gambling establishment etc
For the second straight week, Rawls racked up over 100 yards for CMU, this time against Big Ten cellar dweller Purdue. He had 31 carries for 155 yards and 2 TDs.
Some Purdue fans remember this guy from his Michigan days, others were wondering where the F*** CMU got this guy. Via Hammer and Rails Game Thread:
This Rawls kid is Big Ten quality and he's killing us.
He's a grad transfer from Michigan
Sooo, you’re right.
Yeah, I know. He's one of the lucky few who gets to beat up on us for two different teams.
Put everyone on Rawls
And you might stop them. Then again…
#5 is running the other way when he sees Rawls coming
Rawls up the middle, first down - calling it
"This Rawls kid"; epic.
Also a game recap from WXYZ Detroit mentions Rawls.
Happy to see the kid do well. Go Blue!!
Central Michigan held on for a 20-16 victory over the vaunted Chattanooga Mocs last night, but there was a bright spot for CMU...former UM running back Thomas Rawls rushed for 123 yards and one TD on 25 carries. He also caught 2 passes for 7 yards.
I'm really happy for the guy, glad he found a landing spot and hopefully he finishes his career strongly for the Chips.
Box score HERE
Not a huge surprise as Richard Ash and Josh Furman were both redshirt juniors. Hopefully they both get their degrees this spring and find a place to play next year like Michael Cox.
Michigan spokesman says Josh Furman, Richard Ash and Thomas Rawls have all been granted transfer releases.
In the aftermath of the CMU game, I’ve seen a few comments about running backs that go something like this: “If you took out X’s long run, his YPC would have only been Y, so he really wasn't that effective,” or variations thereof. This got me thinking a little about the limitations of using YPC to summarize running back performance, so I've put together a couple ways of looking at running back performance against Central.
First off, sample size concerns are rampant. Statisticians frown on many, many things, but they take particular umbrage when you do anything with a really small sample (read: less than 30). But, like our beloved coaches, we live in the real world where we have to make decisions based on incomplete information; so we continue on despite the limitations of the dataset.
Strength of competition is also suspect. We don't know for sure how good CMU will be this year, but we do know they were outscored by fifty points in the only game they've played this year. They may not be great this year.
Yards per carry is calculated by summing all rushing yards for a player and dividing by number of carries, making it an average (or sample mean). A sample mean is a very useful way of summarizing data with one nagging flaw: it is particularly vulnerable to outliers. The median, on the other hand, as the most central value, can be interpreted as a more typical expectation for a dataset. One extremely high or low value will have virtually no impact on the value of the median. Here's an example: Derrick Green's YPC for the CMU game was 6.1, 2 whole yards higher than Toussaint's 4.1. But Green's median carry of 3 is an entire yard shorter than Toussaint's 4. The YPC might lead you to conclude Derrick Green was a better bet for getting yards than Toussaint, but the median says at least 50% of Toussaint's carries went for 4 or more yards in comparison with Green's 3 or more yards. Since If you needed four yards for a first down, you may want to give it to Toussaint. That's potentially valuable information not contained in the YPC. Then there's the pesky fact that TD runs have a maximum length. If we're two yards out from the end zone, that's the maximum the player can get for that carry. This artificially lowers the YPC of a player who gets the ball over the line; in particular Toussaint's YPC would probably have been higher.
The table below contains a few measures of central tendency for the players who had at least 3 carries (three is still too small, but a line had to be drawn somewhere and Rawls' touchdown seemed to merit his inclusion in this list). Rawls gets no standard deviation because three is a small number.
QB Devin Gardner wins the YPC sweepstakes with a blistering 7.4 YPC bolstered by a median carry of 6 yards. I would advocate getting this man some more carries, but that's a) already happening and b) potentially troublesome for our passing game. Regardless, Gardner does a good job here no matter what metric you use: no negative yardage, a great longest run and two touchdowns on only 7 carries. At least for this game, our shiny "more passing-oriented" quarterback was our most effective running back, which speaks a bit to the value of athleticism at that position.
