What a new approach to evaluating receivers and tight ends says about the 2018 NFL Draft class

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My own personal favorite part of a given draft cycle is when pro coaches and scouts complain that others aren’t helping them do their jobs well enough. This is typically a construct for quarterbacks — they don’t know how to line up under center! — but there are variations.

Earlier in April, for instance, we learned about the [hits cap lock button] NFL’s WIDE RECEIVER CRISIS.

The reasons Proehl gives for this CRISIS are things like limited responsibilities and route trees in college spread offenses, iffy technique, etc.

Some of the criticism from Proehl and others stems from the same cause of QB criticism: college offenses are into simplifying, which means we don’t necessarily know how players will handle more complicated systems. Some players from ‘simple’ systems do just fine, and some don’t, but it’s an unknown heading into the draft cycle.

Of course, some of these “slow to lift off” prospects were over-drafted in the first place Dorsett, Williams, Perriman, and White all had below-average catch rates in their respective college careers, and as we’ll learn, your college catch rate correlates relatively well with your pro catch rate.

Using the marginal efficiency concept I originally discussed here, White and Dorsett were both in the bottom 10 percentile in marginal efficiency among 2010-17 wide receiver draftees. That they were over-drafted (White went seventh and Dorsett went 29th in the 2015 draft) wasn’t their fault. Meanwhile, looking at marginal explosiveness would have provided pretty significant red flags for Treadwell (15th percentile among 2010-17 draftees) and Agholor (37th), too.

So yeah, it’s not necessarily colleges’ fault that teams have been drafting certain receivers too high. But there’s one thing stats and scouts can agree on: this year’s receiver crops isn’t all that impressive.

It is a permanent disclaimer, that stats can’t measure everything you need to know about, well, anything. But they can start us down the right path.

Here are some things we can learn about receiver draftees.

1. As with QBs and RBs, your college WR stats are your pro ceiling ... with a few more exceptions.

It is a commonly accepted notion that receivers’ stats are driven in part by the quality of the QB. That makes sense. While everyone depends on everybody else in a complicated sport like football, receivers need a quarterback to throw the ball before they can even begin to prove their worth.

Still, in terms of broad measures, we still basically know that a receiver’s college stats are his pro ceiling.

Using yards per target, of 71 wideouts who were a) drafted between 2010-17 and b) targeted at least 100 times in their first four pro seasons*, only three exceeded their college average by any significant amount: Julio Jones, Kenny Stills, and Randall Cobb.

Jones’ college averages were dragged down significantly by an injury-plagued sophomore season. He averaged just 6.5 yards per target that year, but looking at just his freshman and junior seasons, he averaged 9.8. His pro average through four seasons? 9.8.

Stills and Cobb, meanwhile, left college as blank slates in a way. Both were used in a number of different roles at Oklahoma and Kentucky, respectively, and it was the same story in their first four years in the pros, too. Stills was a high-efficiency guy with the Saints and a big-play threat with the Dolphins. And after playing little in his first year at Green Bay, Cobb was used as a possession man in year 2, then erupted for 1,287 yards (14.1 per catch) in year 4. (Since then: 10.5 yards per catch or fewer each year. Weird career.)

Yards per target is an incredibly broad measure, though, taking into account aspects of both efficiency and explosiveness. If we split those things out, the statistical picture gets a little bit blurrier. But perhaps not as blurry as you might think.

* Once again, we’ll use a player’s first four seasons as a guide, since that’s all you’re probably guaranteed to have a guy with a rookie contract. These 71 wideouts will be used for all the charts below.

Whereas we can almost definitively say for QBs and RBs, their college stats are their pro ceiling, there are indeed more exceptions with receivers, for all the reasons listed above. But their correlations between college and pro success are actually stronger than that of QBs or RBs. And one particular combine stat is pretty telling, too, albeit in extremely contradictory ways.

WR stat correlations Stat 1 Stat 2 correlation Stat 1 Stat 2 correlation 40-yard dash NFL marginal explosiveness (first 4 yrs) -0.525 College catch rate (career) NFL catch rate (first 4 yrs) 0.427 College marginal efficiency (career) NFL marginal efficiency (first 4 yrs) 0.350 40-yard dash NFL marginal efficiency (first 4 yrs) 0.325 College catch rate (career) NFL marginal efficiency (first 4 yrs) 0.303 College yards per catch (career) NFL yards per catch (first 4 yrs) 0.297 College marginal explosiveness (career) NFL marginal explosiveness (first 4 yrs) 0.230

Again, nothing here is air-tight in terms of statistical significance. Far from it. But these are pretty good if you’re looking for projection factors — again, better than their QB counterparts. I didn’t expect to see that.

