gambling establishment etc
Last month I put together a new way of looking at down and distance and some new metrics. Like the four factors that have become prevalent in basketball, here is my shot at looking six factors for evaluating a football team. There are two key areas that aren’t included. Turnovers, which are critical to explaining past outcomes but poor at predicting future outcomes. The second is special teams. As Brian noted in the previews, special teams are funny because a lot of the value is derived by the presence or absence of big plays. Like turnovers, these are obviously key plays, but they make predicting future performance a challenge because they show up in very inconsistent ways.
The Six Factors
You could call him a factor (Fuller)
|Field Pos||Early Conv||Bonus Yds||Avg 3rd Dist||Adj 3rd Conv||Red Zone|
|Offense||25.4 (19)||49.2% (39)||107 (51)||7.2 (59)||+28% (4)||7.0 (1)|
|Defense||19.2 (55)||44.1% (30)||40 (10)||11.2 (2)||-6% (37)||3.0 (9)|
The first week is going to have some big outliers, with not a lot of competitive games, so the rankings should smooth out over the next month or so.
The defense was really outstanding against Central Michigan. There were almost no big plays, they put the Chips in awful third down situations and limited them both times the offense set them up in good position to enter the red zone.
The offense wasn’t really great in early downs but was exceptional in high leverage situations. Bonus yards (although possessions were limited) and first and second down plays were below NCAA average for the first week but third down and red zone performance was outstanding.
Field Position: A team’s expected points based on where a team started its drives
Early Conversion: The percentage of first downs' that are converted prior to a third down play
Bonus Yards: All yards gained after the first down marker
Average 3rd Down Distance: Average yards to go on third down
Adjusted 3rd Down Conversion: Rate of conversion for a team on third down, adjusted for the standard conversion rate based on yards to go, 0% is average
Red Zone: Points per red zone trip (TD’s counted as 7 regardless of PAT)
All categories except field position are based solely on plays in competitive situations (all first half plays and any second half plays where the drive begins or ends within two scores). Only games against FBS opponents are included, but after last week maybe I need to reconsider that.
Individual Game Scores
It’s just week one so we won’t kick in opponent adjustments for another month. I also included all garbage time plays in the totals since there were so many new players getting touches in the second half.
Devin Gardner: +16.4 (12.2 in the first half)
Fitzgerald Toussaint: +3.1
Derrick Green: +4.4
Shane Morris: +2.2
Deveon Smith: –0.8
*All numbers are PAN, Point Above Normal, a representation of how many points a player adds or subtracts from the team’s final score as compared to an average player/team
If you’re on twitter or look at stats at all, you’ve probably experienced the NCAA stats overhaul that happened this year. In general, it’s awful, but now has auto-play video ads. From the play by play they have stripped out first names of players (so this week we won’t be able to differentiate between Cam and Thomas), no longer list the starters for a game, removed tackler information unless it is a sack, provide no description of a penalty, removed targeted receivers for incomplete passes and removed all yardage detail from punts and kickoffs. It’s pretty awful.
The one slight benefit is they did add directional information to plays. So we can look at how Michigan performed over each side of the line. When running here is how Michigan performed (scrambles and NORFLEEEEET removed):
Left: 5.9 YPC, +2.7, 14 plays
Middle: 3.2 YPC, +5.3, 18 plays
Right: 3.0 YPC, +1.4, 4 plays
Running left was Michigan’s most successful direction but all the benefit was in big play generation. Michigan yielded 50 yards on its two big runs to the left, but was under 3 yards per carry on all other plays to the left.
Ron Zook Dumb Punt of the Week
Dumb punts typically fall into two different types,
1. Punting on short yardage deep in opponent territory for “field position” reasons, even if the values to field position are highly debatable.
