Peppers at 10, which seems low.
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Amazing. Words fail to describe the weekend I had in glorious Ann Arbor. Met Marlin, Perry, Braylon, even David Pollack. And now I'm stuck back in Pennsylvania like a desperate heroin junkie with a condition that can best be described as an addiction for the Michigan Difference.
Love that team. Love that place. And I love Meeshigan Football.
Finally, thanks to the MGoTeam for a really fun and unique experience on Friday.
THE BLOCKHAMS™ runs (typically) every week here at MGoBlog and on its official home page. Also, don't forget to check out the Friday Fun, my weekly single panel comic based on trending Michigan events, available on Twitter and the home page every Friday.
I’ve been wondering lately about Michigan’s modern coaches (i.e., from Bo on), and how their winning percentages stack up when we consider the quality of the opponents they’ve played. Just off the top of my head, it seems to me that:
- Lloyd Carr was a much better coach against ranked opponents than we give him credit for, but lost more games than he should have to unranked teams.
- Brady Hoke thusfar has done well in winning the games he should win (i.e., vs. unranked opponents), or at least has done better than Lloyd Carr did.
- Gary Moeller and Lloyd Carr went through an absolute gauntlet of a schedule in the 1990s.
But I wanted to see if those notions are actually supported by the stats. So I started looking at Michigan’s coaching from 1969 to 2012 against ranked teams. I should start out by explaining that “ranked” here means the AP Top 20, as the AP did not rank teams 21-25 until 1989. I’ve therefore disregarded all 21-25 rankings of opponents.
Here are our heroes’ (and anti-hero's) overall M records:
*All Hoke stats are through 2012 only, as we don't have final AP rankings for 2013 yet.
Here’s how U-M’s coaches have stacked up against teams ranked at game time:
|vs. AP 1-10||vs. AP 11-20||vs. Unranked|
|Bo||16-19-1 (.458)||21-12 (.636)||159-16-4 (.899)|
|Mo||7-5-1 (.577)||5-1-1 (.786)||32-7-1 (.813)|
|Lloyd||19-9 (.679)||19-11 (.633)||84-20 (.808)|
|RR||1-5 (.167)||1-4 (.200)||13-13 (.500)|
|Brady||0-2 (.000)||1-2 (.333)||18-3 (.857)|
Some obvious points jump out:
- RichRod and Hoke, and even Moeller to some extent, have small sample sizes. Keep this in the back of your mind for all that follows.
- Lloyd had a VERY impressive record against the AP Top 10. In fact, he started out on a huge roll. From 1995-2002, Lloyd was 11-1 against the Top 10 at game time.
- Lloyd lost a substantial number of games against unranked teams. Brady’s done pretty well against the unranked. Bo really killed the teams he should have killed.
I know, I know, pre-season bias in rankings, especially early. But let’s not completely discount game-time rankings. Though some of them, particularly early in the season, are just plain wrong, some might actually be good indications of a team’s quality as of the time you played. For example: some of Glen Mason’s Minnesota teams were pretty good as of Michigan week, but then plummeted through the rest of their seasons, perhaps from psychological issues, after losing their red-letter games for the Jug. Were those teams better when Michigan played them in week 5 or 6 than those teams’ final unranked status would indicate? Very probably.
But of course, rankings at game time, particularly early in the season, don’t tell the full story about the quality of the team you’ve played. The season’s final rankings are probably most illustrative (except for Minnesota-like situations as described above):
|vs. AP Final 1-10||vs. AP Final 11-20||vs. Final Unranked|
|Bo||6-25-1 (.203)||16-8 (.667)||172-15-4 (.911)|
|Mo||2-7-1 (.250)||7-2 (.777)||35-4-2 (.878)|
|Lloyd||10-14 (.417)||14-6 (.700)||98-20 (.831)|
|RR||0-8 (.000)||0-3 (.000)||15-11 (.577)|
|Brady||0-3 (.000)||1-1 (.500)||18-3 (.857)|
Final rankings may give you a better overall picture by removing most of the pre-season bias, but with final rankings a big caveat also applies: When you beat a team, its final ranking drops. When you lose to a team, its final ranking rises. Beating a good team makes it look worse to the poll voters. So in general, the coaches should have worse winning percentages against teams in the final rankings than they'd have against teams ranked at game time.
- Bo’s REALLY kicking ass against the unranked dregs (Mo and Hoke too), but not doing so hot against teams having great seasons. It makes sense that a coach’s record against the final Top 10 should not be great, but Bo’s was pretty dismal. All of the bowl losses certainly didn’t help him.
