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Before fully kicking off this summer’s continuation of my rushing study, I’ve got to get some things out of the way. The first, and simplest, of them is to make this whole thing more accessible.
A new name!
Above other things, improving that approachability consists of changing the series name itself (thanks to the advice of a smart veteran in the field who actually knows what he’s talking about). “Observational Rushing Number(s)” (ORN) doesn’t roll off the tongue, but it checks the rest of my desired boxes: catchy abbreviation, acronym originality (as far as I know), and self-explanatory-ness. I won’t go back and change anything to reflect this shift, but will be referring to the series by ORN from here on out.
Generated yard rates and box disadvantage
After some data digging, it appears that these two stats can work together quite well to give us a different perspective of a back’s creativity, further separated from outside situations that Stuff Generated Yards per stuff (SGY/C) and Hit Generated Yards per hole hit (HGY/C) can be subject to. Using box disadvantage, I can filter out plays that provide overly favorable (on passing downs, when defenses are happy to give up some yards on the ground) or unfavorable (in goal line situations, where safeties are walked into the box or even substituted for more linebackers) numbers to the running game. Now, we have a subset of standard running plays, so that goal-line backs aren’t punished and third-down-carriers aren’t rewarded.
The second half of the task, now, is to look at how backs create in these standard situations. As things stand now, I’ve effectively separated carries in which the back hits a hole into three buckets (“gashes” of 10-plus Generated Yards, “chunks” of four-to-nine GY, and “takes” of less-than-four GY), while stuffs are sorted into two buckets (three-plus GY and under three GY). The cutoffs are obviously arbitrary to a degree, but still meaningful, and have turned out to translate well to rushing styles.
Evidence of that translation arises in the relationship between these GY rate buckets and the simple HGY/SGY averages. For instance, take a look at HGY/C plotted against H 10+ Rate (10-plus GY rate on hits):
(That dot way up there in the corner? That’s Marlon Mack. His numbers were unsustainably good in a small sample size, but still indicative of an awesome creator.)
The correlation is similarly strong when looking at SGY/C and S 3+ Rate (three-plus GY rate on stuffs):
In future years, I’ll be interested to see whether the simple averages or the GY rates are better indicators of future play. My hunch is that players’ HGY/C and SGY/C marks will regress back toward those trend lines (which will be more accurate and better-defined with more backs in the sample). Regardless, for now, it’s clear that GY rates give us another good look at a back’s creativity.
Using the modified Supercomposite, we can strip apart the ORNs in order to grade both the running back and blocking unit individually. Take that down a level, place each charted game into one data set, and you can score every player’s individual performances. Let’s look at Kareem Hunt’s performances from Week 1 through 14:
Hunt had a pretty dang consistently good 2017. With percentile performances we can look at week-to-week variance, ceilings, floors, and trends in running back (or offensive line) play. The interesting part is that those trends vary a lot by player and will be some of the most interesting phenomena to dig into once I jump into my individual write-ups.
I’ve gotten to the point where there’s an overwhelming amount of ORN-specific terms that I toss around in these articles. To mitigate the issue, I created a glossary of the most important and highly-used terms in the series.
That’s about it. These (likely) are each of the new tools that I’ll use in my 2017 NFL season ORN series, so with nothing else to explain or elaborate on, the fun stuff comes next!