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Wide Receiver Class Statistical Projections

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I've been working on some college-to-pro statistical projection models around draft season, starting with quarterbacks, non-rush linebackers, and now wide receivers. These haven't gotten much traffic, but I think their results are interesting. I decided to try my hand at wide receivers this time around because of the supposed statistical unreliability of college receivers going pro, and it came out okay.

Things of note about the model:

  • The projection is in terms of average Approximate Value in Years 3-4. Approximate Value (AV) is ProFootballReference's sort-of-all-in-one stat that you can see explained here: https://www.pro-football-reference.com/blog/index37a8.html
  • The model also projects a % chance that the player reaches the "Bust" and "Pro Bowl" thresholds, which I have loosely defined as <5.0 AV and 10.0 AV respectively.
  • The model is built on data from, and built for, only players drafted in Rounds 1-3 because of the even greater statistical unreliability of Day 3 draft picks (and their low likelihood of success).
  • The WR model is built only on college statistics, draft position, and height and weight. No combine measurements were significant enough to warrant inclusion.
  • The correlation coefficient between projected AV and real AV in the model is 0.45. This might not seem significant, but it's a step in the right direction from NFL scouting (draft position is correlated to AV at -0.31, showing that loosely the higher-drafted WRs perform better).

The model was built based on data from 2006 to 2015 (the last year where players have reached Year 4) and has had decent results compared to reality:

Probabilities of Hitting Thresholds (2006-2015)
Projection: >5.00 AV
Threshold Reality Projected Avg.
Pro Bowl 26.32% 16.05%
Hit 78.95% 71.42%
Bust 21.05% 28.58%
Projection: <5.00 AV
Threshold Reality Projected Avg.
Pro Bowl 4.90% 6.82%
Hit 33.33% 34.73%
Bust 66.67% 65.27%

Without further ado, the 2019 class rankings, with a bit of a surprise in first (and last) place:

1. ANDY ISABELLA, MASSACHUSETTS

A. Isabella, WR, Massachusetts
Statistic Figure
Projected AV 5.33
Bust Chance 32.43%
PB Chance 15.08%

My model is a fan of the little guy this year. Isabella's projection, if put in the 2006-2015 data set, would edge out Jordan Matthews' projection for 10th-best. Being projected above the 5.0 bust threshold is in itself an achievement - less than 16% of WRs drafted in Rounds 1-3 from 2006-2015 hit a projection of 5.0 or greater. For those wondering, no, Isabella's projection isn't helped by his crazy 4.32 speed - no combine events were deemed significant enough to warrant including in the model. What Isabella did to have such a high projection was score very highly in both efficiency-based statistics, like receptions per team attempt, and volume statistics, like receiving yards. Including both leaves Isabella with a high projection as he heads to Kliff Kingsbury's Air Raid with Kyler Murray.

2. MARQUISE BROWN, OKLAHOMA

M. Brown, WR, Oklahoma
Statistic Figure
Projected AV 4.85
Bust Chance 42.60%
PB Chance 12.52%

Brown may not have hit the 5.0 AV threshold, but he's still projected to be a hit in the majority of cases (57.40%). Brown was helped by good efficiency and volume statistics and the highest draft position in the class, but not by a body type that hasn't proven as successful in the pros (5'9", 166 lbs). Still, taking the "gamble" on Brown might be worthwhile for the Ravens if he can hit like his % projection suggests. Brown's projection is sandwiched between that of Kevin White and Jeremy Maclin, so it could go either way. Still, Brown's projection is above that of big names like Odell Beckham Jr. and Julio Jones.

3. J.J. ARCEGA-WHITESIDE, STANFORD

J.J. Arcega-Whiteside, Stanford
Statistic Figure
Projected AV 4.44
Bust Chance 51.30%
PB Chance 10.33%

The Eagles' new wideout ties Mike Sims-Walker and Paul Richardson with a 4.44 projection, but barely misses the 50% hit mark. Arcega-Whiteside's statistics weren't mind-boggling, but his 14 touchdowns in his final year helped to raise his projection. On the (rightfully) conservative side with his Pro Bowl projections, the model gives Arcega-Whiteside just a 10% chance to be a Pro Bowl-threshold player. 

4. N'KEAL HARRY, ARIZONA STATE

N. Harry, WR, Arizona State
Statistic Figure
Projected AV 4.43
Bust Chance 51.51%
PB Chance 10.28%

Jim Cobern of CommonManFootball analytics on YouTube ranked Harry as the top receiver in this year's class. My model isn't as high on Harry, but it still gives him a good coin-flip chance of success. If he hits with the Patriots, it doesn't mean anything good for the rest of the NFL. Harry's projection is just below Arcega-Whiteside's, though he did reel in 10 more receptions for a team that threw the ball less than Stanford. Harry put up numbers throughout his career at ASU, and the model gives him a 48.49% chance to keep doing so as a New England Patriot.