- Lloyd’s 10-14 against the Final Top 10 is still pretty darned impressive, and his combined 24-20 against the Final Top 20 is fairly impressive as well. But again, he’s lagging behind in beating teams having unranked seasons.
- RR of course was absolutely dismal against teams finishing in the Top 20. Wisconsin’s 2008 team was not able to crack the final Top 20 to put a single mark on the board for Coach Rod.
So it looks as if my first two initial thoughts were generally right. Thusfar Lloyd was a pretty good big-game coach, taking his whole career into account (I’ll save comparisons of early career vs. late career for another piece). And Brady’s not losing to a lot of teams that he has no business losing to.
But what about the schedule strength? On average Bo faced fewer ranked teams in the days before 85-scholarship parity (in 1970 he didn’t face a single team ranked at game time or in the final rankings) and before the resumption of the Notre Dame series and the scheduling of Miami and Florida State. Also, even in some of his best seasons the Big Ten didn’t let him go to a bowl game. How many of their games on average did our coaches play against ranked teams?
Based on the game-time rankings:
|% of Games Played vs. AP 1-10||% of Games Played vs. AP 11-20||% of Games Played vs. Unranked|
Based on final rankings:
|% of Games Played vs. AP Final 1-10||% of Games Played vs. AP Final 11-20||% of Games Played vs. Final Unranked|
- It looks like Mo’s schedules were indeed murder, whether you look at the game-time rankings or the final rankings.
- Bo’s and Lloyd’s schedules got significantly easier when you look at the final rankings.
- RichRod’s schedules became brutal when you look at the number of teams he faced that finished in the Top 10. But again, if you lose games, the teams you play look better in the final standings. And of course it’s a small sample size; if RR manages to beat Utah in 2008, Penn State in 2009, Iowa in 2009, or Wisconsin in 2010, those numbers look different.
- Hoke hasn’t played a lot of high quality teams. Thanks, down Big Ten and watered-down non-con scheduling.
Given the disparity in schedule strength, let’s look at the coaches’ winning percentages as if Lloyd’s 13-year schedule is the measuring stick for schedule strength. I think that’s fair, as 13 years is a pretty good sample size, Lloyd had both some really good and some bad seasons, and Lloyd’s tenure was the time in which Michigan’s schedule entered into our current era of weaker non-conference scheduling and greater parity as the effect of the 85-scholarship limit has fully set in.
For example, we’re going to take Bo’s .458 against the Top 10 at game time and assume that he’d played as many games against the Top 10, on a percentage basis, as Lloyd did, and so on. How do our coaches’ career winning percentages stack up then?
Based on the game-time rankings:
|Actual Win %||Win % Adjusted to Lloyd's Strength of Schedule||Change|
Based on the final rankings:
|Actual Win %||Win % Adjusted to Lloyd's Strength of Schedule||Change|
- When adjusting for schedule strength, Lloyd suddenly looks pretty good. He’s only around 20 points lower than Bo’s storied/heralded/legendary career. A swing of just four games in Lloyd’s career would’ve put him above Bo. If Lloyd goes 126-36 instead of 122-40, Lloyd becomes the Michigan coaching king when percentages are adjusted for schedule strength. And that’s not too big a stretch at all. Think about it: if Michigan had gotten few breaks in the 2000 season (i.e., Hayden Epstein doesn’t miss an extra point and a 24-yard field goal against UCLA; Michigan scores more than a field goal in the second half at Purdue; the A-Train holds on to the ball at Northwestern), and if Michigan hadn't given up just one of the several fourth-quarter blown leads in 2005, Lloyd would’ve had a better career winning percentage than Bo, equalized for schedule strength. But more on this later.
- Again, Mo’s schedules were murder. His percentage rises when compared to Lloyd’s schedule strength.
- RichRod’s also up in the final rankings, again because of the many opponents he played that wound up in the final Top 10.
- Hoke doesn’t look so hot. But rebuilding and fusion cuisine and all that.
In the comparison of Lloyd to Bo above, we’ve adjusted Bo’s 1-10 percentage and 11-20 percentage to Lloyd’s frequency of playing in those games. But playing the national No. 1 is usually a much tougher game than playing the national No. 10, or even No. 3. I haven’t taken the time to adjust the winning percentages by frequency of playing every single spot in the rankings, but I have collected some info on how those guys did against the Top 2 and against the Top 5 at game time:
|Record vs. AP 1-2||Record vs. AP 1-5|
|Bo||3-6-1 (.350)||8-12-1 (.405)|
|Mo||0-3 (.000)||2-4-1 (.357)|
|Lloyd||3-3 (.500)||8-3 (.727)|
|Brady||0-1 (.000)||0-2 (.000)|
Those are some great numbers from Lloyd, but all of those games are 2003 or earlier, when he started 11-1 against the Top 10, aside from games against No. 2 Notre Dame and No. 1 Ohio State in 2006. For what it’s worth, U-M hasn’t beaten an AP No. 1 since Miami in 1984.