By the way, spare some time in your thoughts and prayers for the math-inclined NFL scouts out there, as they try to figure out how to deal with the fact that there’s a pretty strong correlation between lower 40 time and higher explosiveness (as we would expect) ... and a correlation nearly as strong between higher 40 time and higher efficiency. Finding you a man who can do both is tricky.

2. Tight ends are almost impossible to evaluate

I was pretty excited when I saw those statistical correlations above, as what I saw for tight ends was what I expected to see for all pass catchers. That said, the combine stats paint a very strange picture of what to look for in a tight end.

(Note: the data below is for the 37 tight ends who were drafted between 2010-17 and have been targeted at least 50 times in the pros.)

TE stat correlations Stat 1 Stat 2 correlation Stat 1 Stat 2 correlation Broad jump NFL marginal explosiveness (first 4 yrs) 0.421 3-cone drill NFL marginal efficiency (first 4 yrs) 0.377 Vertical jump NFL catch rate (first 4 yrs) -0.359 Broad jump NFL yards per catch (first 4 yrs) 0.353 3-cone drill NFL marginal explosiveness (first 4 yrs) -0.307 Broad jump NFL marginal efficiency (first 4 yrs) -0.269 Vertical jump NFL yards per catch (first 4 yrs) 0.268 40-yard dash NFL marginal efficiency (first 4 yrs) 0.243 40-yard dash NFL marginal explosiveness (first 4 yrs) -0.218 College marginal efficiency (career) NFL marginal efficiency (first 4 yrs) 0.170 College marginal explosiveness (career) NFL marginal explosiveness (first 4 yrs) 0.112 College catch rate (career) NFL marginal efficiency (first 4 yrs) -0.020 College catch rate (career) NFL catch rate (first 4 yrs) -0.006 College yards per catch (career) NFL yards per catch (first 4 yrs) -0.002

It kind of makes you laugh out loud, doesn’t it? The better athlete you are, the more likely you are to be an explosive receiving option, and the less likely you are to actually be an efficient receiving option.

You almost have to decide what you’re looking for in a tight end and go from there. And the minimal correlation between college stats and pro production suggests that while you probably can’t coach away a quarterback’s flaws, and receivers are perhaps more well-defined than we think, tight ends are indeed lumps of clay to be sculpted, at least in terms of the passing game. (I’m guessing college film will tell you about a guy’s blocking proficiency, though.)

It probably makes sense that tight ends are a bit of a blank slate, though, considering the success of former basketball players at the position, huh?

3. Your best 2018 draft options are blurry

Up top, I referenced the concept of prospects ranking in the 60th percentile or higher among other draftees in marginal efficiency, marginal explosiveness, and catch rate. Since there are decent correlations between college and pro proficiency in each category, it would stand to reason that, if combined with a decent 40 time and perhaps other Combine measurements, you could find some prospects more likely than others to succeed there.

Of the list of “slow to lift off” guys above, Devante Parker was the only one to rank in in the 60th percentile or above in all three stats. His 4.45 40 time ranked him in the 54th percentile there, as well. He got a slow start because of injuries, but he seems to have improved his professional stock in the last two seasons, catching a combined 113 passes for 1,414 yards, and five touchdowns, with a 62 percent catch rate. That tops what most of the others on that list have managed, at least.

Granted, we don’t have 40 times for every prospect, but here’s a list of the guys who hit at least the 50th percentile in all three statistical categories and 40 time, listed with their pro production so far:

Brandin Cooks (No. 20 pick, 2014): 58 games, 280 catches, 3,943 yards (14.1 per catch, 9.2 per target), 27 TD

Amari Cooper (No. 4 pick, 2015): 46 games, 203 catches, 2,903 yards (14.3 per catch, 8.1 per target), 18 TD

DeVante Parker (No. 14 pick, 2015): 43 games, 139 catches, 1,908 yards (13.7 per catch, 8.2 per target), 8 TD

Will Fuller (No. 21 pick, 2016): 24 games, 75 catches, 1,058 yards (14.1 per catch, 7.5 per target), 9 TD

Titus Young (No. 44 pick, 2011): 26 games, 81 catches, 990 yards (12.2 per catch, 7.0 per target), 10 TD

Chris Conley (No. 76 pick, 2015): 37 games, 72 catches, 904 yards (12.6 per catch, 7.8 per catch), 1 TD

Corey Coleman (No. 15 pick, 2016): 19 games, 56 catches, 718 yards (12.8 per catch, 5.5 per target), 5 TD

Even with a bunch of statistical indicators and decent correlations, that’s a pretty mixed bag.