5. PARRIS CAMPBELL, OHIO STATE

P. Campbell, WR, Ohio State
Statistic Figure
Projected AV 4.26
Bust Chance 55.11%
PB Chance 9.37%

Ohio State's speedster is the top-ranked wideout in this class to fall under the 10% Pro Bowl chance threshold. The new Colt built a reputation for himself with his speed, but he produced solid volume stats at OSU. Campbell's 90 catches in 2018 ranked second in the rankings to the aforementioned Isabella. Campbell was solid overall, but not special in many regards.

6. A.J. BROWN, OLE MISS

A.J. Brown, WR, Ole Miss
Statistic Figure
Projected AV 4.11
Bust Chance 58.29%
PB Chance 8.57%

Metcalf may have received all the pre-draft buzz, but it was Brown who was off the board first, and rightfully so, per the model. With Metcalf out much of the year, Brown was the real target-hog for the Rebels' offense, catching 85 balls. Brown's 6-2, 226 frame is also relatively ideal for the NFL. Brown's efficiency stats, however, were unremarkable, and they, along with his just 6 touchdown receptions in 2018, dragged down his projection. Brandon LaFell (4.14) and Robert Woods (4.09) are the two closest to Brown's projection.

7. DEEBO SAMUEL, SOUTH CAROLINA

D. Samuel, WR, South Carolina
Statistic Figure
Projected AV 4.02
Bust Chance 60.20%
PB Chance 8.09%

Drafted third among wideouts by San Francisco, Samuel had unremarkable overall statistics at South Carolina that led to a mediocre projection. Steve Smith (the Giants one) is the only other WR to ever notch a 4.02, though Smith recorded better volume statistics. As the middleman of the class rankings, Samuel's 4.02 is just below the average of the 2006-2015 sample (4.05).

8. MILES BOYKIN, NOTRE DAME

M. Boykin, WR, Notre Dame
Statistic Figure
Projected AV 3.49
Bust Chance 71.44%
PB Chance 5.26%

Boykin, the lowest-drafted of the rankings, kicks off the lower group of players, not even hitting 3.50 AV. Boykin's statistics were nothing special at all, hitting just 872 yards for a decently pass-heavy Notre Dame team. Jaguars (arguably) WR1 Marqise Lee hit 3.47 a few years ago, the closest to Boykin's projection. Boykin was a workout warrior, consistently testing in the 80th percentile and above (https://www.mockdraftable.com/player/miles-boykin), but unfortunately for him, my model is unimpressed with the Underwear Olympics.

9. DIONTAE JOHNSON, TOLEDO

D. Johnson, WR, Toledo
Statistic Figure
Projected AV 3.40
Bust Chance 73.35%
PB Chance 4.78%

Johnson heads to the Steelers in an effort to usurp James Washington as the team's No. 2 behind JuJu Smith-Schuster. Johnson's 49 receptions for 761 yards and 8 touchdowns is a little low for what the model wants to see, as is Johnson's 183-pound frame. With a Pro Bowl chance below 5%, the Steelers might not have found a diamond in the rough, but they could have found a contributor. Time will tell for Johnson, whose 3.40 barely edges out DeSean Jackson's 3.38. 

10. JALEN HURD, BAYLOR

J. Hurd, WR, Baylor
Statistic Figure
Projected AV 3.28
Bust Chance 75.89%
PB Chance 4.14%

Hurd's career arc has been an intriguing one, as he went from splitting carries with Alvin Kamara at Tennessee to being Baylor's No. 1 receiver. If my model is to be believed, Hurd's journey could end quickly in the NFL. His below-25% chance of success isn't a great one, and he only compiled okay statistics (4 touchdowns, etc.) for a Baylor team that threw the ball over 37 times per game. The one saving grace for Hurd could be that he's still getting there: as a player just shifting positions now, Hurd might have room to grow into something for the 49ers, who doubled up on wideouts early.

