When it is all said and done, there will be some public apologies handed out to Rich Rodriguez and his staff. Woe to the man who brings change! This has been the saying echoing through the eons of human existence. And last year, the University of Michigan Football program literally began a cycle of change that created a great upheaval. Perhaps one of the greatest the school has ever known, at least for many of its fans that is. To the Michigan fan, they know about the stadium renovations and the new offense. To the non Michigan fan they love to stoke the coals of a miserable season. Or to put it another more simple way, they just love to see Michigan fail. And for some people the emotional investment begins and ends with bragging rights, and not the process it took to earn those bragging rights. From the transferring of players, coaching changes, injuries, weight room time, bad officiating and so on the list of things facing a new coach is endless. And then when you silent the angry seething madness of fans they just want and expect more. Where does it end? Give Rich Rodriguez credit for taking the job because I am sure some coaches turned it down. Because to be the new guy at a storied school like Michigan, should it go bad, could mean the end of your head coaching career.
Building a community is a tough thing to do. You have to get people to build it and want to keep giving back to it while embracing the larger community at the same time. And this is tough to accomplish from a sales perspective if your community is not going so well. When you bring about change into an established community it is even more difficult. And at the University of Michigan last year the football fans showed a big time reason why this is. They were angry at the losses and confused as to what happened. The community was crumbling; opposing teams heckled and threw verbal elbows. The Michigan fan was surrounded it seemed and its old Big House was no place to hide.
Not to fear though Michigan fan, your coach did not exactly do too shabby in recruiting. He landed a 4 star QB in Tate Forcier and really accomplished something herculean. He kept a 5 star recruit in state in big time William Campbell. All in all a class of nine 4 and 5 star recruits after a season of low output. And it was also a season where kids committed, decommited and recommitted at record paces. The rocky waters navigated, the Michigan hater must now look on and wonder if Michigan Football is Bullet Tooth Tony from the movie Snatch. Through the rough transition Michigan found new legs and new life.
I for one know the struggles this team must embrace this coming year. And I hope that they do. It will be another year of forging an identity in the face of not being the great Michigan of old. But in the struggle to get there boys, you are becoming. I hope we as fans remember that as well.
See yah at the Spring Game,
So here I am watching Pittsburgh play Xavier last night, and I am wondering about the talent I am seeing on the floor. Each position looks very skilled, and I am comparing them in my mind to Novak and Douglass and Lee and Merritt. It seems like no comparison, but Michigan came very close to playing in the Sweet Sixteen, so I ask myself: "Self, is Beilein great, am I underestimating our guys or what?" Don't get me wrong. I LOVE Novak and Douglass and Lee - love those guys who play their hearts out and play smart. I had no skills but played hard and therefore didn't suck at times.
So, what am I looking at (pulled only guys with double digit MINS per game)?
NOTE: Sorry about the readability issue. It looked much better as I laid it out.
NAME PTS RBD AST TO BLK STL MINS
S. Young 18.9 6.2 1.1 2.4 0.8 1.0 31.7
D. Blair 15.6 12.4 1.2 1.2 1.0 1.5 27.1
L. Fields 10.7 2.5 7.5 2.0 0.1 0.8 32.2
J. Dixon 8.5 2.6 2.0 1.0 0.7 1.4 24.7
T. Biggs 6.6 4.3 0.7 1.0 0.5 0.4 24.0
B. Wanamaker 5.8 3.3 2.1 1.7 0.2 0.8 18.7
G. Brown 5.3 3.2 1.3 1.1 0.3 0.5 19.4
NAME PTS RBD AST TO BLK STL MINS
B. Raymond 14.1 4.1 1.4 1.6 0.3 0.5 30.3
D. Brown 13.7 6.1 1.9 1.7 0.9 0.7 29.5
C. Anderson 9.9 5.5 2.5 2.3 0.5 0.7 27.2
J. Love 6.7 5.9 0.5 1.3 1.2 0.4 21.7
D. Jackson 6.6 3.5 2.7 2.0 0.1 1.3 27.1
T. Holloway 5.5 2.0 2.2 1.9 0.1 0.7 21.5
K. Frease 5.4 3.7 0.8 1.7 1.3 0.3 14.6
B. Redford 5.1 0.6 0.6 0.6 0.1 0.3 12.8
J. McLean 4.4 4.4 0.7 1.1 0.7 0.4 14.6
Who are these guys that make up two very good teams and what does it say about Michigan basketball (if anything)?
