(In this 3-part series, we’ll take a look at the overrated, underrated, and projected first round receivers according to three of my favorite statistics for evaluating college talent: WROPS, RAS, and WRAPS.)
With the Green Bay Packers in desperate need of more wide receivers, the position has been the primary focus of many a Packer pundit in anticipation of the 2022 draft. Adding statistical context to receivers is extremely helpful in picking out potential pretenders and ascenders. As a quick primer:
1. WROPS (Wide Receiver OPS)
For those unfamiliar with WROPS, it combines a receiver’s Catch Percentage and Yards per Reception into one statistic, scaled to baseball’s “OPS” stat. In general, 1.000 is great, .900 is very good, .800 is average, and anything below is sub-par. WROPS is made up of WROBP and WRSLG, also weighted to their MLB counterparts. Anything over a .400 WROBP is excellent, but a receiver with a .330 WROBP can still be effective with a WRSLG over .600, just like a power hitter in baseball, and “power hitters v. high-average hitters” is maybe the best way to think about the types of receivers that WROPS attempts to contextualize.
For instance, in 2020, Chris Olave had a WROPS slash line of .514/.519/1.033. Most pass-catchers with a .500 WROBP are running backs catching checkdowns regularly, but Olave managed the number while also managing 14.6 yards per catch. It was secretly one of the greatest college receiving seasons of all time and is the platonic ideal for a “high average hitter” receiver.
Contrast Olave with Alabama’s Jameson Williams in 2021, and his also incredible .402/.657/1.058. Williams' catch percentage would still see him as productive with a much lower WRSLG, but instead we see one of the greatest power hitting receivers of recent memory. Williams caught 79 balls, and made the most of all of them, posting the 2nd highest WRSLG of the 2021 college season of any player with 50 catches. He’s not the only slugger in the draft (Alec Pierce’s .367/.558/.984, for instance), but Williams blows them all away.
WROPS is effective in identifying high-level producers because it properly credits all types of receivers by answering the question: “Is your catch percentage good considering the yards you gain when you make a catch?” It is a rate stat, and can also be useful to identify efficient players who may lack targets for various reasons.
2022 WROPS 50+ Receptions
|Jaxon Smith-Njigba||Ohio State||WR||13||95||0.509||0.558||1.067|
|Jack Sorenson||Miami (OH)||WR||13||76||0.368||0.611||0.978|
|Isaiah Likely||Coastal Carolina||TE||13||59||0.454||0.512||0.965|
|Jalen Tolbert||South Alabama||WR||12||82||0.362||0.594||0.956|
|Jaivon Heiligh||Coastal Carolina||WR||13||66||0.384||0.564||0.949|
|Mitchell Tinsley||Western Kentucky||WR||14||87||0.414||0.531||0.946|
|Trayvon Rudolph||Northern Illinois||WR||14||51||0.356||0.578||0.933|
|Ali Jennings||Old Dominion||WR||13||62||0.365||0.568||0.932|
|Deven Thompkins||Utah State||WR||14||102||0.378||0.551||0.929|
|Brandon Bowling||Utah State||WR||14||56||0.431||0.492||0.922|
|Malik Williams||Appalachian State||WR||14||52||0.400||0.521||0.921|
|A.T. Perry||Wake Forest||WR||14||71||0.316||0.601||0.916|
|Jayden Reed||Michigan State||WR||13||59||0.337||0.574||0.911|
|Garrett Wilson||Ohio State||WR||11||70||0.408||0.498||0.906|
|Austin Williams||Mississippi State||WR||13||52||0.503||0.393||0.896|
|Jaquarii Roberson||Wake Forest||WR||13||71||0.384||0.502||0.885|