So how often did the coaches play in really big games (using game-time rankings)?
|% of Games Played vs. AP 1-2||% of Games Played vs. AP 1-5|
So Bo played really big games just slightly more often than Lloyd did, and Mo’s murderous schedules are apparent here as well. I’m not sure this difference between Bo and Lloyd is significant. I’m still comfortable saying that Lloyd is only a touch behind Bo in terms of impressiveness of career. Sacrilege? Perhaps. But in terms of wins, losses, and quality of opponents, I think that’s a fair statement. Now, that's not saying anything about what Lloyd could have achieved, or how maddening it was to watch some of his games. Of course, Bo sustained that level of success eight seasons longer than Lloyd did, and there's something to be said for that.
What do we get from all of this? I think the stats support the wisdom of the ideas set out above: Lloyd Carr was pretty darned good against ranked teams, but not as hot as he should’ve been otherwise; blame the 85-scholarship parity era for that. Brady Hoke has generally won the games he should win. And the 1990s schedules, particularly Gary Moeller’s, were potentially the most brutal stretch Michigan has ever faced.
And don't worry, I'll say it for myself: Cool story, bro.
[Edited to correct Brady Hoke's 2-year record to 19-7 instead of 18-7. All stats accordingly corrected.]
Last week UMgradMSUdad went over B1G football against the spread for the first week. He had commented "But if anybody else is interested in doing it, I say go for it." So I did. If you'd like anything else tracked, let me know and I will consider it. Unless it's tracking the top-25, I don't believe I'll put time/effort into that. Any top 25 team that's relevant to Michigan will be tracked, given they're in our conference.
I Bet You $20 I Can Get You Gambling By the End of the Day
|Week 1||Week 2|
|Michigan||-34.5||-31.5||59-9 (CMU)||+18.5||-4||-5||41-30 (ND)||+6|
|Ohio||-35||-34||40-20 (Buff)||-14||-28.5||-28||42-7 (SDSU)||+7|
|Michigan St||-27||-28||26-13 (WMU)||-15||-24.5||-21.5||21-6 (USF)||-6.5|
|Indiana||-24||-25||73-35 (Ind St)||+13||-14||-12.5||35-41 (Navy)||-18.5|
|Illinois||-24||-17||42-34 (So Ill)||-9||+7.5||+8||45-17 (Cinci)||+36|
|Northwestern||-3||-6.5||44-30 (@Cal)||+7.5||-16||-17||48-27 (Syr)||+4|
|Penn State||-7||-8||23-17 (Syr)||-2||-24.5||-28||45-7 (EMU)||+10|
|Nebraska||-27||-31||37-34 (Wyo)||-28||-31||-28||56-13 (S Miss)||+15|
|Iowa||-3||-3||27-30 (N Ill)||-6||-24||-26||28-14 (Misso St)||-12|
|Wisconsin||-44||-44||45-0 (UMass)||+1||-45||-45||48-0 (Tenn Tech)||+3|
|Purdue||+7.5||+10.5||7-42 (Cinci)||-24.5||-17||-17||20-14 (Ind St)||-11|
|Minnesota||-14.5||-13.5||51-23 (UNLV)||+14.5||-15||-16||44-21 (N Mex St)||+7|
- The B1G went 8-4 ATS last week, improving on their 5-7 record from the first week.
- As you can see, Michigan has done very well ATS in their first 2 weeks, the best in B1G.
- Northwestern, Wisconsin, and Minessota are the only other B1G teams that are 2-0 ATS.
What about next week? Can't make money on past spreads...
Show Me the Money
|Michigan St||-28||-24/-26||NL||Young St|
- Hoke is 3-1 ATS when playing MAC teams at Michigan, with his only loss coming from beating EMU by 28 with the spread of -28.5.
- Michigan has covered 3 straight games at home.
- Hoke is 11-6 ATS at home.
- Gardner is 5-2 ATS & 6-1 O/U as the starting QB with the last 4 home games going over the total.
- Hoke has been favored at home by over 30 points twice, and covered in both contests.
- Terry Bowden & the Zips were 1-11 last year, but went 6-6 ATS and are 0-2 ATS this year.