Their star rankings and year...
NAME STAR YEAR
S. Young **** SR
D. Blair **** SO
L. Fields **** SR
J. Dixon JR
T. Biggs **** SR
B. Wanamaker **** SO
G. Brown **** SO
NAME STAR YEAR
B. Raymond *** SR (2005 commit)
D. Brown *** SR (2005 commit)
C. Anderson JR
J. Love *** JR
D. Jackson **** SO
T. Holloway **** FR
K. Frease **** FR
B. Redford *** FR
J. McLean *** SO
I put the "2005 commit" next to Raymond and Brown because they are showing more eligibility, so I assume redshirts, but something ain't right in the database.
Anyway, there is a lack of five stars - although Pitt is loaded with four stars - and clearly leadership from the 2005 guys. As a formula, it would suggest that Beilein can make serious hay with a steady stream of seniors and maybe a four star guy in every class. Both those things are very likely to happen, as Michigan will clearly go in a different direction than Ohio State...
"The 7-foot freshman [Mullens] announced Thursday he would declare himself available for the NBA draft, the fifth Buckeye's player in the last three seasons to leave after playing one year."
I think the upside for Beilein is scary.
I have seen comments on several sites about this and I just want to point out that losing the star of last years Michigan v. Penn State game is not great but this should hopefully be a Non-issue. This is assuming that the injury is a broken leg, not something major and the medical staff is being extra cautious.
Postives on this...
- Tate will get even more time with the 1st team and should get extra snaps in the short spring practice season.
- This should solidify that the race to be the opening game starter is wide open.
- Creates some options to re-evaluate the experiments at the QB position that include: Carlos Brown and Justin Feagin.
- Asks the team to rally around Tate and may officially signal the start to his era as the starting QB.
- At least he was out and about, so the injury probably isn't in great need of any major surgery.
- Sheridan can use all the practice he can get.
- David Cone might be forced to throw the football with a helmet on to someone that should actually see the field in the fall.
- The urgency to get Denard Robinson on campus and practicing just became even more apparent.
- This could diminish the QB competition between our two best options for the fall.
Hopefully there is some good news from Richrod today, and that this is just precautionary.
Update at bottom
Update 2 at bottom
Note: This is a long and complex read. I know that. I'm looking for assistance with a project I'm working on that I know everyone will be interested in. If you wish to skip all of the reading, I have summarized everything in bullet points at the bottom.
I had hoped to keep this my little secret until I was completely done and I could unveil everything at once, but I no longer believe that I could do this project as efficiently without some other input. As an engineer, I require myself to do everything with as high efficiency as possible so I must petition the MGoBlog community for help.
As many (more likely all since you're on a site like this) of you are aware, there have been more and more threads being posted which essentially go down as so:
Poster 1: "We're going after slot-dot X and he's only 3 stars!. Argh! Doesn't RichRod understand he's not at WVU anymore and he needs to get MICHIGAN quality recruits. RichRod=Fail."
Poster 2: "Stars don't matter, obviously RichRod thinks that he's good enough and that's good enough for me."
Poster 3: "Rankings are early, they'll change, just settle down for now"
Poster 2: "He's only 3 stars but look at his offer sheet, I'd take someone that's 3 stars with offers from USC, OSU, UF, 'Bama, etc. over a 5 star with offers from us and the MAC."
Poster 1: "Stars do matter, you need talent!"
Poster 2: "Mike Hart, Braylon Edwards... nuff said"
And so on and so on.
So, I started thinking about rankings and their usefulness at predicting future college and pro success. To that end, I'm going to undertake what I believe will be the largest statistical analysis of recruiting rankings to date. But I need some help.
