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The 2017 Phenom Index for Rookie Wide Receivers

The NFL Combine gets under way later this week, which means we’re officially in the thick of prospect season. As such, I’ve been invited back to write another edition of the Phenom Index, which has been posted at RotoViz every year since 2014.

What is the Phenom Index?

In the same way that #TeamRotoViz uses various metrics that contextualize a player’s performance,1 the Phenom Index is my way of incorporating a player’s age into their evaluation.

Why is this important? Consider that among the 2017 wide receiver class, the youngest prospect is 20.1 and the oldest is 25.3. Don’t you think five years — or even two years — is worth accounting for? Case in point, Eastern Washington receiver Cooper Kupp is two months OLDER than 2014 draftees Mike Evans and Allen Robinson. Yes, really.

To be clear, being an older prospect doesn’t mean you can’t be good, it just means the expectations are different; Keyshawn Johnson and Marvin Harrison are great examples of this.

Also, for everyone thinking “yea, but these guys are only going to be in the league for a few years. Who cares how old they are?” The point here has nothing to do with career longevity. The matter at hand is figuring out how talented a player actually is. A 20 year old dominating defensive backs who are 21 or 22 is much more impressive than a 23 or 24 year old doing the same.

The Phenom Index is calculated by looking at player’s age and their final season market share of receiving yards and bolting them together using z-scores. Typically, I like to think about this as a filter for finding young, talented players who could emerge to be among the game’s best within three seasons. There’s no magic threshold for being an NFL success, but the average Phenom score of the top 12 fantasy receivers in the NFL last year was 1.98. Two years ago the average was 2.47. It’s incredibly rare for a player to have a score below zero and turn into a premier fantasy option. Here is a look at how the Phenom Index related to 2016’s top fantasy receivers, with the 2015 stats in parenthesis.

  • Lowest PI score in cohort of top 12 receivers: 0.27 Michael Thomas2 (0.31 – Doug Baldwin)
  • Median PI score in cohort of top 12 receivers: 1.95 (2.20)
  • Average PI score in cohort of top 12 receivers: 1.98 (2.47)
  • Highest PI score in cohort of top 12 receivers: 3.98 – Amari Cooper (4.44 – Allen Robinson)

Phenom Index scores for 2017 wide receiver prospects

I’ve sorted the table to display the top 20 scores for the 2017 class, but there are nearly 130 total scores included below for you to explore. Also, because combine invites seem to matter, I’ve indicated that. If you want to check out historical scores, there were nearly 800 published in the 2015 edition of this article and 130+ in the 2016 edition. 3

