The 2019 Prospect Success Indicator Report

Update:
  1. Removed Juston Christian due to being released by the Ravens shortly after signing as a UDFA. Only added him as the only non-combine invite assuming he’d be drafted/sign UDFA. 
  2. Also, minor updates to percentile rankings +/- 1%

Welcome to the third annual Prospect Success Indicator report. Normally this is the part where I give you a rundown of the top 12 wide receivers prospects in this year’s class. However, I decided to switch it up this year because I now have ample enough data from 2010-2018 that I feel it is best if we look at the class in a more holistic view (see table below).

PSI is a model designed to help narrow the draft field – to learn more about the specifics of the PSI model click here – and increase your odds of hitting on a wide receiver. With that in mind, of the 51 wide receivers I have in this year’s class, 23* of them scored in the 50th percentile or better.

Looking at the table below we learn that from 2010-2018 of all wide receivers who have produced the top 24 seasons 91% have come from wide receivers who scored in the top 50% of the model.Capture
The other 28 are immediately eliminated from the fantasy draft board. So while your league mates are playing with a 1/51 chance of hitting you have already taken steps to double your odds with a 1/23 chance entering your rookie draft.

So now that we have narrowed down the top wide receivers, with the best odds to give us a return on our investment, let’s begin with the top 50th percentile group of receivers.

  • Hakeem Butler – PSI Score – 4.39 – 49th Percentile
    •  *Hakeem has fallen outside the top 50th percentile after a model update
    • Player Comp: Kenny Golladay – 2017 3rd round pick
    • Not Top 10, why?
      • Breakout Age: 21.3 – of all the top 24 wide receivers since 2010 only 6 have had a breakout age of 21 or greater, and only 2 have gone on to repeat.
      • Butler broke out as a sophomore, but he didn’t burst onto the scene until this year when Allen Lazard (UDFA) left school for the NFL. This is a HUGE piece of contextual info that isn’t talked about enough. We ding Riley Ridley for not beating out late-round receivers at Georgia, so why do we give Butler a pass? 
  • Antoine Wesley: PSI Score – 4.47 – 50th Percentile
  • David Sills: PSI Score – 4.52
  • Cody Thompson: PSI Score – 4.52
  • Keelan Doss: PSI Score – 4.62
  • Stanley Morgan: PSI Score – 4.64
  • Miles Boykin: PSI Score – 4.64
  • J.J. Arcega-Whiteside: PSI Score – 4.75 – 60th Percentile
    • Player Comp: Mike Williams – 2010 4th round pick
    • Not Top 10, why?
      • Missing data. He didn’t participate in agility drills or bench press. If he had done them and succeed he would’ve scored as the #5 wide receiver in this class in the PSI What-If Rankings (so keep that in mind) but still outside the top 90th percentile.
      • Context: Arcega-Whiteside never had a one thousand yard season in college and most of his production was heavily weighted in touchdowns. This is not the ideal profile you typically see from a future elite WR1 entering the NFL.
  • Greg Dortch: PSI Score – 4.97
    • Player Comp: Ace Sanders – 2013 4th round pick
    • Not Top 10, why?
      • Missing data. Just like Arcega-Whiteside, if he had participated in the Vert, Broad, and Bench and succeeded in them then the PSI What-if Rankings would put him as the #4 wide receiver in this class.
      • Context: Dortch is the shortest wide receiver in this class, is too light for his height (injury concern), and has small hands. The number of successful wide receivers, as defined by PSI, with similar concerns and go on to be successful? Zero. Even with all that being said, you can’t deny his age-adjusted production.
  • D.K. Metcalf: PSI Score – 4.99
    • Player Comp: Josh Gordon – 2012 2nd round pick
    • Not Top 10, why?
      • Low Dominator Rating of only 20% is the biggest factor here. He also tested poorly in agility drills, but that’s far less concerning. If you were scared off by his poor agility drills, you shouldn’t be.
      • Context: Metcalf missed a lot of games in college due to injury. Even when he was on the field he wasn’t the true alpha dog wide receiver for his team every game. In total Metcalf played in 21 games. I did research this off-season that showed if he does become a top 24 wide receiver he would do it having played in the fewest amount of college games entering the NFL with 21. 30-40 games played was the sweet spot for elite talent. Finally, he also over-indexed in touchdown production over yards, just like Arcega-Whiteside. Touchdown production is not a predictive stat, yards however are.
  • Jamarius Way: PSI Score – 5.01
  • Kelvin Harmon: PSI Score – 5.14 
    • Player Comp: Juron Criner – 2012 5th round pick
    • Not Top 10, why?
      • Entering the NFL at age 22 and breaking out at 20.8 is just average, not elite. He also showcased that he is not fast (4.60 40 time), not explosive (117-inch broad jump), and not agile either (7.15 3 Cone).
      • Context: Harmon’s athletic traits lend us to believe that he will be limited in what he can do in the NFL and that the most likely role for him is as a slot wide receiver rather than a wide receiver who can play all three roles. He also tested athletically very closely to Laquon Treadwell who also has been used more as a slot wide receiver than outside wide receiver and has struggled to find success at the NFL level.
  • Diontae Johnson: PSI Score – 5.33 – 70th Percentile
  • Penny Hart: PSI Score – 5.38
  • Felton Davis: PSI Score – 5.49
  • Lil’Jordan Humphrey: PSI Score – 5.87
  • KeeSean Johnson: PSI Score – 5.89
  • Dillon Mitchell: PSI Score – 6.00
  • Emmanuel Butler: PSI Score – 6.01 – 80th Percentile
  • Andy Isabella: PSI Score – 6.01
  • A.J. Brown: PSI Score – 6.12
  • N’Keal Harry: PSI Score – 6.87 – 90th percentile 
    • Player Comp: Dez Bryant – 2010 1st round pick
    • Not #1, why?
      • N’Keal Harry takes the runner up this year in the model but that is only due to the fact that his shuttle time was never released to the public. If it was a good time, and there is a very good reason to believe it most likely was, then he would come in tied for #1 spot with a perfect score of 7.00. Either way, Harry registers in the 90th percentile which places him with the most successful group in the PSI model. Harry is the wide receiver with the best odds at long term value and the safest choice for the number one rookie wide receiver.
      • Context: Harry is my number one wide receiver in this class and it’s not close. He will carry high draft capital to go along with his great college production and elite athleticism.
  • Ashton Dulin: PSI Score – 7.00
    • Player Comp: Justin Watson – 2017 5th round pick
    • #1, why?
      • Ashton Dulin was the only wide receiver to register a perfect score in this class. He had the best Dominator Rating in the class with 61-percent, he also had the youngest Breakout Age with 18.3, and finally, he checked every single athletic measurable box you could ask.
      • Context: While all the advanced metrics love Ashton Dulin there are a couple things we cannot ignore. First, he played for the smallest school I’ve ever heard of at Malone University and second, he’s also likely to go undrafted. If he gets drafted it will be no earlier than the fifth round. I would love to see a team invest some draft capital on him and hope it happens for him.