Let me describe what I'm planning on doing, what I've already done to accomplish that goal, and what I still need to do. Then I'll finally be able to show everyone what I need help with. You'll also be informed enough to offer criticisms, advice, and ask questions if necessary.
1- What I plan on doing
I'm going to take all recruiting data from Scout and Rivals from 2002-2009. As of right now, that includes: name, positional rank, number of stars, HT/WT/40, position, hometown, and home state. I'm then going to also compile data on how many starts each player had in each year of his career, if he redshirted, if he left early for the draft (manifested as number of years of eligibility remaining), the number of All-Conference honors received, and the number of All-American honors received. I will also take information on if they were drafted, what round they were drafted in, what overall number they were drafted as, what position they were drafted for, and what team they went to.
Once I have all of that data, I will first do a top-level analysis to see, independent of everything else, how star rankings alone are at predicting collegiate and pro success as defined by the stats that I will have collected above.
From then on, I will keep trying to dig further to get more and more relevant models and conclusions. This will include but will not be limited to how the average rankings of the other players around another player (independent of that player's rankings) affect collegiate/pro success, the number of blue-chip recruits that completely fail, the number of blue-chip recruits that leave their home state, the average team ranking, success of rankings at predicting success at each individual position, the affect of positional ranking on future success, etc.
I'm going to try to come up with as many ways as possible to analyze the data that either decouples the data or gives conclusions that are independent of coupling. Figuring out how to do that will be difficult but fun.
As a side note, this will also let me eventually compare Scout and Rivals to say with some authority, whose [final] rankings are more accurate.
Of course, I will also apply standard statistical analysis procedures to determine if my conclusions could be deemed statistically relevant or not (I don't know with what percent confidence yet so don't ask).
2- What I have done
It's all well-and-good to have thought all of this out, I'd be willing to wager that at least one other person currently reading this has thought about it, but thinking alone won't get any of us anywhere. So, I've started to do a lot of the grunt work as a sign of my commitment so that people will understand that I'm dedicated enough to make helping me worth their time.
I have already collected all of the information from Rivals for every class and every player.
So, for the classes from 2002-2009, I have every name, positional rank, Rivals Rating (RR), star rating, position (as Rivals breaks it down), and what school they committed to.
I have also created an Excel spreadsheet template that will allow me (once I get all of that data) to merely copy and paste a few things from Rivals and all of the data that I have on every player will be retrieved. With that, I will be able to create a spreadsheet for every BCS team (as Rivals only has complete listings for BCS teams) which will have every class and all of the data for each kid in every class all in one spot. Then I'll be able to do my analyses more easily.
3- What I still need to do
Obviously I'm still not done with the collecting data/grunt work as I still have to take all of Scout's data. It's taking a little while because of the way that they format their data compared to Rivals. Fortunately, I have solved the problem and can now do the usual copy and paste (followed by several other things to make it all work).
I'm considering also grabbing data from ESPN but I'm really not sure if it's even worth it. They only have data from 2007-2009 (I believe) so that doesn't even include a class that been drafted yet.
More importantly, I need to find a source for the other data that I'm trying to collect. I need to find some place(s) that lists all of following:
- If a player redshirted
- Number of starts each year
- Every All-Conference team (not just first team) for all BCS conferences starting from 2002
- Every All-American team starting from 2002
- Every transfer since 2002
- What position each player was drafted for
- Individual player positional statistics (e.g. completion percentage, interceptions, tackles for loss, etc.)
There is also some other data that I’m going to try and collect but I already have sources for that so it need not be listed here.
4- What I need help with
I need help finding the data that I list above. Pieces of it are available everywhere but I haven’t found a single site that has a repository of all the information implied in even just one of those points above.
Additionally, getting individual statistics is extremely hard. But, it would allow more comparisons than possibly anything else. But, there are literally tens-of-thousands of players. There were over 1000 wide-receivers in 2009 alone! There are simply too many players to try and go to each player individual profile page somewhere and collect the data. I, unfortunately, require lists. That is, unless there is some tool or way to automate that data collection process. I myself know of no such way but that is one of the reasons that I’m asking the MGoBlog community for help, because I don’t necessarily know everything that I could do to make this project as easy as possible (at least on the data collection front).