2. Punting while trailing in the fourth quarter when future possessions are highly limited
There were 13 punts last week (excluding mercy punts with large leads, not that Hoke would care). 4 of the 13 came from current or future B1G members. Mark Dantonio and Michigan State are the only ones to do it twice. Dantonio wanted to start the year off right so before midway through the first quarter he had twice punted on short yardage from Western Michigan territory. The first time on 4th and 1 from the 41 and the second time on 4th and 3 from the 48. #B1G
27 times teams punted in the fourth quarter within two scores of the lead. Georgia, New Mexico, California and Fresno State all punted from opponent territory with no more than 7 yards to go for a first down. Northern Illinois and Iowa combined for four 4th quarter punts while trailing or tied in their matchup.
And the winner is…Mark Richt and Georgia. The Bulldogs punted twice while trailing in the fourth quarter. The first was on 4th and 7 from the Clemson 40 with about 12 minutes left, trailing by 3. Clemson would take the ball 87 yards for a touchdown to go up by 10. On the next possession, Georgia was facing a tough 4th and 15 on their own 43 but now there were only 6 minutes left and they were down 2 scores, and Clemson had scored 38 points on them. Richt still chose to punt away. Georgia got the ball back down 10 with less than 2 and half minutes to play. They did get a quick score but failed to recover the onside kick.
Notes from around the NCAA
- You may not have heard but Michigan State’s offense was kind of bad last week. With defensive touchdowns and other big turnovers, an average team would have scored 41 points given State’s field position. They were one of the worst offenses in the country in both early conversions (38%) and adjusted third down conversion rate (-15%).
- Alabama won easily over Virginia Tech but the offense did not look strong. The Tide generated only 24 bonus yards, only four teams were worse.
- Three games saw both teams generate over 200 yards past the first down line. Georgia-Clemson, Northwestern-Cal and Vandy-Ole Miss were some of the most exciting games of the week with big plays on both sides. Oklahoma versus Louisiana-Monroe was the worst, with only 75 yards combined from both teams.
- All the Texas A&M talk was around The Manziel “controversy” train but the A&M offense was amazing on early downs. It’s hard to be good at both converting early downs and limiting third down distance. The Aggies did both, tops in the country with 1.7 average yards to go on third down to go with a 59% early conversion rate.
Notre Dame 6 Factors
|Field Pos||Early Conv||Bonus Yds||Avg 3rd Dist||Adj 3rd Conv||Red Zone|
|Offense||13.8 (68)||49.2% (39)||278 (2)||5.4 (26)||+1% (37)||7.0 (1)|
|Defense||10.9 (11)||52.5% (60)||91 (32)||8.1 (19)||+14% (75)||3.5 (18)|
If you watched any of the Irish game on Saturday, it’s not too hard to see where things went right for their offense. 278 bonus yards was second only to Georgia for the week, and Notre Dame did it in only 7 drives. Notre Dame looked like they were playing NCAA Football on the peewee difficulty setting with the way they broke out the big plays.
With so many big plays and with the opponent being an overmatched Temple squad, I don’t know that we know a whole lot else about Notre Dame’s offense from Saturday’s results. On defense the Irish mostly held serve. The Owls were faced with limited field position, expected to score only 11 points based on field position for the game. Notre Dame allowed over 50% early conversions and was awful (75th out of 88 teams) on third down.
With both Michigan and Notre Dame putting up easy wins against overmatched opponents in week one, I’ll have to revert to preseason rankings for a prediction. Going into the season I had Notre Dame at #15 and Michigan ranked 17th, essentially tied. With the game at Michigan I think they will have a slight edge. If they can keep the turnovers and big plays even, I think it’s a clear advantage Michigan.
Michigan 24 Notre Dame 21
Pretty much what I predicted last year
Last year I published my first stock watch based on my preseason team ratings and schedules and compared them to the Vegas preseason projections to identify teams that I thought would be outliers from the consensus opinion on preseason predictions. While I had some mixed results, all three of Michigan’s main rivals were flagged as potential outliers and my numbers differed from most preseason projections.
Here are some quotes I wrote prior to last year’s season:
It pains me to admit it but this Buckeye team could be very dangerous…The Buckeyes are set up for Urban to get credit for an upswing they probably would have had anyway, but it will probably take some significant first year growing pains to keep Ohio from a great theoretical bowl game.