|Khalil Shakir||Boise State||WR||12||77||0.398||0.479||0.877|
|Calvin Jackson||Washington State||WR||13||66||0.381||0.495||0.876|
|Thomas Hennigan||Appalachian State||WR||14||60||0.424||0.452||0.876|
|Skyy Moore||Western Michigan||WR||12||95||0.422||0.449||0.871|
|Jerreth Sterns||Western Kentucky||WR||14||150||0.448||0.419||0.867|
|Josh Kelly||Fresno State||WR||13||52||0.371||0.495||0.866|
|Kalil Pimpleton||Central Michigan||WR||13||62||0.351||0.512||0.862|
|Corey Sutton||Appalachian State||WR||13||61||0.366||0.488||0.854|
|Chris Olave||Ohio State||WR||12||65||0.379||0.475||0.854|
|Xavier Hutchinson||Iowa State||WR||13||83||0.461||0.393||0.854|
|Thayer Thomas||North Carolina State||WR||12||51||0.464||0.386||0.850|
|Josh Downs||North Carolina||WR||13||101||0.409||0.436||0.845|
|Parker Washington||Penn State||WR||13||64||0.422||0.422||0.844|
|Victor Tucker||UNC Charlotte||WR||11||51||0.431||0.413||0.843|
|Tay Martin||Oklahoma State||WR||13||80||0.400||0.432||0.832|
|Grant DuBose||UNC Charlotte||WR||12||62||0.354||0.475||0.829|
|Tyler Snead||East Carolina||WR||12||67||0.402||0.422||0.824|
|Te'Vailance Hunt||Arkansas State||WR||11||51||0.344||0.479||0.822|
|Emeka Emezie||North Carolina State||WR||12||60||0.379||0.442||0.821|
|Michael Mayer||Notre Dame||TE||12||71||0.430||0.389||0.820|
|Trey McBride||Colorado State||TE||12||90||0.403||0.413||0.815|
|Jahan Dotson||Penn State||WR||12||91||0.374||0.429||0.803|
|Hassan Beydoun||Eastern Michigan||WR||13||97||0.448||0.347||0.794|
|Corey Rucker||Arkansas State||WR||12||59||0.331||0.462||0.793|
|Charlie Kolar||Iowa State||TE||12||62||0.387||0.403||0.790|
|Roderic Burns||North Texas||WR||13||58||0.331||0.455||0.787|
|Jalen Wayne||South Alabama||WR||12||53||0.393||0.393||0.785|
|Smoke Harris||Louisiana Tech||WR||12||71||0.435||0.350||0.784|
|Winston Wright||West Virginia||WR||13||63||0.425||0.360||0.784|
|Travell Harris||Washington State||WR||13||76||0.426||0.353||0.779|
|Jalen Cropper||Fresno State||WR||13||85||0.425||0.350||0.775|
|Jaden Walley||Mississippi State||WR||13||55||0.398||0.376||0.774|
|Lajohntay Wester||Florida Atlantic||WR||12||65||0.415||0.356||0.771|
|Jesse Matthews||San Diego State||WR||14||57||0.398||0.373||0.771|
|Jayshon Jackson||Ball State||WR||13||69||0.373||0.396||0.769|
|Makai Polk||Mississippi State||WR||13||105||0.438||0.330||0.768|
|Justin Hall||Ball State||WR||11||61||0.436||0.330||0.766|
|Ryan O'Keefe||Central Florida||WR||13||84||0.442||0.320||0.762|
|Brennan Presley||Oklahoma State||WR||14||50||0.353||0.409||0.762|
|Malachi Corley||Western Kentucky||WR||14||73||0.425||0.314||0.739|
|Dillon Johnson||Mississippi State||RB||13||65||0.513||0.215||0.728|
|Dylan Drummond||Eastern Michigan||WR||13||64||0.359||0.363||0.722|
|Zack Kuntz||Old Dominion||TE||13||73||0.395||0.314||0.708|
|Jo'quavious Marks||Mississippi State||RB||13||83||0.498||0.198||0.696|
|Austin Osborne||Bowling Green||WR||12||64||0.404||0.281||0.685|
2. Relative Athletic Score (RAS)
Almost everyone knows and loves Kent Lee Platte’s (@Mathbomb) RAS at this point, but if you are unfamiliar with RAS, please visit the RAS site. In short, RAS combines the various aspects of a prospects athletic testing into size, speed, explosion, and agility categories, and aggregates them into a single number on a ten point scale, which gives us a good indicator of that player’s overall athleticism. The RAS Card is a triumph of data visualization, and instantly tells you, upon a glance, everything you need to know about the athleticism of a player.
