Beilein by Fuller, Orr and Ooster via Bentley.
I got this question from PeteM on the board: Where does John Beilein rank among Michigan's all-time basketball coaches?
The question is subjective since everyone has their own criteria. Mine: wins (total), winning percentage, Big Ten regular season titles, tournament success, All-Americans/NBA prospects, and general good guy-itude.
Non-candidates for completeness:
I kept Cowles out of it since this was getting long and he only coached for a few (wild) seasons, wherein he dragooned football stars and developed the pick and roll.
For ease, I call the 2013-'14 season "2014" etc.
* Rather than winning % I showed their average record over a 30-game season.
** NCAA tournament factor, equivalent to average number of tournament games his teams would play in. A 1.00 means his average team will make the tourney and go out in the 1st round. I took out the play-in rounds.
† This could as well be 7 or 8: Manny Harris was recruited by Amaker but played his entire career for Beilein. Stauskas, GRIII, LeVert, and McGary at least can be counted as future NBA players. It's too early to say the same for Walton/Irvin but it's not a bad bet either.
I ended up breaking this up into two posts because it was getting long, so here's the candidates chronologically through Johnny Orr:
|Mather [via Wikipedia]|
E.J. Mather (1920-'28)
Career at M: 9 seasons, 108 wins (67%), 3 Big Ten titles (1 outright)
All-Americans: Bennie Oosterbaan (1927 & '28), Richard Doyle (1926), Harry Kipke (1924)
Pros: Kind of pre-dates that.
Story: Took over a young program and went 3-9 his first year, then tied for the Big Ten championship his second, winning his last 8 games of the season to tie Purdue and Wisconsin at the end. The 1926-'27 season, when Bennie Oosterbaan lent his talents, was the best; Michigan went 10-2 in-conference and 14-3 overall. Soon after that season Mather had major surgery for cancer, and wasn't the same after that. Yost coached the 1927-'28 team in Mather's name; the cancer claimed his life that August.
Thing: Mather was also a Yost football assistant, and two of his players later became football coaches.
Better than a Beilein: It's tough to judge that far back or guess what the future might have held, but he didn't have a nationally competitive team until his 8th year so I'm comfortable putting him behind.
[After the jump it gets tougher]
Tourney face. [Fuller]
Beilein teams go further in the tournament than their seeds. This is known. We've repeated it so often that smart bracketeers even calculate it into their expectations. I've saved the "why" and "wherefore" of this effect for a roundtable question since that gets into the basketball strategy stuff that I'm weak in.
What I can do is build a pivot table out of multiple bits of data; in this case it was lots of schmearing and pasting, column breaks, and vlookups from sports-reference.com's bracket history and annual coaches records. The important lesson here is you're supposed to know it was hard.
UPDATE: Here's the raw data.
The first thing I tried was straight-up expectations by seed: top seeds are expected to get to the Final Four, 2-seeds to the Elite Eight; 3- and 4-seeds to the Sweet Sixteen; 5-, 6-, 7- and 8-seeds to the round of 32. The results had Beilein #5 after Brad Stevens of Butler, Sean Miller, and some Mizzou coaches who often had 9 seeds. That suggested there's a problem with my figuring:
I'm expecting 9 and 10 seeds to never advance so they're always in the positive; every time an 8 loses to a 9 it's a hit. The actual distribution is, unsurprisingly, progressive:
With over 1300 teams in my study there's very little deviation from the logarithm. It suggests, for all our complaining, that the committee does a pretty good job.
|Seed||Exp Wins||Seed||Exp Wins|
Since I'm a history major who had to re-teach himself exponential functions this morning (if predicting basketball games required encyclopedic knowledge of Plantagenets I'd have Ken Pomeroy's job) please go easy on me if I dispense with the other stuff and just use the values Excel returned as a base expectation of tournament victories for each seed (at right). The formula according to Excel:
y= 1.1634Ln(x) + 3.2127
With an expectation for victories now I can get a reasonable comparison versus that, for example a 2-seed that advances to the Sweet 16 has 2 victories minus 2.41 expected = 0.41 fewer wins than they should have. The last thing was to remove coaches who've been to fewer than five tournaments. We're ready to rename March after a coach. But which one?