For once in their football life the Domers could actually be underrated heading into this season…If the bounces go Notre Dame’s way this season they have a shot to be a top-10 team. Their biggest hurdle is going to be a schedule that entering the season looks to be far and away the nation’s toughest…there are plenty of other reasons to be optimistic on the Irish roster.
I have no doubts the Spartan defense is going to be good. I just don’t think they are going to be great and I have major questions about the offense. With a new quarterback and nearly 90% of their receiving production gone, there is little history on their side that they can have a productive offense. Breaking in that many new players at skill positions has Sparty projected to be one of the worst offenses in the country this year, Le’Veon Bell or not. Their defense will keep them afloat but unless Michigan St breaks in a new crew on offense at an unprecedented rate, the offense will be this team’s limiting reagent.
I took the most heat for the MSU pick as several Spartans caught wind of this and told me how a first year quarterback and new wide receivers were nothing to be that concerned about and were highly offended about my prediction as one of the worst offenses in the country. 20 points per game later, I stand by my prediction.
After the big three, it wasn’t all sunshine and roses. I did pick Texas to contend for a national championship, Missouri and Tennessee to be mid-level SEC teams and Kansas State to fall back to the middle of the Big 12.
On the other plus side, I pegged LSU, West Virginia and Arkansas all dead on.
Overall the success was mixed but for Michigan’s three main rivals, I would put my preseason prognostication on them up against anyone’s.
This year my predictions for Michigan and its three rivals are dead on with Vegas heading into the season. Notre Dame should settle in to an average of the unlucky 2011 and the lucky 2012 (8.7 predicted versus 8.5 Vegas). Michigan State should see the offense get better and the defense get worse and compete with Michigan and Nebraska for the Legends Division title (8.2 versus 8.5). Ohio State should ride an easy schedule to double digit wins (10.7 versus 11) and Michigan is projected to another year of holding serve before the recruits start flooding into the starting lineup (8.6 versus 8.5). There isn’t any significant room between my predictions on these four teams and the Vegas preseason lines.
So who do I disagree on? Let’s look at the five major conferences.
The only title contender I have any major difference with the oddsmakers is in Wisconsin. My numbers are a big fan of new coach Gary Andersen and I have the Badgers nearly a whole game (9.8 versus 9) ahead of the Vegas number. Nebraska will have the inside track for the top record in the Legends Division thanks to an easy schedule. Michigan is rated as the best team, but consider the Huskers frontrunners thanks to a slate that avoids both Wisconsin and Ohio State.
Northwestern, Purdue and Penn State are the three teams I have the most disagreement on and I think they are all three overrated by at least 2 games.
No major differences for SEC teams. Alabama is obviously the favorite with Georgia and Texas A&M as my two leading contenders. Like last season, I still think South Carolina is a good but not great team.
2013 should be a fulcrum year for Texas and Mack Brown. After an amazing run in the 2000’s, the 2010’s have not been the brightest lines on Brown’s resume. If he has the capacity to turn it around, 2013 should be the season to do it. Texas’s roster is rated the highest of any team since the 2011 Alabama squad (based on recruiting rankings with upperclassmen weighted heavily). Several groups are also high on Texas, I have them projected at 10.6 wins, a full game clear of Vegas and everyone else in the Big 12.
By biggest sell team of the year is TCU. Vegas has them predicted at 8 wins and I don’t see them making it to bowl eligibility. Kansas and Charlie Weis could exceed expectations, I have the Jayhawks with an outside shot at bowl eligibility.
Like the SEC and the Big Ten, I think the Pac-12 has a clear-cut frontrunner. Even with the loss of Chip Kelly, I think Oregon is in line for 11 wins on average. I see USC as the biggest threat, I have them a game ahead of Vegas at 10.4 wins (in 13 games) versus Vegas’s 9.5. Stanford is projected at the same 9.5 but I have them as a distant third in the Pac-12 with only 8.3 projected wins.
Of the seven teams in the new ACC projected to win at least 7 games by Vegas, I am within a half game in my projections for all of them except Virginia Tech. Like TCU from the Big 12, I think Virginia Tech is vastly overrated this year and am only projecting them at 5.2 wins for the season.