I’d also like to find a way to collect data on all of the schools that have officially offered a kid a scholarship to see if there is some way to show that stars or scholarship offers is, statistically speaking, the best measure of a kid’s future ability. Again, I can’t go to every Rivals profile page to try and collect that data. This is one area where I feel that since the pages are so similar, it might be possible to write some sort of script to do the work for me. Unfortunately, I’m a ChemE and MSE person, not a CSE person (for those of you outside the engineering that’s Chemical Engineering, Material Science Engineering, and Computer Science and Engineering respectively) so I don’t know what tool or utility I would go about using to accomplish that. I am in Tech. Services so I’m sure that if someone pointed out to me the appropriate tool and maybe some documentation on how to use it then I wouldn’t have any problems.
I know that what I wrote above was long so here’s the summary (whether you read everything preceding this or not).
I’m going to perform a statistical analysis on Scout and Rivals to determine how good their final star ratings and positional rankings are at predicting future success both in college and the pros. To do so, I have already collected the data from Rivals and am currently working on collecting data from Scout. I will probably not take data from ESPN although that is not a certainty.
To determine collegiate success I will take data that includes but is not limited to All-Conference honors, All-American honors, and the number of starts. To determine pro success I will take into consideration where a player was drafted and for what position.
I know where to acquire some of the information that I need but I still need help finding useful places to take large amounts of data on:
- All-Conference teams
- What position each player was drafted for
- Number of starts by each player
I would also like to find a way to automate data collection, specifically with an eye towards collecting data on what schools offered each kid a scholarship. Since there are tens-of-thousands of kids this cannot be done individually but must somehow by automated. I do not know how to do that and am thus asking for help. The same situation applies for collecting individual, positional specific, statistics on each kid.
If anyone would like to help me out with what I have asked, then I would greatly appreciate it. Any criticisms will be well-received (or at least as well-received as I can) and taken into account. Any comments or other thoughts are also welcome and appreciated.
For more information, read the sections above.
Since so many people have responded with helpful ideas, if you wish to contact me with anything that you either don't want to post in the comments, is too long and complicated for the comments, or that you wish to have a more private dialogue about then email me at:
That's not my main email so I won't check it as often (i.e. not every 20 minutes) but I'll try to check it at least once a day. If you want to send me anything, links or other work that you've done that might help me, then send it there.
Thanks for all the great ideas and please keep them coming. I'm still thinking about ways to handicap a teams that have a lot or a little talent relative to the average (for reasons that are too long to fully explain in this update, although there are some interesting thoughts on why and how in the comments below). I'm also looking for ways to automate the data collection process. There are a few suggestions below but I'm going to be looking for more so please tell me.
Again, I prefer using the comments if possible but if not then email me.
Update 2: 3-27-09
Well, it's been pointed out in the comments and confirmed by me that the email address is listed above doesn't work. That's because I had a small typo. Of course, small typos in email addresses are big typos.
Anyways, the correct email address is: [email protected]
If you tried emailing me earlier with the previous email address then please try again. I appreciate your patience.
I've always admired people who are able to argue forcefully about a topic without getting personal, attacking, or losing their temper. It seems a rare quality these days, especially on the web, where the cloak of anonymity seems to lend itself to comments that, were they made in person, would likely get someone's ass kicked.
One of my best friends at M was politically the direct opposite of me. At the time we were both on our way to law school, and very much into philosophical and political debates, which sometimes degenerated into yelling. Yet it never got personal, and it was forgotten by the time we entered Rick's. And while we don't keep in touch much, I consider him one of my best friends.
About a year ago, I saw a profile of Justice Scalia on 60 minutes, and what struck me most about it was they said that the two best friends on the Supreme Court were Scalia and Ruth Bader Ginsburg, his direct opposite politically. They asked him about it and he said "I don't argue with people, I argue with ideas." I thought that was pretty rare.