11. MECOLE HARDMAN, GEORGIA

M. Hardman, WR, Georgia
Statistic Figure
Projected AV 3.15
Bust Chance 78.65%
PB Chance 3.45%

Hardman might not have been looked at as a top-tier wideout prospect, but the Chiefs saw enough to trade up for him to presumably replace Tyreek Hill. Hardman only caught 35 balls in his last year at Georgia, and only compiled 543 yards, neither of which on its own projects to above 3.0 Approximate Value. Georgia didn't throw as much as other CFB teams (only 25.5 attempts per game), but Hardman still didn't impress from an efficiency and market share perspective. Overall, it might be a surprise to see Hardman adequately replace Hill. On the other hand, with Patrick Mahomes manning the Chiefs, I wouldn't be too quick to count him out.

12. TERRY MCLAURIN, OHIO STATE

T. McLaurin, WR, Ohio State
Statistic Figure
Projected AV 3.02
Bust Chance 81.40%
PB Chance 2.75%

After gaining a bit of steam as potential Round 1 guy late in the process due to a good combine, McLaurin fell to the third round, where he was scooped up by a Washington team that drafted his quarterback, Dwayne Haskins. Again, my model ignores McLaurin's combine performance for the event's statistical unreliability, but it does acknowledge his college performance. McLaurin scored 11 times in his last season, on almost a third of his catches. However, his projection suffers greatly from poor efficiency statistics - McLaurin hit just 35 receptions for 701 yards on an Ohio State squad that threw the ball forty times per game. The result spells a bad projection for Terry.

13. D.K. METCALF, OLE MISS

D.K. Metcalf, WR, Ole Miss
Statistic Figure
Projected AV 2.45
Bust Chance 93.49%
PB Chance <1.00%

No, I didn't forget about Metcalf. Count the model firmly not among his supporters. Make no mistake, 2.45 AV is a terrible projection. It's "good" for 10th-worst against the data set from 2006 to 2015. Now, there are things to acknowledge with Metcalf, and a Pro Bowl chance that low is incredibly conservative for this athletic freak. However, there is concern about Metcalf's neck injury, and it limited his statistics. As a result of his injury, DeKaylin only caught 26 balls all of the 2018 season. It might not be his fault, but it's certainly troubling. Compounding that with a team that threw the ball quite a bit (much of it to A.J. Brown), and you have a bad projection. However, if any team can unlock that 6% hit chance for Metcalf, it might be the Seahawks. They certainly have a good deep ball game that will only get better with D.K., as Brett Kollman breaks down here: 

I'd highly recommend it. It's worth a watch if you have the time.

TL;DR -

2019 Wide Receiver Class Projections
Name Projected AV Bust Chance PB Chance
A. Isabella 5.33 32.43% 15.08%
M. Brown 4.85 42.60% 12.52%
J.A. Whiteside
4.44 51.30% 10.33%
N. Harry 4.43 51.51% 10.28%
P. Campbell 4.26 55.11% 9.37%
A.J. Brown 4.11 58.29% 8.57%
D. Samuel 4.02 60.20% 8.09%
M. Boykin 3.49 71.44% 5.26%
D. Johnson 3.4 73.35% 4.78%
J. Hurd 3.28 75.89% 4.14%
M. Hardman 3.15 78.65% 3.45%
T. McLaurin 3.02 81.40% 2.75%
D.K. Metcalf 2.45 93.49% <1.00%

If you feel like taking a look at more similar statistical projections, check these out if you feel like it:

 

 

 

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Here's the historical data showing how the model has performed, comparing NFL results (AV) to projection (bust chance and Pro Bowl chance), and separated into risk-factor groups. Remember, "Bust" is defined as <5.0 AV, and "Pro Bowl" is defined as 10+ in this model. There's definitely a pretty decent track record here:

