By Jacob Bourgeois; Twitter: @JacobBourgieFFB
Prompted on Twitter by numbers junky and writer at www.dynastyleaguefootball.com @Cooper_DFF, I started exploring receiving metrics with the goal of eliminating QB play from WR performance. There are other metrics out there (www.pff.com + www.playerprofiler.com). In fact, what I’ve come up with depends a lot on the work at www.playerprofiler.com, who list out Average Depth of Target (aDOT) and % of Catchable Targets for each player in 2020. From what I could find, “Yards per Catchable Target,” and the same adjusted by aDOT are new numbers that could provide some insight into a receiver’s true value.
Yards per Catchable Target (YpCT) is pretty self-explanatory. It’s the total number of yards a player had on a season, divided by their number of catchable targets. This yields average yardage per catchable target. The catchable part is intended to eliminate bad throws from the QB – I agree that not all catchable throws are created equal, but catchable vs. non-catchable gets us much closer. WRs can also account for uncatchable throws, either because they run a bad route, zig when they should have zagged, or lack the long speed to meet the ball downfield. Which brings us quickly to limitations: this stat can’t account for route running. Calvin Ridley, who is middle of the road in this metric, wins between when the football is snapped and when it hits his gloves. Deebo Samuel on the other hand (and some interesting names to be discussed) do absolutely win this way. Put the ball in my hands and let me show you what is what. That’s what we’re measuring: what you can do with your chances once a ball is within reach. For route running, Matt Harmon’s https://receptionperception.com/ is a great tool, and simply paying attention to Average Separation at www.playerprofiler.com would go a long way.
When I first did the math on YpCT and ran through the list I saw a lot of deep ball guys close to the top which makes sense, if all else is equal the receiver who catches the ball further downfield will have more Yards per catchable target than someone running shallower routes. To account for this, my next step was to divide out Average Depth of Target: depth adjusted YpCT or daYpCT.
This yielded numbers around one, also kind of intuitive (right?). If Calvin Ridley has an Average Depth of Target of 14, it holds that if he catches the ball with some frequency, then he’s going to have close to 14 yards per catchable target. Drops subtract from this total and Yards after the catch (YAC) add to it.
i.e. if Calvin Ridley has 100% catch rate on catchable targets, and 0 Yards after the catch, then his Yards per Catchable Target will exactly equal his average depth of target in this metric; thus daYpCT = 1. If he has 90% catch rate (and 0 YAC/R), then his YpCT will be 90% of his aDOT; daYpCT= 0.9. If he has 1.4 YAC/R (and still a 100% catch rate), then his YpCT will be 1.4 yards better than his ADOT; daYpCT = 15.4/14 = 1.1.
Adjusting YpCT by average depth of target skewed the numbers more than I expected towards the slot guys, or the guys like Tight Ends who receive shallower balls and are expected to make progress – verses deeper threats who’s yardage work is all before the catch and their success is measured simply by coming down with the ball. Both numbers tell us something, so I will present the data side by side. I’ve toyed with adjustment factors to get to something that balances the two out (YpCT^1.5/aDOT was a good balance) but it became too abstract and less interesting to me. There is also the potential to adjust the catch percentage based on the average depth of target to concede that downfield catches are harder to make and harder still to improve on once they’re in your hands, but I haven’t found an adjustment factor that makes me feel whole inside, so I’m not ready to present that idea.
But that’s too much about the process.
The Results: Winners
The table below shows players in order by YpCT filtered for daYpCTs greater than 1. These are the winners of this metric system, who did the most with their catchable opportunities. You’ll notice Tyreek Hill just makes the cutoff on daYpCT but has a top end YPCT. This tells us, that a lot of his damage comes on lower percentage plays, and while he’s running under the ball in air. Gallup, DJ Moore, and Rashard Higgins are all like Tyreek in the way they won in 2020. Emmanuel Sanders, Courtland Sutton in 2019, and Danny Amendola have lesser average depths of target and accounted for their high end YpCT through high catch percentage and yards after the catch, and thus they show up high on daYpCT.
Is there anything actionable from the below?
- Julio Jones ain’t done.
- Justin Jefferson did it with Volume and Efficiency.
- Rashard Higgins, D.J. Moore, and Will Fuller were all efficient with high end aDOT.
- Michael Gallup and Emmanuel Sanders made lemonade from lemon targets.
- Deebo Samuel is a beast with the ball in his hands. I actually adjusted his aDOT from 2.2 to 6 to make my numbers look prettier. At a 2.2 aDOT he’s off the chart literally on daYpCT (4.94). If I charted RBs and TEs as well, they would be way up there with daYpCT.
- Michael Pittman raised my eyebrows with his daYpCT.
The Results: Losers
The below table is sorted by depth adjusted Yards per Catchable Target (daYpCT) starting from the bottom. If you watched any football in 2020, A.J. Green bottoming out the metric is no surprise. Many of us missed how bad Preston Williams was because the sample size was so limited. Ruggs was used on the deep deep balls and didn’t convert (compare to MVS who was the only receiver with a higher aDOT). Darnell Mooney’s 2020 season is actually propped up more by spot opportunity than it is by efficiency. The single digit YpCTs with low efficiency are all red flag players fitting the JAG category to a tee.
- Odell is not in sync in Cleveland.
- Calvin Ridley’s value is in what he does before he gets there as we’ve discussed already.
- DK Metcalf put up a season similar to Tyreek, and just missed the 1.0 daYpCT
- Denzel Mims is right between Metcalf and Tyreek – arrow up for me.
- Rookies Gabe Davis, Tee Higgins, and Chase Claypool are bunched up with middling efficiency.
- Golladay’s success might have been more Stafford / utilization than we think.
That’s all I have time for in this one – I know this doesn’t paint a full picture – but I am not done exploring this and other metrics. Drop me a note on Twitter if you hate it 😉.