Among the running backs, Toussaint and Green duke it out for maximal effectiveness depending on which measure you use. Green wins on YPC, longest run, and least negative minimum run. Toussaint had a higher median, most touchdowns, and most carries. Rawls has the highest median of the RB's, but since he only had three carries, sample size tells us to pay no heed.
____ Yards and a Cloud of Dust
Hearkening back to the days of Three Yards and a Cloud of Dust (TYaaCoD), I wanted to know who was more reliable if you need three yards every time you rush. The table below contains the percent of carries the player achieved at least three yards, embodying the spirit of slightly-in-jest Schembechlerian Michigan Football.
Personally, though, I find three yards slightly lacking. If you run three yards every rushing play and you rush every play, you end up facing 4th and 1 every series. Our Fearless Leader would still go for it on fourth down every time (Heil Hoke!), but it's not an optimal situation to find yourself in. What you really want is someone who can pick up 3.5 yards or so every play, so you get a new set of downs after every three. The play-by-play is unhelpful in this regard, however, only listing integer values for yards. So I also calculated the Four Yards and a Cloud of Dust (FYaaCoD) metric, which is how the table below is sorted. If you get four yards every carry, you can go on rushing forever.
I did make a slight modification to the success rates of both metrics: I counted a touchdown as a success regardless of how many yards the play was because there is no further to go.
|Row Labels||Total Yds||Carries||TYaaCoD||FYaaCoD|
For TYaaCoD, you would want the following players rushing in order: 1. Green 2. Gardner 3. Rawls 4. Toussaint 5. Smith 6. Johnson. All players are between 50% and 75% successful at getting 3 yards against CMU, which is heartening. Moving to FYaaCoD, you would want 1. Gardner. 2. Rawls 3. Toussaint 4. Green, 5. Johnson 6. Smith.
There's some shuffling when you move to FYaaCoD: Derrick Green drops from first to fourth, and Smith falls to sixth at a slightly disappointing 29% success rate. Rawls still has only three carries, but two of them pass the FYaaCoD test, so he has a terrific success rate of 67%. Almost as good as Devin Gardner, who had over twice as many carries. Devin's ability to scramble is probably for real. Toussaint's actual strength as a running back comes through a bit more on the FYaaCoD metric. On his 14 carries, he hit 4+ yards 57% of the time, and he often surpassed four. That increases the chance of success for future plays, as the distance to the first down marker is smaller.
I thought about running the same analysis with passing yards, but it didn't feel right since yards per catch vary widely based on the play. Your wideout running the deep route will end up with more yards per target than the slot ninja you toss the bubble screens to. That is more schematic than based on individual skill. It is true that running plays are also not all created equal. But every running play starts behind the line of scrimmage and heads as far as possible into enemy space, making comparison a reasonable exercise.
Any statistical summary is just that: a summary. We lose information when we look at average, median, min, max, total yds, TYaaCoD, FYaaCoD, etc. that is available to us in the actual dataset. Our lizard brains just can't process significant amounts of data in numerical form in any reasonably quick fashion. But there is one thing we are great at: reading charts. So I've assembled the information from each rushing effort for everyone with 3+ rushes in order from least yards gained to most. I've colored the touchdowns Highlighter Yellow™ so you can include/exclude them from your mental calculations as needed.
For recent time's sake, Drake Johnson. Fare thee well, 2013 Drake. We hardly knew ye.
A. We were completely misguided to push for Devin-Gardner-to-wide-receiver last year when his natural position is clearly running back. The fact that QB's get an extra blocker has no bearing on this.
B. At this exact moment in time, the staff's decision to go 1. Toussaint 2. Green 3. The Field. is pretty justified. We saw flashes of brilliance from both of them—maybe even more from Green—but Toussaint overall had a better day. If Green sheds a few pounds and picks up just a hair more speed in the process, though—and I think we all expect that to happen— he could become the clear #1 even by mid-October. De'Veon Smith is not yet ready for world-beating, but he did display that vaunted balance. Hold off on judgment on him at this point.
C. Charts are indeed fun to look at.
D. Norfleet had one rushing effort for 38 yds, which I didn't include in this analysis because dividing by zero is difficult and because his YPC would make Brian cry.