As noted above, I am mostly in line with the Vegas line of 8.5 wins for this Michigan season, but barring a Gardner injury, there is definitely more upside to downside. Michigan has 8 games where they should be a solid favorite. At their projected level, odds are that one of them finds a way to get away, but if they can win all 8, that leaves coin flip games against Nebraska, Michigan State, Notre Dame and Ohio State. If Michigan is better than expected at all, those 8 games should move to virtual locks and make a double digit win season a very real season. Without a major change event, there is a very solid downside firewall in place for this season, at least if you think, like me, that Penn State and Northwestern are generally overrated entering the season.
Pull up the NCAA official stats and Michigan’s red zone efficiency looks great, ranking third with scores on 93% of trips. Brendan Gibbons had a lot to do with that as Michigan connected on 14 field goals in 46 trips. But as tends to happen in these situations, the truth is much more complicated the NCAA would have you believe.
After the concept of fumble luck, 3 <> 7 may be the second statistical pillar of MGoBlog. The NCAA’s stat does not believe what we believe. Their rankings are based on a simple equation:
[Times scoring in the Red Zone]
[Trips to the Red Zone]
For the NCAA 3=7. An equally simple measure that has been strangely ignored is Points Per Trip (PPT). By that measure (and taking out meaningless second half trips and games against FCS teams), Michigan drops to 44th at 5.2 PPT in 36 qualifying trips.
Red zone Efficiency is a very easy stat to overreact to. The sample size is small and a couple of fluky plays can swing the ranking either way. When you expand the study beyond the end result of the trip and look at the 110 individual plays that comprised Michigan’s 2012 red zone offense, there is at least a little more sturdy basis for evaluation, although the smaller the sample set, the more likely there is a large piece of luck involved in any outputs, whether positive or negative.
Second Down was not our Down, and Other Findings
To evaluate each play I looked at the touchdown percentage for drives at each possible possible down, distance and yardline from inside the 20. Every play either makes the offense more or less likely to score a touchdown on the drive. A first and goal from the 1 yard line results in a touchdown on the drive 91.4% of the time, therefore a touchdown is worth 8.6%. Second and goal from the 1 results in a touchdown 87.3% of the time so getting stopped on first down is worth –4.1%. Each play is evaluated based on its impact to Michigan’s chances of scoring a touchdown on the drive. Even though the odds of a field goal dropped slightly as you move back within the 20, for this study I just wanted to focus on the effect on potential touchdowns.
Michigan ran 43 first down plays on their qualifying red zone trips last season and put themselves in a situation more likely to result in a touchdown on 47% of them. Even though their plays were slightly more likely to be negative than positive, the positive plays had a higher magnitude, resulting in a net positive of about 52%, or half of a touchdown.
Second down was where the problems started. Michigan ran 39 qualifying second down plays in the red zone and only 14 of them bettered their chances of reaching the end zone. Michigan finished at –221% on second down, a loss of over two touchdowns due to poor second down performance.
Michigan actually held up well on second down rushes, improving their odds on 12 of 23 second down rushes. The problems were centered around second down passing. After the Robinson to Gardner touchdown on the first 2nd down red zone pass of the season, Michigan went 0-9 with 2 sacks on the next 11 pass plays. Michigan quarterbacks locked into Devin Funchess and Jeremy Gallon in these ill-fated situations as the were targeted on 7 of the 9 incompletions. The incredibly surprising play action was not the only issue, only 2 plays were noted as play action in the UFR’s and another 3 were listed as waggle or rollout, but one of those was the initial touchdown.
Where Michigan struggled on second down they excelled on third down. Michigan got a first down or touchdown on 16 of 28 third down plays and reversed their second down loss with a +324% change in their touchdown odds on third and fourth down. Michigan’s binary down success was largely driven via the pass but the situation greatly changed when Devin Gardner came on for Denard Robinson. Denard was 1-5 with a sack on third down while Devin Gardner went 5-5 (all for first downs or touchdowns) with a sack. Where the second down plays were focused on two different players, Gardner third down passes were to 4 different players on the five completions.
