last year’s number down). Michigan’s biggest loss is Junior Hemingway, who certainly bailed Michigan out a few times last year.
The last category is randomness, which appears to have a very large impact on even the most skilled category, and complete control over a couple of them, meaning any real prediction is fairly foolish. To be a little foolish, then, I’d guess that interception categories improve to above average (say low 40s), but overall turnover margin gets worse, dropping to the 50s. However, I have only slightly more confidence than I do when calling a coin toss.