Solak | 2018 Senior Bowl Contextualized Quarterbacking Available
It is with tremendous pleasure that I offer to you today the full Senior Bowl Contextualized Quarterbacking: the most intensive guide to the 2018 Senior Bowl quarterbacks you will find.
Okay, it’s likely the only one. But the point remains.
If you’re yet unfamiliar with the Contextualized Quarterbacking (CQ) project, it’s a chart-oriented project. By cataloging every throw a quarterback makes and understanding the particular factors around that throw, we can draw out conclusions regarding under what circumstances these quarterbacks best work, and under what circumstances they simply cannot operate.
You can download the CQ here: Contextualized Quarterbacking
Let’s take a look at what’s inside:
Player Data Sheets
There are three pages to every player data sheet. The first gives a quick-glance scouting report, to provide a sense of familiarity to a whole slew of numbers. The player’s gross data is included, as well as their situational data. How a player performs on 3rd downs isn’t terribly interesting to me, unless they’re shockingly good or shockingly poor. It gives me a feel for their ability in tough situations.
You will notice, as you go through the CQ, that the calculations for Adjusted Conversion % has changed. It now includes all dropbacks under those particular conditions, which includes scrambles, sacks, throwaways, and the like. Better numbers!
The data by region helps us understand how a player distributes the ball within his offense, and to what regions of the field he tends to be more accurate. Josh Allen’s .714 accuracy score to his left 20+, for example, sticks out like a sore thumb, especially when compared to the congruent score in 20+ right.
The second page of the CQ player sheet is entirely new-never before seen! Heat maps show us how in greater visual detail how heavily players lean to certain areas of the field, from where the bulk of their production comes, and what their accuracy and ball placement look like when divorced from one another. As you’ll read in the CQ (I hope!), placement is a more complex metric and is more predictive of “good throws” than accuracy-separating the two helps us determine which completion percentages and yardage market shares may be telling lies.
The exceptional data up top is a hat’s tip to the work that the CQ does not do: evaluate QB decision-making. The CQ is interested in the thrower, not so much the mind behind it: as such, there is no deep-diving data that goes in to the sacks a QB takes, or the yardage he saves by throwing the football away, et cetera. A meek look at the percentage of dropbacks on which these things occur gives us a cursory glance at a QB’s propensity to take risks, try to extend plays, or have a ball batted at the line.
Here, we turn to the crown jewel of the CQ: the contexts. We can separate a QB’s attempts by these contexts, and in doing so, understand how each context affects a QB’s accuracy, placement, risk-taking/erraticism, and so on. This information not only helps open the book on the prospect, but helps us imagine an offense in which each of these QB’s could be successful. Is not this the ultimate goal of player evaluation? Not only finding the good ones, but deploying them in a way that maximizes their ability.
Be sure to check out the “Notable Measures” table up at the top. That table just quickly glances over some of the regions in which the QB in question stands out among his group-both on the good and the bad ends, respectively. That data comes from the massive treasure chest of comparative data at the end of the CQ, following the player sheets.
Woah Nelly, this is some good stuff. These pages take metrics of interest-placement in tight windows? Accuracy when pressured? % of offense due to YAC? Drop rate?-and compares them across the board for each quarterback, so that we can see how the competition stacks up. This graph, for example, highlights just how often Luke Falk and Brandon Silvers-Air Raid QBs-are throwing the ball behind the line of scrimmage, compared to their contemporaries. Mike White and Kurt Benkert, on the other hand (both Air Raid inspired offenses) spend a lot more of their time in the 0-9 range.
I don’t know if there’s data like this anywhere else. These numbers help us estimate the real, quantifiable impact of the shifting landscape of QB play on individual performers, which sharpens our evaluation of their tape and primes us for a thorough investigation into their game in Mobile next week. Whether or not you attend the Senior Bowl, I hope you can find a use for this data as you evaluate these players, and that you come back for more when the entire CQ drops-with all quarterbacks-before the 2018 NFL Draft.
I’ve used the pre-released CQ data to exemplify how we can gear this data into better evaluations. You can check out some of those posts here:
The link for the CQ, again, is here: Contextualized Quarterbacking