Gardner’s third down prowess continued on the ground with a +122% rating on five third down red zone carries. The lack of confidence in the traditional running game around the goal line was evident as only 4 of 13 red zone carries on third and fourth downs were taken by running backs. Toussaint and Vincent Smith both went 1/2 on their attempts.
Devin Gardner Devin Gardner Devin Gardner
So Devin Gardner was pretty good in the red zone. Over all plays he was +432%, or over 4 touchdowns added over the course of the season. In fact, Gardner’s success was probably unsustainably good. I don’t have touchdown’s added for all players, but if you look at pure points added in the red zone, Gardner’s five game red zone average was the second best season ever to Tim Tebow’s 2007 Heisman season. Gardner is really good in the red zone but it is going to be very tough to sustain this level for a full season, only one player ever has.
But what about the other Wolverines?
The only other Michigan player to finish with a positive number was Justice Hayes, by a hair. Hayes’ singular red zone carry against South Carolina netted him a 2% increase. Among the other running backs, Thomas Rawls was –12%, Vincent Smith was –66% (although he was actually the most valuable receiver) and Fitzgerald Toussaint was –117%. All three were making positive plays less than 50% of the time.
Denard finished with a slightly negative red zone contribution for the season, with –39% but on a team low 39% positive ratio. As mimicked by his career, Denard showcased a lot of valuable game changing plays in the red zone, but struggled with consistency. In the end, his 2012 red zone negatives outweighed his positives.
On the receiving side, targets of Vincent Smith, Jeremy Gallon, Drew Dileo and Devin Funchess all finished on the positive side while Roy Roundtree was the sole receiving target to end with a negative rating with pair of 3rd and Goal targets from the 7 falling incomplete.
What It Could Mean for 2013
As noted above, red zone efficiency is fickle stat and can easily swing. With that said, based on small sample size splits, here are some pros and cons heading into the season.
- Keep taking care of the ball, no QB interceptions or RB fumbles in the red zone is a great streak to keep up
- Even with rocket-shoes Gallon and The Funchise, Michigan was at their best when spreading the ball around
- Devin Gardner will probably not be as good in the red zone as he was last year but his success was strong enough that it was more than just sample size
- Stay aggressive and hopefully the third down success can hold, but hopefully more trips can be resolved before then
- Fix second down passing, 1-10 with 2 sacks, was really ugly
- Need contributions from the running backs in the run game. Too many trips were dependent on Gardner/Robinson bailing the offense out.
The two biggest things that seem like more than just fluky outcomes of limited play counts are the success of Devin Gardner in the red zone in both running and passing and the failures passing the ball on 2nd down. Some of this is due to the incredibly surprising play action, 5 of the 12 UFR’d plays where listed as PA, rollout or waggle, but the other six plays weren’t any better.
At this point I have no clue how to keep my expectations for Devin Gardner on earth. There are lots of sample size issues with only five games under his belt but those were five pretty spectacular five games from him and he was at his best in the highest leverage situations. I don’t think he can do it for a whole season and hopefully the defense and running game mean he doesn’t have to, but man, that guy made a lot of plays last year.
While everyone is busy breaking down the scrimmage film with a Jim Garrison-like passion, I thought I would sneak a little preseason preview of some concepts I have been thinking about for how to measure success on a down by down basis. If you want to avoid the nerdy details, skip down for some pretty charts.
Looking at down by down success is a tricky thing and right now there are only limited tools for how to evaluate how an offense is utilizing its most precious resource. The only mainstream tool is third down conversion percentage. This tool’s simplicity is both its weakness and a hidden strength.
Third down conversion rate does not take into consideration how hard your third downs are to convert. Two teams could have identical conversion percentages but if one team has a lot of third and shorts and the other doesn’t the team that doesn’t is accomplishing a much tougher job than the first team. That absence of context is also the hidden strength. Third down percentage isn’t a great predictor of how good your team performs on third down as much as it is an all-encompassing look at how good your team is at getting to manageable third downs and then converting them.