WRDraftCollegeCombine?msYDSMSyd ZAgeAge ZPHENOM
Curtis Samuel2017Ohio StateYES31.10.57620.4-2.3382.914
JuJu Smith-Schuster2017USCYES25.40.04820.1-2.6492.697
Jerome Lane2017AkronYES33.20.7720.8-1.872.64
Zay Jones2017East CarolinaYES43.51.72421.8-0.8292.553
Josh Malone2017TennesseeYES31.40.60320.8-1.9072.511
Noel Thomas, Jr.2017ConnecticutYES48.72.20522.3-0.2352.44
KD Cannon2017BaylorYES350.93721.2-1.4882.425
Jalen Robinette2017Air ForceYES55.42.82622.90.4212.405
Isaiah Ford2017Virginia TechYES30.50.5220.9-1.7782.298
Krishawn Hogan2017MarianYES39.11.3221.6-0.9562.276
Corey Davis2017W. MichiganYES42.51.63122-0.5832.214
John Ross2017WashingtonYES31.70.63121.1-1.5562.187
Chris Godwin2017Penn StateYES28.10.29820.8-1.8332.131
Tanner Gentry2017Wyoming41.31.5222-0.5122.032
Drew Wolitarsky2017Minnesota38.11.22421.8-0.8022.025
Ishmael Zamora2017Baylor28.60.34421.1-1.5531.897
Karel Hamilton2017Samford36.31.05321.8-0.8291.883
Taywan Taylor2017W. KentuckyYES36.71.09421.8-0.741.834
Fred Ross2017Mississippi StateYES340.84421.6-0.9771.821
Lance Lenoir2017Western Illinois36.91.11521.9-0.6691.784
Keevan Lucas2017TulsaYES34.20.86321.7-0.8571.72
Malachi Dupre2017LSUYES27.50.24221.2-1.4181.66
Robert Davis2017Georgia StateYES32.80.73321.7-0.8331.565
Chad Hansen2017CaliforniaYES34.20.86322-0.6051.467
Travis Rudolph2017Florida StateYES24.5-0.03621.3-1.3341.299
Josh Reynolds2017Texas A&MYES31.30.59421.9-0.6911.285
Michael Clark2017Marshall22.9-0.18421.2-1.4611.277
Tony Stevens2017Auburn29.80.45521.8-0.7771.232
Anthony Warrum2017Illinois State37.61.17622.5-0.0261.202
Thomas Sperbeck2017Boise State33.60.80722.2-0.3341.141
Matt VandeBerg2017Iowa361.02922.4-0.091.12
Carlos Henderson2017Louisiana TechYES31.40.60322-0.5151.119
Zach Pascal2017Old DominionYES31.10.57622-0.5121.088
Torii Hunter Jr.2017Notre Dame24.5-0.03621.6-1.0330.997
Kenny Golladay2017Northern IllinoisYES431.67823.20.7350.943
Victor Bolden Jr.2017Oregon StateYES260.10321.7-0.8390.942
Isaiah McKenzie2017GeorgiaYES25.20.02921.7-0.8540.883
Jonnu Smith2017Florida International20.2-0.43421.4-1.2640.83
Kendrick Bourne2017Eastern WashingtonYES20.6-0.39621.4-1.2080.812
Trent Taylor2017Louisiana TechYES35.40.97422.70.1870.787
Ryan Switzer2017North CarolinaYES29.20.422.2-0.3770.776
Noah Brown2017Ohio StateYES14.9-0.92521-1.6760.752
Austin Carr2017Northwestern39.11.316230.5750.741
DeAngelo Yancey2017Purdue26.90.18722.1-0.420.606
Amba Etta-Tawo2017SyracuseYES38.41.25223.10.7130.538
Rodney Adams2017South FloridaYES27.90.27922.3-0.2260.505
Mike Williams2017ClemsonYES27.20.21422.2-0.2840.499
Aaron Peck2017Fresno State26.80.17722.2-0.30.477
Daikiel Shorts Jr.2017West Virginia26.70.16822.2-0.2910.459
Dede Westbrook2017OklahomaYES36.91.11323.10.680.433
Speedy Noil2017Texas A&MYES14-1.00821.2-1.4240.416
ArDarius Stewart2017AlabamaYES35.30.96423.10.6270.337
Domonique Young2017Purdue24.6-0.02622.2-0.3550.329
Dameon Gamblin2017New Mexico20-0.45221.8-0.780.328
R.J. Shelton2017Michigan State30.20.49222.70.1710.321
Jimmy Williams2017East Carolina20.4-0.41521.9-0.7150.3
Bug Howard2017North CarolinaYES22.9-0.18422.1-0.4510.267
Andre Patton2017Rutgers28.50.33522.60.1040.231
Jesus Wilson2017Florida StateYES20.5-0.40621.9-0.6260.22