How long should we wait for this guy?
There is constant chatter on this board and in the media about how freshmen RBs should be able to contribute right away. The basic tenet of this belief is that if a RB is athletic and is any good, he'll be able to produce right away. Sure, he might not have the nuances of pass protection and route running down, but he should at least be able to pick-up some yards on running downs as a true freshman. Guys like T.J. Yeldon make this easy to believe.
So, I decided to find out how true this is. If you suck as a freshman RB, are you likely to be any good at any point in your career? If Derrick Green doesn't contribute significantly this season, should we ? Going even further, is Rawls a lost cause at this point? Hayes?
Having a little less time than I'd like to do a thorough examination of the data, I used a somewhat limited sample: the top 40 RBs in terms of yards/game from 2012. I broke seasons into three categories: Primary starter (PS), significant back-up (SB), and insignificant season (IS).
These categories are actually surprisingly simple to define: Primary starters are obvious, and guys that are significant contributors at the position are equally easy to separate from the dudes that get trash-time and spot carries. Insignificant seasons also include redshirts, but not medical redshirts. I also took out JUCOs.
Here are the top 40 RBs from 2012 (NOT in order of production):
|2||1||0||Le'Veon Bell||Mich St||JR|
|2||1||0||Joseph Randle||Okla St||JR|
|2||0||0||Jahwan Edwards||Ball State||SO|
|1||0||0||Kenneth Dixon||La Tech||FR|
|2||0||1||Giovani Bernard||N Carolina||SO|
|1||2||1||Kerwynn Williams||Utah State||SR|
|3||0||1||Robbie Rouse||Fresno St||SR|
|1||1||1||Dri Archer||Kent State||JR|
|1||1||1||Carlos Hyde||Ohio State||JR|
|1||0||2||Antonio Andrews||Western Ky||JR|
|1||1||2||Kasey Carrier||New Mexico||JR|
|1||1||2||D.J. Harper||Boise St||SR|
|1||0||3||Zurlon Tipton||C Mich||JR|
|1||0||3||Cody Getz||Air Force||SR|
I have to admit, I was pretty surprised. Only 15 (37.5%) avoided having insignificant or redshirt seasons their first year on campus. And only six (15%) were the primary starters as true freshman, leaving nine (22.5%) as back-ups. That means the vast majority, 25 players (62.5%) spent at least one year doing nothing or next-to-nothing. Of those 25, only four (10%) went from insignificance to starting in one season. The rest (21, 52.5%) spent at least two years developing before becoming starters. And nearly as many (14, 35%) spent multiple years doing almost nothing as jumped right in as contributors (PS or SB) in their true freshmen campaigns. Heck, even Eddie Lacy redshirted.
This is admittedly a small sample size, but it's enough to draw some basic conclusisons:
- Plenty of talented RBs have insignificant seasons; many have more than one
- RARELY does a freshman RB burst onto the scene as a primary starter
- About half of these guys spend at least two years developing before they start
- The experts are idiots (of course, I must admit that I believed the "if they're any good they'll contribute as true freshmen stuff before I looked at it)
And some Michigan-specific conclusions:
- If Green and/or Smith doesn't contribute significantly this year, he's unlikely to start next year
- We shouldn't worry if Green and/or Smith doesn't contribute significantly this year
- Hope is not lost for Hayes, Johnson, or even Rawls.
It's worth noting that a few of the guys that spent multiple seasons developing turned out to be pretty darn good players. Guys like Eddie Lacy, Venric Mark, Carlos Hyde, Kenjon Barner, and Stefphon Jefferson all spent at least a couple seasons as insignificant contributors. On the flipside of that coin, lots of the best talent contributed early: Ka'Deem Carey, Le'Veon Bell, Montee Ball, Johnathan Franklin, and Todd Gurley.
Basically, we don't need to worry if Green and Smith don't contribute this year. It's definitely a good sign if they do, but there are much better things to be concerned about (S, OG, OC, and now WR) in 2013.
More completely one-sided highlights.