3. WRAPS (WROPS+RAS)
I then take WROPS, which is a production statistic, and combine it with RAS (Relative Athletic Score to create a single number which tells you whether a prospect is both productive AND athletic. I call this Frankenstein’s Monster “WRAPS.” WRAPS works on a 20-point scale (10 for RAS and 10ish for WROPS) and generally speaking, WRAPS works pretty well. The only two players in last year’s drafts to put up elite WRAPS numbers were Ja’Marr Chase (awesome), Kyle Pitts (also awesome), and Nico Collins (not awesome yet, but he’s stuck on the Texans so let’s give him some time). Previous WRAPS stars include Justin Jefferson (awesome), CeeDee Lamb (pretty darn good) and Brandon Aiyuk (good). It’s not perfect, as Henry Ruggs was also elite, as was John Hightower, but by and large, it works extremely well in identifying elite talent.
|Player||Position||Year||College||All Time RAS||WROPS||Adjusted WROPS||WRAPS|
|Player||Position||Year||College||All Time RAS||WROPS||Adjusted WROPS||WRAPS|
|Christian Watson||WR||2022||North Dakota State||9.96||1.058||10.58||20.54|
|Kevin Austin||WR||2022||Notre Dame||9.94||0.957||9.57||19.51|
|Jalen Tolbert||WR||2022||South Alabama||8.58||0.956||9.56||18.14|
|Keshunn Abram||WR||2022||Kent State||9.17||0.878||8.78||17.95|
|Velus Jones Jr.||WR||2022||Tennessee||9.07||0.877||8.77||17.84|
|Calvin Austin III||WR||2022||Memphis||9.05||0.861||8.61||17.66|
|Derek Wright||WR||2022||Utah State||8.68||0.861||8.61||17.29|
|Chris Olave||WR||2022||Ohio State||8.65||0.854||8.54||17.19|
|Jalen Nailor||WR||2022||Michigan State||8.02||0.909||9.09||17.11|
|Khalil Shakir||WR||2022||Boise State||8.28||0.877||8.77||17.05|
|Garrett Wilson||WR||2022||Ohio State||7.74||0.906||9.06||16.8|
|Deven Thompkins||WR||2022||Utah State||7.25||0.929||9.29||16.54|
|Skyy Moore||WR||2022||Western Michigan||7.54||0.871||8.71||16.25|
|Danny Gray||WR||2022||Southern Methodist||6.74||0.95||9.5||16.24|
|Erik Ezukanma||WR||2022||Texas Tech||6.68||0.859||8.59||15.27|
|Kalil Pimpleton||WR||2022||Central Michigan||6.5||0.862||8.62||15.12|
|Tay Martin||WR||2022||Oklahoma State||6.4||0.832||8.32||14.72|
|Octavius Evans||WR||2022||Boise State||6.91||0.76||7.6||14.51|
|Calvin Jackson Jr.||WR||2022||Washington State||5.68||0.876||8.76||14.44|
|Jahan Dotson||WR||2022||Penn State||6.29||0.803||8.03||14.32|
|Jaivon Heiligh||WR||2022||Coastal Carolina||3.88||0.949||9.49||13.37|
|Chris Pierce Jr.||WR||2022||Vanderbilt||5.75||0.722||7.22||12.97|
|Stanley Berryhill III||WR||2022||Arizona||5.79||0.689||6.89||12.68|
|Reggie Roberson||WR||2022||Southern Methodist||4.34||0.819||8.19||12.53|
|Makai Polk||WR||2022||Mississippi State||4.85||0.768||7.68||12.53|
|Kameron Brown||WR||2022||Coastal Carolina||2.53||0.995||9.95||12.48|
|Kaylon Geiger Sr.||WR||2022||Texas Tech||4.72||0.768||7.68||12.4|
|Kwamie Lassiter II||WR||2022||Kansas||4.46||0.788||7.88||12.34|
|Tre Turner||WR||2022||Virginia Tech||3.5||0.865||8.65||12.15|
|Travell Harris||WR||2022||Washington State||4.31||0.779||7.79||12.1|
|Justin Hall||WR||2022||Ball State||4.18||0.766||7.66||11.84|
|Emeka Emezie||WR||2022||North Carolina State||3.21||0.821||8.21||11.42|
|Kyric McGowan||WR||2022||Georgia Tech||3.77||0.752||7.52||11.29|
|Jack Sorenson||WR||2022||Miami OH||1.24||0.978||9.78||11.02|
|Brandon Bowling||WR||2022||Utah State||1.68||0.922||9.22||10.9|
|Danny Davis III||WR||2022||Wisconsin||2.38||0.835||8.35||10.73|
|JaCorey Sullivan||WR||2022||Central Michigan||2.3||0.83||8.3||10.6|
