1. Advanced NFL Stats weighs in on the evaluating running backs/running games discussion, which I addressed (with assistance from some wonderful comments) here and here. Do read the whole thing, but Brian has, as always, a very interesting take. Drawing on earlier discussion about risky and conservative strategies for underdogs and favorites (see my discussion of the topic here and Brian's here), he asserts:
I want to address an age-old water cooler question that Chris discussed in his post at Smart Football. Consider two RBs, both with identical YPC averages. One however, is a boom and bust guy, like Barry Sanders, and the other is a steady plodder like Jerome Bettis. Which kind of RB would you rather have on your team?
The answer is it depends. Essentially, we have a choice between a high-variance RB and a low-variance RB. When a team is an underdog team, it wants high-variance intermediate outcomes to maximize its chances of winning. And when a team is a favorite, it wants low-variance outcomes. Whether those outcomes occur through play selection, through 4th down doctrine, or through RB style, isn't important. If you're an otherwise below-average team, you'd want the boom and bust style RB. If you're an otherwise above-average team, you'd want the steady plodder. . . .
Further, even if the high-variance RB has a lower average YPC, we'd still want him carrying the ball when we're losing. This is due to the math involved in competing probability distributions.
That's just one aspect of it. He uses a handy chart for the distribution of runs for the various backs...
...and notes how curious it is that Tomlinson's distribution looks so much like that of the rest of the NFL. (This same thing ends up holding true for most backs.) What conclusions does Burke draw? With the usual caveats,
[w]hat amazes me is how similar they all are to each other and to the league average. . . . Usually, a RB needs 4 to 5 yards to just break even in terms of his team's probability of converting a first down. What we'd want to see on a RB's distribution is as much probability mass as possible to the right of 4 yards.
So if [Jerome] Bettis' distribution looks so much like Tomlinson's, how does Bettis have a 3.9 career YPC and Tomlinson have a 4.4 career YPC? As others have noted previously, the difference among RB YPC numbers primarily come from big runs. It's the open field breakaway ability that separates the guys with big YPC stats from the other RBs. Of Tomlinson's runs, 1.5% were for 30 yards or more. Bettis' 30+ yd gains comprised only 0.46% of his carries. The other RBs and the league average are as follows:
- NFL 0.91%
- [Jamal] Lewis 0.88%
- [Brian] Westbrook 0.93%
- [Adrian] Peterson 2.20%
Adrian Peterson's 2.2% figure is exceptional. It's interesting because it really suggests that what separates Peterson as a great runner is based on only 2% or so of his runs. Otherwise, he's practically average.
2. Courtesy of Brophy, I have added video of Mike Leach's "settle & noose" drill, which, it will be recalled, is both a great warm-up drill and works on teaching receivers to find holes in the zone and quarterbacks how to deliver the ball to them.
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