[Don't act all surprised; you knew I'd make you jump for it.]
Site note: As with last year, we'll be having a basketballgasm liveblog for Day 1 of the tournament, shifting to the hockey game at 3, and then going through the Round 1 matchup with Wofford. DraftStreet, whose 40k tourney is still filling up (as of this morning ~1600 of the 2000 spots are filled), is sponsoring, and a few former players will be joining us to promote the Go Blue Bowl.
Speaking of filling things, you're probably filling your brackets right now, so here's my now-annual post and tool for helping with that. Last year was the first since 2000 that I didn't win at least my buy-in back. Things I use:
The Power Rank (friend of the blog Ed Feng)'s interactive bracket. Ed is one of the cutting-edge guys in sports analytics. On his tool if you hover over any team you can see their probabilities to reach each round, or hover over a spot in the circular bracket to see every team's likelihood of getting there. Michigan is 58% to reach the Sweet 16; from there every game is virtually a toss-up.
The Wall Street Journal's blind comparison. They show you two profiles and say a little about the team, and you make your pick presumably without bias, though you can often figure out exactly who they're talking about:
Bracket Science's Bracketmaster tool. Peter Tiernan's blog is a standard for following bubble teams and gets things right that others don't (like Louisville as a 4 seed). The Bracketmaster+ tool lets you get into data going back to 1985. If you're a member it gets deeper but non-members can use it to do things like show Beilein's Michigan teams in the tournament:
Poologic Tool. This helps you decide how many upsets to pick based on the size of your office pool (in a large pool it's best to be the only one with a certain champ). Also you can calculate ROI on various picks.
My tool (download the excel sheet) Which uses straight-up Kenpom scores and provides a weak confidence score based on the premise that 16 seeds never beat 1 seeds. I also added injuries for each team. Looks like this:
What I do is normalize the closest 16-1 matchup (Wichita St vs. Cal Poly) as 100% for the 1 seed to win, set that as the "chaos factor," and use the KenPom ratings to percentile everyone else's games into a confidence number. Then I roll through anything under 70% and decide if my knowledge of those teams might justify taking the under.
If you're in a big pool, run multiple brackets, each with carefully selected upsets.There's no such thing as an NCAA tournament without lots of big upsets and at least one surprising run. The 1 seeds all made it to the Final Four just once. If you submit one milksop bracket you're up against every other milksop bracket and will get beat by the one crazy guy who had LSU going to the Elite 8 or something. Hitting on a carefully selected upset that rearranges a bracket and lets you ride a different high seed to the Final Four is the most typical route to a win.
If you're in a small pool, play conservative. One or two points won't usually make a difference in a small pool, but the likelihood of something crazy like that one guy's wife who picks based on the cuteness factor of mascots winning is cut down so you don't need to take risks to get ahead.
Pick the upsets the most carefully. I love picking 6-11 upsets because if you get it wrong they're bound to get wiped out by the 3 anyway. If you roll the dice on a 3-seed or lower losing early though, you'll feel like an idiot as the rest of your pool collects the easy points. A tournament without upsets never happens, but neither does a tournament with all the upsets. You can totally undo a great pick with a terrible one elsewhere.
Get value for your upsets. Know who's in your pool and the inefficiencies. This year, those of you in Michigan are facing the mother of all inefficiencies in that Spartan fans are bound to submit extra brackets just to have one that has State going all the way. Fans will generally take their favorite team to go two rounds later than they really belong and conference teams to go a round further. This is an inefficiency (even if MSU looked like they could dominate the tourney on Sunday).
Be really really lucky. This is really the only rule.
My regional breakdown, still.
After I did that regional study of football talent production by state, Michael Elkon (Braves & Birds, SB Nation, regular HTTV contributor) asked if I'd do the same with hoops recruiting. I responded that I'd love to, but we just had our first child and I need some time to stare at her. This is also my response for why I didn't have any content last week. In fact it is my excuse for everything; to those who don't have kids I can say "you don't understand" and they have to shut up because this is the ultimate trump card. Those who are already parents keep quiet because they're in on it. Having kids is AWESOME!