|Brandon Robinson||WR||2022||Florida Atlantic||2.1||0.805||8.05||10.15|
Not every elite NFL receiver had a great WRAPS score, of course. Jerry Jeudy didn’t put up great combine numbers, but scouts were, I think, correct in looking past that. WRAPS also occasionally struggles with “prototypical slot receivers” like Cooper Kupp or Hunter Renfrow, who thrive with a different brand of athleticism and often a different type of production. Kupp has obviously grown far past a simple slot player despite his 5 RAS, and there is something to be said for an athletic profile featuring extreme agility only. Scouting is still an extremely important part of picking any player and even more so with receivers, who can make up for many physical limitations through fluid movement, use of leverage, and body control.
All of that said, WRAPS still poses an important question to every scout. “If you weren’t productive in college, and you’re not that athletic compared to your peers, why should we like this you?” Sometimes there is a good answer to this question, especially if the receiver’s college quarterback was awful or the scheme they played in demanded non-efficient routes. But even within an awful offense, most truly good receivers will show some level of elite production. If WRAPS doesn’t like your guy, the burden shifts to the scout to explain why we should still like said player.
For this post I’ll be referring to the PFF big board as a proxy for scouting. You may have a different scout that you prefer, and that’s fine, but the PFF board is well known to all, accessible, and reflects mainstream views of the vast majority of players. On the chart below you can see a receiver’s spot on the big board contrasted with their WROPS/RAS/WRAPS, for additional context.
PFF Big Board, WROPS, RAS, WRAPS
|Calvin Austin III||87||0.861||9.05||17.66|
|Kevin Austin Jr.||157||0.957||9.94||19.51|
|Velus Jones Jr.||204||0.877||9.07||17.84|
|Johnny Johnson III||329||#N/A||5.42||#N/A|
|Michael Woods II||347||0.765||7.58||15.23|
Let’s get to it and talk about the most overrated receivers in this year’s draft.
1. Justyn Ross – Clemson
PFF Rank – 66th overall. WRAPS – 9.92
Of all players who qualified for a WROPS score and worked out at the combine or a pro day, Ross has the lowest WRAPS. No other player is in single digits, with Josh Johnson posting 11.91 for the 2nd worst number. Ross struggled at his pro day with, well, everything, recording a 2.56, though he was impacted by a foot injury at the time. Ross isn’t universally loved by every scout, but he’s on enough boards to warrant the overrated tag, and like every overrated player, Ross has his excuses.
He is thought to be much more athletic than his metrics show, and as a freshman with Trevor Lawrence at quarterback, dominated the competition. However, his production suffered as a sophomore (also with Trevor Lawrence) as his yards per reception crashed, and he missed his entire junior year due to spinal fusion surgery, which is itself not a great indicator of future success. His senior season simply wasn’t very good, and while the quarterback play at Clemson has been a mess post-Lawrence, it’s hard to shake just how similar his numbers were to that lackluster 2nd season.
If Ross falls, he may be worth a flyer to see if a better quarterback and another year to recover helps to rekindle that production, but there are too many red flags to warrant a high pick.