To hit the 50th percentile in each of those four categories, you need a plus-11.6 percent marginal efficiency, a plus-0.40 marginal explosiveness, a 63 percent career catch rate, and a 4.45-second time in the 40. One guy hits the mark in all four categories: Texas Tech’s Keke Coutee.

Here’s where context begins to overload what we can learn from college stats.

Calvin Ridley was one of the most frequently targeted players in the country — Alabama quarterback Jalen Hurts’ reads were basically Ridley first, Ridley second, and then run. Still, he thrived during his junior season, raising his marginal efficiency from plus-6 percent to plus-13 and his marginal efficiency from plus-0.30 to plus-0.43. Both of those marks would put him over the 50th-percentile bar.

Equanimeous St. Brown, meanwhile, saw his efficiency numbers plummet after a QB change in 2017. He posted a plus-19 percent marginal efficiency with DeShone Kizer behind center in 2016, then a minus-3 percent last year.

Like Stills, Christian Kirk saw his usage change pretty drastically in his final season, from an all-or-nothing big play guy (plus-0 percent marginal efficiency, plus-0.39 marginal explosiveness) to more of a possession guy (plus-10 percent, 0.33). He still doesn’t quite clear the explosiveness bar, but his 4.47 40 time suggests he might be able to.

Coutee indeed passes every test, and his year-to-year growth was pretty incredible: plus-8 percent marginal efficiency and minus-0.33 marginal explosiveness as a little-used freshman, then plus-15 percent and plus-0.50 as a sophomore and plus-17 percent and plus-0.65 as a junior. But how much of a penalty does he get for playing in a Big 12 spread-style offense? Granted, his head coach was Mike Evans’ offensive coordinator at Texas A&M, so the lines blur here, but Coutee could fall under the “limited route tree” umbrella in a lot of coaches’ eyes.

Are there any sleepers later in the draft? It all depends on what you’re looking for.

Deontay Burnett was one of the most efficient receivers in college football, but his 40 time stinks.

Deon Cain is fast and potentially explosive, but he was used in a drastically different way at Clemson in 2017, and his numbers suffered (plus-11 percent marginal efficiency, just plus-0.18 marginal explosiveness).

Is J’Mon Moore getting punished by my use of career stats? He was thrust into the No. 1 WR role as a sophomore, catching passes mostly from a true freshman. That’s a dreadful combination. But in his final two seasons, he produced a plus-10 percent marginal efficiency and plus-0.57 marginal explosiveness. Combined with a decent 40 time, he could be worth a mid-round pick.

Jester Weah and Marques Valdes-Scantling each produced blazing explosiveness numbers and 40 times, but both were dreadful from an efficiency standpoint. Worth the risk?

Is the picture any clearer at tight end? Not really.

4. Just pick Mike Gesicki. Or Jaylen Samuels.

You can obviously see whatever you want when it comes to tight end data, but it has to be noted that Mike Gesicki both a) pretty much nailed every Combine measurement and b) improved drastically on the field over the last two years.

In attempting to catch passes from Christian Hackenberg in 2015, he managed just a minus-13 percent marginal efficiency and minus-0.02 marginal explosiveness. In two years in a new offensive system with quarterback Trace McSorley? Plus-7 percent and plus-0.38, respectively.

That’s still not incredibly efficient, but either he or Oklahoma’s Mark Andrews posted the best combination of stats and measurements. And Andrews was basically deployed as a wideout.

Again, though, these stats are such that good athleticism could mean bad efficiency. Good luck. But know that if you choose NC State’s Jaylen Samuels, you could be getting both an interesting tight end prospect and the most efficient running back prospect in the draft. Pick him now, and figure out what to do with him later.