Robert Wheelwright2017Wisconsin21.6-0.30422-0.50.196
Drew Morgan2017ArkansasYES21.5-0.31422.1-0.4630.149
Cory Butler-Byrd2017Utah22.1-0.25822.1-0.4010.143
KeVonn Mabon2017Ball State35.30.96423.20.830.134
Amara Darboh2017MichiganYES31.30.59422.90.4640.13
James Quick2017LouisvilleYES22.5-0.22122.2-0.2910.07
Jordan Westerkamp2017Nebraska25.80.08522.50.0270.058
Sebastian Smith2017Ohio30.30.50122.90.4610.041
Keon Hatcher2017ArkansasYES23-0.17522.3-0.2140.039
Shelton Gibson2017West VirginiaYES28.40.32522.80.3130.012
Deon Watson2017Idaho23.6-0.11922.4-0.069-0.05
Gerald Everett2017South Alabama24.5-0.03622.50.021-0.056
Austin Duke2017Charlotte34.70.90923.41.012-0.103
Tim Patrick2017Utah30.20.49223.10.673-0.181
Quincy Adeboyejo2017MississippiYES12.1-1.18421.6-0.999-0.185
Al Riles2017Louisiana-Lafayette32.10.66823.30.877-0.209
Damore'ea Stringfellow2017Mississippi18.9-0.55422.2-0.327-0.227
Deante Burton2017Kansas State21.8-0.28622.5-0.032-0.254
Aregeros Turner2017Northern Illinois15.4-0.87822-0.58-0.298
Josh Knight2017Marshall23.9-0.09122.70.218-0.309
Ricky Seals-Jones2017Texas A&MYES12.8-1.11921.8-0.78-0.339
Jamari Staples2017LouisvilleYES18.8-0.56422.3-0.21-0.353
Billy Brown2017ShepherdYES36.11.03923.81.422-0.383
Tim Crawley2017San Jose State24.3-0.05422.80.341-0.395
Cooper Kupp2017Eastern WashingtonYES33.10.75923.51.16-0.401
Josh Atkinson2017Tulsa30.70.53823.40.963-0.424
Gabe Marks2017Washington StateYES19-0.54522.4-0.106-0.439
Dontre Wilson2017Ohio State13.7-1.03622-0.558-0.477
Michael Henry2017Western Michigan22-0.26722.70.211-0.479
Stacy Coley2017Miami (Florida)YES21.2-0.34122.60.15-0.491
Ricky Jones2017Indiana23.8-0.10122.90.486-0.586
BJ Johnson III2017Georgia Southern34.60.923.91.508-0.608
Jordan Reid2017Ohio20.8-0.37822.90.409-0.787
Anthony Nash2017Duke25.20.02923.30.867-0.838
Riley McCarron2017Iowa28.30.31623.51.157-0.841
Artavis Scott2017ClemsonYES12.3-1.16522.2-0.309-0.856
Trey Griffey2017Arizona20.1-0.443230.501-0.944
Scott Orndoff2017Pittsburgh21.1-0.351230.603-0.953
Deon-Tay McManus2017Marshall18.4-0.60122.90.418-1.018
Michael Rector2017StanfordYES19.8-0.471230.603-1.074
Montay Crockett2017Georgia Southern19.8-0.47123.10.618-1.089
Jake Maulhardt2017Wyoming20.2-0.43423.10.67-1.104
Zach Wright2017Rice20.7-0.38823.20.8-1.187
Jehu Chesson2017MichiganYES18.1-0.628230.563-1.191
Travin Dural2017LSUYES18.2-0.61923.10.686-1.305
Brandon Reilly2017Nebraska19.7-0.4823.30.855-1.335
Darreus Rogers2017USCYES19.4-0.50823.30.92-1.428
Chris Lewis2017South Alabama20.8-0.37823.51.086-1.464
Greg Ward Jr.2017HoustonYES-3.6-2.63821.5-1.14-1.497
Jhajuan Seales2017Oklahoma State15.4-0.87823.10.664-1.543
Shaq Hill2017Eastern Washington20.6-0.39623.71.292-1.688
Mack Hollins2017North CarolinaYES14.7-0.94323.30.88-1.823
Corey Jones2017Toledo19.5-0.49923.91.502-2.001
Alonzo Moore2017Nebraska22.6-0.21224.11.822-2.034
Kermit Whitfield2017Florida StateYES11.5-1.2423.20.812-2.052
Rokeem Williams2017Miami (Ohio)22.8-0.19324.21.878-2.071
Ishmael Adams2017UCLA5.7-1.77722.90.495-2.271
Jordan Frysinger2017Idaho20.2-0.43424.31.967-2.401
Josh Magee2017South Alabama300.47425.33.051-2.577
Cole Freytag2017UTEP23.6-0.119252.771-2.89
Gehrig Dieter2017Alabama7.4-1.61923.91.502-3.121