While I haven't always lived up to that standard myself (especially when I read some troll on the Freep website), I try to. I've thrown around "you're an idiot" too much, and turning to this site, I see that thrown out or worse quite a bit in the majority of threads. I wonder if you guys think the overall tone of this site and the comments section is: A-about right, B-too accusatory and personal, or C-not personal and derogatory enough asshole!
Not that "you're an idiot" is not ever deserved. There was a thread the other day about poole1dan, who defined the word idiot and worse in his comments. In fact I went to youtube, where he has a channel, to tell him he was ignorant and giving the rest of us a bad name. More (perhaps) deserved scorn might go to that guy who ignores actual facts in favor of his argument (e.g. the recruiting rankings don't matter guy)... debatable anyway. Not debatable is that guy who says that Brian is an idiot (poole1dan again), or calls people he doesn't agree with idiots simply because they have the opposite opinion. You may or may not agree with Obama, but clearly he is an intelligent guy who deserves respect.
So, this may too much of a Rodney King thread, but I'd be interested in the replies. I love a good argument, but like going to get a beer afterwards a lot more.
Now that the initial Scout 300 and Rivals 250 have both been released I thought it would be interesting to compare the two sets of early rankings. Below I have recorded both rankings for recruits of interest (if I missed any, help me out). I have also averaged the two to reach a composite ranking for each player, which I'll call the player's "preliminary consensus" ranking.
Disclaimer: I think rankings are imperfect. I know they evolve. I do not think they guarantee success or damn a player to mediocrity; but neither do I think they are worthless or arbitrary. I hope this post invites comments about the rankings themselves, but not another tired back and forth over their general validity, e.g. "rankings don't mean anything" -- "yes they do" -- "what about successful 2/3 star player X?" -- "but look at this NFL draft data" -- etc.
2010 "Preliminary Consensus"
 Seantrel Henderson (S:1; R:1)
 Marcus Lattimore (S:2; R:4)
[4.5] Lache Seastrunk (S:7; R:2)
 Jackson Jeffcoat (S:6; R:6)
[9.5] Jeff Luc (S:9; R:10)
 Kyle Prater (S:10; R:18)
 Jordan Hicks (S12: R:16)
[32.5] Robert Crisp (S:36; R:29)
[45.5] Christian Green (S:54; R:37)
[50.5] William Gholston (S:57; R:44)
[54.5] Mack Brown (S:63; R:46)
 Chris Dunkley (S:93; R:61)
 Tai-ler Jones (S:81; R:101)
[107.5] Dietrich Riley (S:70; R:145)
[118.5] Corey Brown (S:168; R:69)
 Ricardo Miller (S:115; R:123)
[123.5] Marvin Robinson (S:148; R:99)
 Devin Gardner (S:77; R:177)
[133.5] Brennan Clay (S:155; R:112)
[135.5] Dior Mathis (S:137; R:134)
[139.5] Latwan Anderson (S:213; R:66)
 Chaz Green (S:127; R:155)
[158.5] Robert Bolden (S:83; R:234)
 DeJoshua Johnson (S:210; R:114)
 A.J. Cann (S:212; R:162)
 Nickell Robey (S:265; R:125)
[197.5] Jerald Robinson (S:157; R:238)
[199.5] Jeffrey Godfrey (S:215; R:184)
[202.5] Josh Furman (S:105; R:X)
[210.5] Austin White (S:121; R:X)
 Jay Guy (S:140; R:X)
 Brandon Ifill (S:154; R:X)
[240.5] Torrian Wilson (S:X; R:131)
[251.5] C.J. Olaniyan (S:203; R:X)
 Caleb Lavey (S:214; R:X)
 Cullen Christian (S:254; R:X)
 Nick Hill (S:262; R:X)
[288.5] Austin Gray (S:277; R:X)
[291.5] Kenny Shaw (S:283; R:X)
[296.5] Scott McVey (S:293; R:X)
Unranked of interest: Jeremy Jackson, D.J. Williamson, Lo Wood
Note on methodology: For players not ranked in the Rivals 250, I computed the Rivals half of their composite ranking with a value of 300. For players missing the Scout 300 I used 350. This is admittedly inexact. It may punish a player too much for not making the list (or not enough).