I have to say I am not enamored with this wide receiver class one bit. Most years one small school wide receiver gets near the top, this is the first time that the model not only has three, but one of them is the consensus number one wide receiver in the model. Also, most fantasy football consensus rankings have guys in the top five that just aren’t likely to be elite talents. This spells bad news for this class as a whole as it feels we are looking at a hybrid of the 2012/2013 class all over again. Except for this time Harry is DeAndre Hopkins, Metcalf is Josh Gordon, Emmanuel Butler is Keenan Allen, KeeSean Johnson is Robert Woods, Dulin is Adam Thielen and everyone else falls by the wayside. To me that would be best-case scenario and, I’m not sure it’ll even be that good when it is all said and done.

If I have a top-three pick in dynasty rookie drafts, I’m either hoping to land Harry or looking to trade out of that pick immediately. This is the class where landing spot will matter more to me than draft capital. For example, if Metcalf goes in the first round to Baltimore and Arcega-Whiteside goes in the third to Seattle, I will gladly use a second-round rookie pick on Arcega-Whiteside and trade away my first-round pick rather than using my first-round pick on Metcalf

One last thing, if you are one of those fantasy owners who care about the remaining nine percent hit rate group, that produces an outlier wide receiver just about every year, then this is for you. Those wide receivers tend to be highly productive in college but with a late breakout age and/or are extremely athletic. Here is the list of guys who fit that bill for 2019 to keep an eye on.

  • The Highly Productive Late Breakout Group
    • Anthony Johnson: PSI Score 4.06 – 43rd Percentile
    • Preston Williams: PSI Score 3.60 – 38th Percentile
    • Travis Fulgham: PSI Score 3.18 – 31st Percentile
    • Jazz Ferguson: PSI Score 3.12 – 29th Percentile
  • The Elite Athleticism Group
    • *Darius Slayton: PSI Score – 4.37 – 49th Percentile
    • Parris Campbell: PSI Score – 4.24 – 46th Percentile
    • Gary Jennings: PSI Score – 4.24 – 46th Percentile
    • Emanuel Hall: PSI Score – 3.24 – 32nd Percentile
    • Terry McLaurin: PSI Score – 1.68 – 11th Percentile

 

9 thoughts on “The 2019 Prospect Success Indicator Report

  1. Hey Always love your work. Just a note that the link that explains PSI seems to be dead. I preferred previous editions with the good and bad but the percentiles are pretty cool, I wonder if you have easy access to the previous year data based on your new metrics. I wonder if you’re still using the phenom index as part of your evaluation.

    Thanks for your work!

    Like

    1. Yeah an updated database will be uploaded shortly. Phenom index is no longer part of the equation but everything that goes into the phenom index is accounted for just separately so it felt like double counting by adding it back in.

      Like

  2. Hey, I love the work you put into these.
    Quick note, the link that explains the PSI seems to be dead.
    I liked the good and bad format of previous years but can appreciate the percentile approach. Do you have the data for previous years like your previous PSI?
    Does this one still incorporate the phenom index?
    Let me know, keep up the good work, and welcome to the Justin Watson breakout party.

    Like

    1. Hey appreciate it, phenom index is no lo get included but that’s because what goes into phenom index was already being accounted for so it felt a bit like double counting. Took it out and model still held up.

      Like

  3. Thank you for publishing this report.

    Could you provide more details on Deebo Samuel? Looks like he’s shaping up to be a 1st rd dynasty rookie pick, but only has a 39% PSI.

    Thanks!

    Like

    1. Very athletic but every thing else is just average to below average for his profile. Definitely a candidate to be over drafted this year. Looking back at Senior Bowl rosters about 1 WR ends up making a significant contribution in the NFL, if I’m betting on one then give me Andy Isabella. Deebo feels like his ceiling is Sterling Shephard and that’s not something I’m interested in personally.

      Like

    1. This analysis is based soley on college production, athleticism and age so as far as this goes I would not since landing spot isn’t a factor. But in conjunction with this, yes I would. Simply because there aren’t that many prolific offenses and IND is one of those. Still not someone I like long term but someone I’d look to flip if he produces.

      Like

      1. Is there an amount of years that’s fair to say a player isn’t going to breakout if they haven’t already? Moncrief and Parker two that stand out here. Thanks for putting this together by the way, very interesting sorting through the data.

        Like

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