Anyway it's back to work, and because it's me that means charts. So back to charts.
This is NOT exactly accurate
Data are from the Rivals (most easily accessible) databases since 2003. Putting lists of football and basketball recruits against each other is not a one-for-one comparison. Basketball has more teams, fewer recruits per team, way more international players, and players who went directly to the NBA or committed to Kentucky or some other stupid one before they're done with the pretense.
Top basketball players are also far more likely to go to prep schools, and these are often nowhere near their hometowns. The Rivals database lists actual hometowns for many prep players, but not international ones, so, e.g., Canadian from Canada Nik Stauskas registers as a Massachusetts recruit despite being from Canada. Where a hometown was noted I used that. Some states will appear disproportionately large because their prep programs draw kids from around the region, but that is also an advantage to the schools near the prep programs.
Talent Supply By Region
As with football, the Southeast appears to produce a disproportionate amount of talent compared to its population, but to nowhere near the extreme as it is with football. Observe:
|Region||% U.S. pop
|% of Top ~400
|% of Top ~400
|Atlantic||22%||20% (-2)||15% (-7)|
|Midwest||18%||18% ( - )||14% (-4)|
|Northeast||5%||6% (+1)||1% (-4)|
|Pacific||19%||14% (-5)||14% (-5)|
|Plains||17%||17% ( - )||18% (+1)|
|Southeast||19%||25% (+6)||38% (+19)|
The Atlantic, Midwest, and Northeast are considerably better represented, suggesting a marginally higher basketball orientation than the national average. My guess is this has a lot to do with the fact that it doesn't snow in gyms.
The list of top states in proportionally producing more basketball talent was heavily influenced by the prep school effect: New Hampshire (more than 3x their share of hoops talent) was done by three schools: Tilton, New Hampton, and the Brewster Academy. Most of Nevada was Findlay Prep, and Bishop Gorman sent most of the rest. Leaving those aside, the big basketball states (proportional to their population) were Kansas (209%), D.C. (202%), Mississippi (185%), Georgia (183%), Iowa (172%), Virginia (166%), North Carolina (154%), and Indiana (150%).
There's a reverse prep effect at the bottom: Vermont and Rhode Island were drained by New Hampshire it appears, and Delaware seems to have sent their kids to Virginia or D.C. The remainder to produce less than half as much talent as you would expect from their populations: Alaska (17%), Montana (25%), Colorado (34%), Nebraska (40%), New York (41%), South Dakota (45%), and New Mexico (47%).
Michigan (3% of the U.S. population, 2.4% of the top basketball talent) was about in the middle, about even with Wisconsin, Oklahoma, Missouri, Ohio, and Arizona. Straight-up Michigan is the 14th biggest producer of basketball talent, and the 12th biggest producer of football talent. I thought the more interesting stat was within the Midwest (that above table), where Ohio produces nearly half of the top football prospects the basketball talent is shared.
[jump for where they go]
Say uaaaahhh [Upchurch]
Last week when I was talking about the position moves—Jake Ryan to middle linebacker, Roy Manning to cornerbacks coach, etc.—I was mostly positive in the analysis portion, explaining the move as a reaction to having their best defensive player at a defensive role that's quickly becoming as defunct as the spinning fullback.*
In the podcast Brian and Ace expressed some heebies and jeebies over the moves. I can't speak to all of those worries; who knows whether Jake Ryan can read run/pass, or if maybe Desmond Morgan's pass defense was a gaping hole the coaches were covering up in other ways. I can't even give a full answer since Brian didn't do defensive UFRs for Michigan's last three games. But I thought we might use the data we have to see whether the strongside linebacker position in Michigan's defense has been phasing out.