The newer stat that looks at all downs is the Success Rate metric, one I have been on record as not being a huge fan of. Success Rate is a more nuanced look at each down and assigns them a binary pass fail grade depending on whether they meet certain threshold criteria. A binary makes some sense on third down and more sense over the collection of downs, but there is too much opportunity for other value to come and go for the binary to be of major use.
A third way is an expected value (EV). How much value is each team adding or subtracting on given downs. This is a literal value look at ranking teams by what they are accomplishing on a given downs. I have traditionally used this metric but again, it lacks the detail of what is really going on behind the numbers. An EV look tends to lend a lot of value to big play teams and punish consistent gainers. There is evidence to support the rankings coming out that way, but again, I don’t think the numbers tell a good football story in one dimension.
The Early Downs Breakthrough
As I began digging into this I pulled all kinds of numbers looking at each of the three downs separately before it dawned on me, first and second down are really a package deal. They are the offense’s opportunity to either do something big or maximize their chances of a third down conversion, first and second downs and typically on the offense’s terms. You can only create big plays so often and even being good at getting in great third downs all the time still means you are having a lot of plays with a chance for the defense to get off of the field. 3rd and 1’s are converted 72% of the time by the offense, so if you get in three of those situations the odds are nearly two to one that you get stuffed on one of them. Being good at avoiding third downs is a better skill for an offense than getting in manageable ones (although both are obviously preferred).
So to that end, I put together three key metrics for an offense for 1st and 2nd downs:
Early Conversion %: Percent of first downs that are created prior to third down. An average team will convert at about 50% with the best offenses closing in on 60%, like the 2011 Oregon offense.
Bonus Yards: This is a big play metric. For the plays that create a conversion, how many yards beyond the sticks does the average play go. Average teams are around 6.5. Mike Leach’s 2005 Texas Tech team was one of the best ever at 9 yards beyond the stick.
Average 3rd Down Distance: The first two metrics are about the successes, historically, most football coaches are more about minimizing the negative. This metric is for them. For the 50% of the time that the average team faces a third down, how many yards are they typically facing. The average team still has 6.5 yards to go on an average third down. Last year’s Air Force team that Michigan faced was the best of the last 10 years with an average distance faced of 4.0 yards for the season.
Now that early downs have hopefully been understood a little better, it’s time to look at third down and focus on a true measure of the down itself. One option that’s sometimes used is to break down the conversion rates into yardage buckets representing short yardage, medium, etc. This isn’t the worst way to go about it, but still isn’t great. Unless its over a large portion of time, sample size problems are likely and you still potentially have problems, although much smaller now, of where do the actuals trials fall into the buckets. Too many buckets and the splits become hard differentiate, too few and there is little continuity to what you are measuring.
To try and solve these issues, here is my suggested stat:
Adjusted 3rd Down Conversion Percentage: Each third down distance has an average conversion rate that looks like this:
1 yard to go converts at 72%, 10 yards to go at 28%. If an offense converts a third and 1, they get +28% for that play. Fail and it’s –72%. Average up all the third downs for a period and you are left with a single number to reflect how a team has done on third downs, that isn’t weighted by being better at first and second down. The other nice thing is that it is naturally anchored to zero. An average team is at +0%. 2011 Wisconsin with Russell Wilson and Montee Ball was the best Big Ten third down team at +16%. 2011 Alabama was the best third down defense at –15%.
Taking all the above analysis, I pulled the results for last season and put them together in a fancy new Tableau table (click to control the view [ed-S: we know; we're working on the links]).
Circle size represents average third down distance
So, Michigan was pretty good on a down by down basis, last year. Only Clemson and A&M where better at third downs when accounting for yards to go. Michigan was also one of the best teams at avoiding third downs altogether, converting on first or second down about 54% of the time.
The other big take away from this is that there are a lot of Big Ten teams at the left hand side of the chart. It’s a bit hard to tell from this view, but Big Ten teams are some of the best at managing third down distance but some of the worst at everything else. Fully half of the teams in the conference are in the lower left quadrant of teams that are bad at both. An offense whose goal is to get into manageable 3rd downs is an offense that is set up to fail.