- Before last week the Zips had went under the total in 8 straight contests. Last week they went over the total by 13.5 points; looks like they had subs, and it was crazy.
With a total of 57 and a spread of 37, the team totals project to be Michigan (47) and Akron (10). The limits on team totals aren't as lucrative, but I don't see Akron scoring 10 points. Or at least I don't want to see that.
If interested, here are past ATS records for the B1G:
What's your best bet?
This week’s factor favorite (Upchurch)
1. The Six Factors
|Field Pos||Early Conv||Bonus Yds||Avg 3rd Dist||Adj 3rd Conv||Red Zone|
|Offense||15.3 (42)||55% (40)||211 (36)||7.0 (81)||+14% (13)||7.0 (1)|
|Defense||23.4 (80)||41% (30)||145 (35)||5.1 (34)||+8% (75)||3.4 (26)|
*Game score first, season long national rank in ()
Notre Dame had a field position score advantage, mostly thanks to The Worst Pass Ever. Michigan dominated early conversions while more manageable third downs. Brian Kelly teams have traditionally been geared this way, strongly managing third down distance at the expense of facing more of them. Gallon’s big catch a run providing most of the gap in bonus yards as Mattison’s defensive plan limited yards beyond the sticks.
While Michigan continued to be a very good 3rd down team on offense, Notre Dame did well on third down when they had the ball, even beyond the more manageable distances that they faced. The story of the game though was the red zone. Notre Dame made 5 trips into the red zone and came away with 17 points, Michigan made four trips and scored 28. Michigan won by 11.
Two games into the season the national rankings don’t mean much with cupcakes galore and outliers, everywhere. Still, 18 teams have made at least seven trips to the red zone in competitive situations this season, only Michigan and Oklahoma State have scored on every trip. It’s not going to hold up all season, but the evidence is mounting that Gardner is a red zone genius.
It is also amazing that other than Phoenix, Salt Lake City, Denver and west Texas there are essentially no FBS football recruits between the Pacific coast and I-35. It will be interesting to see what happens with this as geographical boundaries continue to overlap with the ongoing conference expansion.
In the comments I pointed out that this maps on to overall demography. The Mathlete's map of recuits
is not significantly different from the US Census' map of population density by county:
But demography can't explain everything. Some states produce more football talent per capita than others.
Football Study Hall published a blog post today about Where FBS recruits come from, in which they tracked FBS recruits from 2008 to 2013 in raw numbers and per capita (click to their article to see the raw data). Mapped using Google Fusion, the result is the following (click to embiggen):
Map showing FBS recruits per capita by state
This map illustrates the recruiting advantage of the SEC and the South generally: Lousiana, Mississippi, Alabama, Georgia and Florida are all well above average in terms of the number of FBS recruits they produce per capita. Texas and Oklahoma are also above average -- and, unfortunately for UT, so is Utah.
The recruiting advantage of Michigan and Ohio
State is also thrown into relief. Although Michigan is below average in the number of football recruits it produces (0.61 recruits per 100k, vs. the national average of 0.75), the state of Ohio is well above average (1.31 recruits per 100k, 9th in the nation), and is of course a consistent and significant source of recruits for UM and OSU.
Nope, Not Déjà Vu:I just sat there in the Big House stunned. I looked over at my two sons (both are in their 30's) and they had that same terrible, horrible, awful look on their faces. THE interception had just happened and I knew we all were thinking exactly the same thing – "Not this again". The comfortable lead had evaporated in less than a few seconds. Would a turnover lead to our doom?
Nope, not this time. Whew!
Synopsis for Turnovers: Here is the overall summary for all games by player (data in yellow was affected by this week's game). Michigan's TOM for the game was +1 and for the year it is now zero – ranked #48. Turnovers were not a primary factor in determining which team won the game.
Norfleet fumbled another punt but no other player has fumbled at all which is a great sign. According to the folks at NFL stats total fumbles (not fumbles lost) shows the best correlation to offense performance. But, Gardner threw THE interception, and now has 3 for the year. M is ranked dead last (#125) for interceptions thrown percentage at 7.4% which is the second stat that correlates to offensive performance.
Countess intercepted two passes and M is now ranked #36 with opponent interception thrown percentage of 3.6%. There were no fumbles by ND but M is still ranked #15 for forced fumbles.
National Rankings: All rankings include games between two FBS teams ONLY and are from TeamRankings except for forced fumbles which is from CFBStats. The four columns with *** show the best correlation to offense and defense (per Advanced NFL stats).