There’s a lot of meat to pull of this bone, but I’ll offer a few quick thoughts here. Hopefully some of the other writers can link back on follow up pieces.

Intriguing scores

Curtis Samuel, Ohio State – The highest Phenom Index score of the 2017 class goes to a guy who also managed 700 rushing yards in his final season. The last player to surpass 700 receiving and 700 rushing in a season was Percy Harvin in 2007.4 As you may remember, Samuel and Harvin both played under Urban Meyer, who has an excellent track record of putting skill position players into the NFL. The other thing to like about Samuel is that he’s got some special teams experience. Overall, he looks like a fantastic multi-faceted threat for today’s NFL.

Krishawn Hogan, Marian – I’d never heard of Hogan until I looked at the NFL combine invite list, but I instantly became fascinated after digging deeper. Listed at 6 feet 4 inches tall and 215 pounds, Hogan amassed 42 receiving touchdowns in three years and 25 RUSHING touchdowns. Get to know him better on this episode of RotoViz Radio.

Corey Davis, Western Michigan – Like a mad scientist muttering to himself in his lab, I penned my Corey Davis love letter in 2014 before the vast majority had a reason to care. Corey Davis has been destined for greatness for some time now. Had he declared for last year’s draft, he would have had the third-highest score, but instead comes in No. 11 in this class. Either way, I am sky high on what he could become.

Disappointing scores

Cooper Kupp, Eastern Washington – In a vacuum, Cooper Kupp’s score looks terrible, especially for someone that could be selected on Day 2. That said, even though Kupp was 23 in his final college season, he’s kicked ass since his age 20 freshman season, and he has some serious special teams juju. This methodology hates Kupp’s chances for NFL success, but I’m taking a wait-and-see approach.

Dede Westbrook, Oklahoma – Westbrook had a remarkable season in 2016 to be sure, but for someone who is going to be a 24-year-old rookie who weighs around 170 pounds, he better be exceptionally athletic. Otherwise, I’d be scared of spending a Day 2 pick on him when there are a number of other cheaper, bigger, more promising prospects available.

Mike Williams, Clemson – Like Kupp, Williams is another player who requires some deeper inquiry. In a vacuum his 2016 score looks underwhelming for someone who could be the first receiver taken. However, if you go back to his 2014 campaign at age 20((he played in one game in 2015 before suffering a neck injury)0, you’ll see a 20 year old who accounted for 33 percent of Clemson’s receiving yards, which would translate to one of the best Phenom scores in this class. Shawn Siegele has written before about how breakout season might be more important than final season, which may be the case with Williams.

In closing, I know it might seem like I’m contradicting myself with some of the comments in the Disappointing section, but probably the most important thing to remember about the Phenom Index is that it’s far from a silver bullet. It’s merely a value screen that will guide you to outstanding young talent. However, it’s important in cases like Kupp and Williams to remember that even “old, underwhelming talent” might have once been young and outstanding too. Ultimately, much more work is required on all of these players and I encourage you to reach your own conclusions.

Jon Moore was a long-time contributor at RotoViz before going to work for PFF in July of 2016. Feel free to reach out to him on Twitter.

  1. i.e. market share, which adjusts for quality of offense  (back)
  2. Michael Thomas’ birth year has been a point of contention for many people for a long time — Mike himself even responded to me then quickly deleted it — but this number is based on the birth year provided by and this score reflects a different number than what appears in last year’s article since I mistakenly updated it to reflect his false 1994 birth year.  (back)
  3. with every passing year, a player’s score is liable to change ever so slightly. This is because I update the averages and standard deviations used to create z-scores with the addition of every new draft class  (back)
  4. Per Sports Reference.  (back)

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