2. Jahan Dotson - Penn State
PFF Rank – 46th overall. WRAPS – 14.32
Dotson’s .803 WROPS ranks him 78th of 121 pass catchers (including TEs and RBs) with over 50 targets, and his splits (.374/.429/.803) are especially troubling. Dotson was a high volume pass catcher, and we often see players in his role struggle with a gaudy yards-per-catch number. Screens and inefficient short throws take their toll, much in the same way Davante Adams tends to excel in the volume-aided DYAR statistic while sometimes struggling with DVOA. But Dotson’s struggles are hardly limited to a lack of explosive plays, as his catch percentage is very poor for a guy seeing a large number of short and medium targets.
In Dotson’s defense, his quarterbacking was only average and he didn’t have much help, and he was much more of a downfield threat as a Junior, averaging 17 yards per reception. But the quarterback in question, Sean Clifford, worked in both seasons, putting up almost identical numbers. If Dotson was hurt by anything, it was the departure of tight end Pat Freiermuth, who attracted underneath coverage, allowing Dotson easier opportunities.
This leads to yet another Dotson problem, as he primarily played outside at Penn State, while his size and lack of physicality will push him to the slot in the NFL. There’s nothing wrong with a good slot receiver of course, but Dotson’s limitations are still limitations, and physical corners caused him plenty of problems at the collegiate level which will likely limit his versatility, and value.
Lastly, and most importantly, while Dotson was unquestionably a good college outside receiver, simply being small isn’t enough to turn you into a good slot receiver. While he was a burner at the combine, running a 4.43 40 with good splits, he didn’t tick the agility box, perhaps the premium statistical indicator for a good slot receiver. Combine all of this with merely average hands and an average overall RAS, and you have a receiver with too many red flags to be mocked in the second.
There is nothing Dotson won’t offer as a pro that you can’t get out of Nebraska’s Samori Toure, who is frequently mocked in the 6th or later.
3. Drake London - USC
PFF Rank – 11th overall. WROPS (not WRAPS) .832.
People like to talk about “scouts v. stats” all the time, when in reality the two almost always work in concert. Every baseball front office uses statistics to bucket prospects to some extent, and I suspect football teams do as well, but there are some things that are simply hard to quantify with numbers alone. Stats are extremely useful for prompting people to check their preconceived biases, and scouts are useful for seeing those skills that are difficult or impossible to put a number to.
99% of the time, my numbers tend to agree with what my scouting friends think of a guy. Every scout and every stat loved Ja’Marr Chase. But every so often I run into a player that I just do not get, and that my stats do not get. Usually, it’s a more middling prospect whom reasonable people can disagree over, but this year is a weird year, and it’s one of the consensus best receivers in the draft in USC’s Drake London. It’s worth noting immediately that London is injured. He is recovering from a fractured ankle, and having missed the combine, is set for a pro day on April 15th. Should he test well, he would immediately shoot up the WRAPS charts, and maybe that’s what will happen, but his WROPS, and in particular his .426/.406/.832 slash line, is a weird one, especially for a 6-4 receiver. That .406 WRSLG ranks 73rd out of 121 ranked players, and puts him in a tier filled with a good number of TEs and RBs, in addition to more slot-based wide receivers. London’s 12.3 yards per reception just isn’t very good, especially when put up against a player like Jameson Williams, who had an almost identical catch percentage on nearly the same number of targets while averaging 19.9 yards per catch.
London’s production looks much more like that of a slot receiver, and some have suggested that he may wind up playing some “big slot” at the next level, with the versatility to move outside as well. Scouts love his release off the line, and do project him as a good outside receiver, but I really wish he showed more production and physicality when lined up outside.
It’s not that London can’t use his considerable frame to body up a DB, and he is physical in a way, but it’s that far too often he just relied on boxing out smaller DBs, rather than using that release and his physical tools to create separation. He led the league with 19 contested catches last year (always a red flag for me), and that lack of separation also lead to drops on an additional 8 catchable balls. Take a look at some receivers from recent years with similar contested-catch rates and note the relative lack of success for these players so far at the NFL level.