Michigan lands pretty average across the Big Five conference landscape in both early downs and third downs on the defensive side. The strength of Michigan State’s defense really shows up here, as they only allowed teams to convert before 3rd down about 2 out of 5 times.
I am trying to put together a package of weekly reports and rankings that I can publish online. If anyone has any thoughts as to what you want to see that aren’t otherwise available, I am open for suggestions.
I think these charts do a good job of reflecting what’s happening on a down by down basis. What they don’t show are the impact of big plays and high leverage plays like turnovers and red zone plays.
1 Future 1st round round draft pick
+2 Freshman starters
This year’s Michigan offensive line is a somewhat unusual combination. The entire interior of the line has graduated, none of whom where drafted. Left tackle Taylor Lewan passed up a chance to be a top 10 draft pick for one more year of Michigan football. The line’s second best player is also back in right tackle Michael Schofield.
What Michigan loses in experience it replaces with recruiting profile. Based on early camp reports, Kyle Kalis appears to have locked down his starting spot and comes in with the highest ever recruiting profile for a Michigan offensive lineman. Projected to join him are fellow redshirt freshman Ben Braden at guard and either Jack Miller or Graham Glasgow at center.
Since the end of the RichRod era produced a two year window where only two scholarship linemen remain, I wanted to see if there were any other programs with the dichotomy of two or three older starters, one of which would be a first round draft choice the following year and two starters that have barely been on campus for a full year. There were three teams over the last four seasons that fit the mold:
The Taylor Lewan: LT James Carpenter, 2011 1st round pick
The Michael Schofield: C William Vlachos, 2.5 year starter
The Kalis/Bradens: RT DJ Fluker, 2013 1st round pick was a highly touted redshirt freshman
LG Chance Warmack, 2013 1st round pick, true sophomore
The Glasgow/Miller: RG Barrett Jones, 2013 4th round pick was a 2nd year starter and redshirt sophomore
Biggest differences: In comparison to Michigan’s new three, Alabama had Barrett Jones who was a returning starter and had a top 200 recruiting profile, significantly higher than whoever wins the center job for Michigan
Yards/Carry: 5.6, 11th among BCS schools
Sack Rate: 9.3%, 113th in FBS
The 2010 Alabama team was just coming off of a National Championship and a Heisman trophy for Mark Ingram in the prior year. The team was Alabama’s only team of the last four years to not win the national championship. They were loaded at running back with the defending Heisman trophy winner Mark Ingram backed up by future first rounder Trent Richardson and future second rounder Eddie Lacy. It’s hard to have a much better projected future than this team did, even if 2010 was the “bad” year. The yards/carry was outstanding but the sack rate jumped out as a surprisingly awful stat.
*Yards/Carry is without sacks, only competitive plays (1st half or within 14 in the second half) and against FBS competition
Sack rate is [sacks allowed ]/[sacks + pass attempts] under the same game conditions as yards/carry
The Taylor Lewan: RG David DeCastro, 2012 1st round pick
The Michael Schofield: LT Jonathan Martin, 2012 2nd round pick, third year starter
The Kalis/Bradens: LG David Yankey, redshirt freshman
RT Cameron Fleming, redshirt freshmen
The Glasgow/Miller: C Sam Schwartzstein, redshirt junior and 1st year starter
Biggest differences: The ages and experience of Stanford group match up almost exactly to Michigan’s this year. They lacked an elite recruit like Kalis among the new starters but did have Andrew Luck running the show behind them.
Yards/Carry: 5.8, 4th among BCS schools
Sack Rate: 3.1%, 7th among BCS schools
The 2011 Cardinal team went 11-1 in the regular season and finished the year #4 in the AP Poll after a loss in a classic bowl showdown with Oklahoma State in David Shaw’s first season as coach after taking over for Jim Harbaugh. If any program personifies what Michigan is aiming for it is Stanford. Tough, power rushing game with a deadly quarterback passing to tight ends, a season like this one might still be a year away for Michigan but the style is exactly where Michigan wants to be this season.