Spread level: rising. The vagaries of year-to-year scheduling and missing UFRs may throw off the data but Michigan's opponents indeed have been throwing out more wide receivers in their base sets as of late.
|Average WRs in Formation by Situation**|
2008 was thrown off by teams going uber-spread: Minnesota, Northwestern, Utah, Illinois, and Miami (NTM) all averaged more than three wide receivers on normal downs, the former three going 4-wide more often than not. That's not too surprising given that defense had a plausible 4-3 run-stopping depth chart, but a huge dropoff if you could mitigate the DL and get past Warren and Trent on the CB depth chart. After that things normalized to a spread-leaning mix of 2- and 3-wide sets until last year.
I wish I had complete numbers. I can tell you that next year Michigan replaces CMU, UConn, Akron, Nebraska, and Iowa with Appalachian State, Utah, Miami (NTM), Maryland, and Rutgers. I can use 2013 stats (from cfbstats) to show you the playcalling breakdown of these offenses:
[If you jump first]
'de-moh-NAY!' s'il vous plait.
The NCAA has published its 2013 data submitted by member institutions for the purposes of Title IX compliance. You can download the spreadsheets from ope.ed.gov.
Politics refresher: Title IX is a gray area topic since it is political but affects college sports which this blog is about. This is a feel thing: it is logical to point out that a male wrestler's experience will be more similar to that of any female basketball player than Derrick Walton's, it is politics to label that "reverse discrimination."
Quinze, seize you: Generally BCS teams spent between 37% (Stanford) and 77% (Oklahoma State) less on the women's sports than the men's. Michigan spent about $7.00 on the fellas for every $3.00 on the gals, a ratio near the top. BCS schools, private schools (who didn't used to have to comply) and Southern schools tended to higher disparities; among the 15 lowest women-to-men expenditure ratios all but three (Minnesota, ND and Pitt) were in the Confederacy. The Dept. of Education doesn't regulate an annual expenditure ratio between men's and women's sports, but they look at them as part of the nebulous compliance system.
|Avg Expenditures by Conference
(in millions) 2012-13
Building Lies. Weirdly, expenses appear more normal than the revenues, which get downright weird. A few examples (for reference, Michigan's men's hockey team reported revenues of $3.2 million, the 4th-most in that sport):
- Stanford's women's basketball team, which was a 1 seed that lost in the Elite 8, reported $16.5 million. The next-highest is Baylor's ($5.9 million), Vandy ($5.6 M), Tennessee ($4.9 M) and UConn ($4.7M)
- Clemson's women's diving reported revenues of $406k. Only two other schools reported any revenue for that.
- TCU said they made $3.4 million from horseback riding and $416k from women's rifling.
- Southern's women's soccer team, which didn't make the tournament field, reported $3.1 million in revenue, which is more than their football team and almost as much as all of their men's sports combined.
- Robert Morris's women's hockey team reported more revenue ($1.1 M) than its men's team ($997k).
- Michigan's men's lacrosse team led the country in revenue: $2.4 million
- Wisconsin's women's ice hockey reported $7.6 million; their men's team reported just under $12 million (double what next-highest, Minnesota, made).
Michigan's the rare school that doesn't pretend its opulent escalator entrance was built for the women's gymnastics team. [MGoBlue.com]
Wisconsin's hockey numbers might be a clue as to how these schools are getting their numbers. The Badgers recently built a practice facility adjacent to the the Kohl Center with donated funds; the women's team plays their game there. Stanford got a massive donation' last year from its version of Ross and built a multi-sport athletic facility with his name on it. Michigan appears to have funneled some of their Big House improvement through lacrosse.
It appears what's happening is when a donation is put toward a building project the schools tend to split that between whichever teams use it. End result: teams that funded major construction projects ended up with the highest ratios of $$ spent on women versus men.
Biggest liars? There's no way to figure out the accounting for these things but it's obvious some programs play with the books more than others. TCU is pretending they built a $3.4 million storage shed for saddles and bridles that the football team just happens to use as an indoor practice facility. They also upgraded the ROTC rifling range, which they attributed to the women's team. They're a private school that
to be a women's college and is still 57% female [ED-S: apologies—you have no idea how many people I've repeated that factoid to over the years] that spent the last decade trying to become a BCS program, which explains the fiscal acrobatics.
[After the jump, comparing expenses to recruiting and performance]