1. JJ Arcega-Whiteside, 2017 (44%)— Scott Barrett (@ScottBarrettDFB) April 9, 2022
2. N'Keal Harry, 2018 (37%)
3. JJ Arcega-Whiteside, 2018 (35%)
4. Jalen Reagor, 2018 (32%)
5. DRAKE LONDON, 2021 (31%)
6. Denzel Mims, 2019 (31%)
Is this not just a list of the top Day 1-2 busts over this timeframe?
Scouts are quick to point out that London can in fact create separation, and that he excels at doing so early in routes, but there are clear splits between his slot work and outside work, and he struggles with this outside release against physical corners. London’s quarterback situation has been a bit of a soap opera with Jaxson Dart joining the fray this year, and Kedon Slovis exiting to Pitt, but it’s hard to have too many complaints about Slovis’ production. He was a well above average college quarterback, and every other receiver on this list has a much more significant gripe.
London was more explosive earlier in his career, and while he didn’t catch enough balls in his sophomore season to qualify for WROPS, his 15.2 yards per catch were the best of his career. That said, his freshman year was was quite similar to his sophomore year, and his .433/.480/.913 as a freshman still looks like the line of a glorified slot receiver.
It’s entirely possible that the scouts are correct about London, and I’m not. I’m happy to eat crow if that’s the case and I don’t wish failure on any prospect, but I just don’t see it and the numbers I do have back up that assertion. The last time I disagreed so vehemently with the consensus was on Jalen Reagor, whose atrocious .277/.469/.746 WROPS and 6.06 RAS didn’t mesh with the glowing scouting reports about him. The Eagles selected Reagor one pick before Justin Jefferson (.502/.464/.966, 9.69 RAS) and I suspect they still regret it. London’s production wasn’t as bad as Reagor’s, but I’m not sure how to justify selecting him over Jameson Williams, Chris Olave, Treylon Burks, or George Pickens. PFF has him 11th overall, and the first receiver off the board. That seems like a reach.
Honorable mention: David Bell - Purdue
PFF Rank – 110. WRAPS – 12.72
Bell is a controversial prospect, and much of what can be written about him has already been written about Big Ten peer Jahan Dotson. Pour one out for the big, slow, Big Ten archetype. Unlike Dotson, Bell’s rankings are more reasonable, and PFF’s 110 doesn’t strike me as egregious. That said, I’ve seen him mocked higher, and want to offer a word of caution.
Bell didn’t do himself any favors with his athletic testing, faring poorly in raw speed, explosiveness, and agility, but that wouldn’t matter so much if his production at Purdue had been better. You might be thinking that his production was fine as Bell is widely regarded to be one of the Big Ten’s best players, but when stacked up against his peers, a big problem emerges. Bell is, like Dotson and London, more of a .400/.400 player in WROPS. The difference with Bell is that his size and power are doing a lot of work after the catch, not his speed/agility. Per PFF charting, Bell was 3rd among receivers in broken tackles last season, which is fine in a vacuum, but broken tackles come with some baggage of their own. Bell was the key cog in Purdue’s fun, gimmicky offense, and often found himself in space, and able to make the most of the athletic gifts he does have. Unfortunately, the lack of athleticism in those testing numbers does show up on tape against better corners where he can struggle to gain separation. Moreover, except for a select few unicorns like Deebo Samuel (who is also shifty and fast, in addition to powerful), power advantages do not translate as well to the NFL (especially without good explosion testing) than speed and agility. Call it the “Ron Dayne Problem.” The much smaller Skyy Moore was almost identical in terms of production, but his agility and speed testing project much better at the next level.
Bell has his fans, and he was unquestionably a force at Purdue. The SIS NFL Draft Site has Bell as the best receiver in college football in terms of EPA per game, and it’s entirely possible that the forced volume to Bell killed his efficiency statistics. 110th also isn’t a particularly high ranking, but PFF has him ahead of superior choices Kevin Austin and Tyquan Thornton, while CBS has him ahead of Alec Pierce and Jalen Nailor. If Bell falls far enough, he’s a fine option, but there are likely to be better options throughout most the draft.