The Taylor Lewan: LG Kyle Long, 2013 1st round pick
The Michael Schofield: C Hroniss Grasu
The Kalis/Bradens: LT Tyler Johnstone
RT Jake Fisher, former Michigan commit
The Glasgow/Miller: G Ryan Clanton
Biggest differences: Last season’s Oregon offensive line was a bit younger than even Michigan’s this year and Kyle Long took a very different path through football than Taylor Lewan. The Oregon newcomers last season had a significantly lower recruiting profile than the three new Michigan starters. In terms of system Michigan and Oregon will obviously be very different in terms of what they are trying to do when they have the ball in both plays and tempo.
Yards/Carry: 6.9, 1st in FBS
Sack Rate: 4.2%, 37th in BCS
This is the weakest among the three connections if only because the offensive systems between Michigan and Oregon are so different. You can’t argue with the results, though. At nearly 7 yards per rush Oregon spent last season running past opponents yet again and finished with another top 5 ranking.
So I think most Michigan fans would take any of those three offensive seasons. The head to head examples are all quite positive but I think the biggest concern from those comparisons is that Michigan’s 2012 yards/carry was much worse than any of the comparison teams’ prior years were. For all three of the similar teams, the prior season had been outstanding and the examined season was very good but a small step backward. Michigan is coming from the opposite direction.
Stanford and Alabama are certainly two programs who look a lot like Hoke’s vision for Michigan both in terms of style and outcomes. History says that in general this roster is still another year away, but based on three teams with offensive lines similar to Michigan, the true unveiling of the Borges offense could come this year.
For the True Freshman evaluation I looked at how the quarterback himself fared. To look at how a team’s offense fared I pulled team offensive performance and grouped them by quarterback starts going into the season and quarterback age. For example, last year all quarterbacks from the class of 2011 were grouped together if they redshirted in 2011 or saw spot playing time. If they started as true freshmen they were considered second year starters.
As noted in the prior article, starting true freshmen quarterbacks is not a formula for winning games. Teams with them at the helm operated 3.9 point per game below an average team. For reference, last year’s Michigan State offense was about 5 points below average.
With even one year of seasoning on the bench, that number moves even higher. The NCAA didn’t start publishing official starters by game until 2009 that I can find so this data only represents the last two seasons. There are some small sample sizes in play here but at the same time, the trends are logical and pass a smell test.
Players in their second year have performed better after going through growing pains on the field in year 1, but players from the prior years class tend to have better debuts as second year players as opposed to true freshmen.
For players in their third year, there isn’t much progression for the guys who have been starting from day 1, but the second year starters show a big leap from 2 points below average to over a point above. At this point the value from the extra starting experience has disappeared and the players with a combination of on and off the field time have passed the most experienced group. Their classmates who have sat for two years fare about as well as the second year starters.
By the time players are in their fourth and fifth year in the program, everyone with some starting experience performers at a similar level near 2 points above average. What is interesting is that the one group who is a strong outlier are the guys who have hands full of splinters from all the clipboard handling. Guys who have sat for their first three years on campus typically aren’t worth the wait. Their debuts are typically on par with a player much younger. As with all of these categories there are exceptions all over the place but a guy waiting his turn this long is more often a guy who couldn’t win the job than a guy who was just waiting behind a better option. There are a lot more Joe Bausermans than Tyler Wilsons.
If you flip the chart the more obvious conclusions show up in that the older a quarterback is the better he does. This shows up as consistent across all seasons of starting with the glaring exception of third year players becoming starters for the first time. With 2 or 3 years of eligibility left this looks like the quarterback sweet spot. You have probably given the quarterback a redshirt year to preserve 3 years of starting time. Two years without starting provides the opportunity to learn without getting too stagnant. This window also opens the door up for highly touted recruits to see the field with plenty of time shine without taking too many rough outings to get there.
It should be noted that these are all averages and there are many variances and exceptions to each situation. Just because you are choosing between a true freshmen and a third year player for your starting quarterback doesn’t mean that the third year guy is the best choice. This is just meant to be a high level look at the general progression of quarterback. With that said, getting Shane Morris two years (unless DG blows up and goes pro) or prep could be a big benefit to keeping the offense moving forward through a changing of the guard at quarterback.