2006-2015 WR Model Results
GROUP: Moderate Risk I (Projected Bust Chance: <50%)
Results: 26.83% (11/41) Busts
Year Name College NFL AV Bust Chance PB Chance
2010 D. Bryant Oklahoma State 11.5 6.56% 21.58%
2010 D. Thomas Georgia Tech 13.5 6.77% 21.53%
2015 A. Cooper Alabama 4 8.04% 21.21%
2012 K. Wright Baylor 4 21.61% 17.80%
2013 S. Bailey West Virginia 0.5 22.67% 17.53%
2007 C. Johnson Georgia Tech 8.5 24.79% 17.00%
2014 D. Adams Fresno State 9 25.85% 16.73%
2012 J. Blackmon Oklahoma State 0 29.25% 15.88%
2014 B. Cooks Oregon State 12 31.79% 15.24%
2014 J. Matthews Vanderbilt 5 32.43% 15.08%
2009 H. Nicks North Carolina 9 33.70% 14.76%
2013 D. Hopkins Clemson 9 34.12% 14.65%
2015 T. Lockett Kansas State 8 35.18% 14.38%
2014 S. Watkins Clemson 5 37.09% 13.90%
2015 N. Agholor USC 7 37.52% 13.80%
2013 T. Williams Baylor 5.5 38.15% 13.64%
2008 J. Nelson Kansas State 10 38.79% 13.48%
2010 G. Tate Notre Dame 8.5 39.21% 13.37%
2006 G. Jennings Western Michigan 11.5 39.42% 13.32%
2014 J. Landry LSU 8.5 39.85% 13.21%
2012 A.J. Jenkins Illinois 0.5 40.06% 13.16%
2010 J. Shipley Texas 1 40.27% 13.10%
2013 T. Austin West Virginia 5.5 41.12% 12.89%
2008 J. Hardy Indiana 0 42.39% 12.57%
2015 K. White West Virginia 0.5 42.39% 12.57%
2009 J. Maclin Missouri 6.5 43.45% 12.30%
2009 M. Crabtree Texas Tech 9.5 44.51% 12.04%
2007 J. Jones San Jose State 5 45.36% 11.82%
2007 D. Bowe LSU 8 46.21% 11.61%
2011 J. Jones Alabama 9.5 46.21% 11.61%
2007 R. Meachem Tennessee 7 46.42% 11.56%
2012 M. Floyd Notre Dame 7 47.06% 11.40%
2009 P. Harvin Florida 10.5 47.06% 11.40%
2009 K. Britt Rutgers 3 47.48% 11.29%
2008 D. Avery Houston 0 47.69% 11.24%
2014 O. Beckham Jr. LSU 6 47.90% 11.18%
2014 M. Evans Texas A&M 9 48.12% 11.13%
2008 D. Thomas Michigan State 0 48.33% 11.08%
2014 K. Benjamin Florida State 6.5 48.96% 10.92%
2006 S. Holmes Ohio State 9 49.18% 10.86%
2012 R. Randle LSU 7.5 49.81% 10.70%
GROUP: Moderate Risk II (Projected Bust Chance: 50-60%)
Results: 60.87% (14/23) Busts
2014 A. Robinson Penn State 3 50.87% 10.44%
2012 S. Hill Georgia Tech 0 51.08% 10.38%
2011 T. Smith Maryland 7.5 51.08% 10.38%
2007 M. Sims-Walker UCF 7 51.30% 10.33%
2014 P. Richardson Colorado 4 51.30% 10.33%
2007 S. Rice South Carolina 8 51.51% 10.28%
2012 M. Sanu Rutgers 6.5 51.93% 10.17%
2006 C. Jackson Florida 0 52.57% 10.01%
2011 L. Hankerson Miami 1 53.42% 9.80%
2015 D. Green-Beckham Missouri 0 54.05% 9.64%
2007 J. Lee Higgins UTEP 1.5 54.26% 9.58%
2013 M. Wheaton Oregon State 3 55.33% 9.32%
2008 M. Manningham Michigan 6 55.54% 9.26%
2007 T. Ginn Jr. Ohio State 4 55.54% 9.26%
2007 D. Jarrett USC 1 55.54% 9.26%
2011 T. Young Boise State 0 55.75% 9.21%
2014 J. Huff Oregon 1 55.75% 9.21%
2011 V. Brown San Diego State 3 55.96% 9.16%
2011 A.J. Green Georgia 11 55.96% 9.16%
2010 E. Sanders SMU 6 56.17% 9.10%
2015 J. Strong Arizona State 0 56.39% 9.05%
2010 B. LaFell LSU 6 57.66% 8.73%
2013 R. Woods USC 5.5 58.72% 8.46%
GROUP: High Risk (Projected Bust Chance: 60-80%)
Results: 76.32% (29/38) Busts
2007 S. Smith USC 7.5 60.20% 8.09%
2015 D. Smith Ohio State 0 60.84% 7.93%
2011 A. Pettis Boise State 2.5 61.26% 7.82%
2012 A. Jeffery South Carolina 8 62.32% 7.56%
2015 B. Perriman UCF 1.5 62.53% 7.50%
2012 R. Broyles Oklahoma 0 62.96% 7.40%
2009 B. Robiskie Ohio State 0 63.17% 7.34%
2006 B. Williams Wisconsin 0 63.17% 7.34%
2013 J. Hunter Tennessee 2 63.38% 7.29%
2006 M. Stovall Notre Dame 1 63.38% 7.29%
2009 J. Iglesias Oklahoma 0 63.59% 7.24%
2012 T.Y. Hilton FIU 10 63.81% 7.18%
2014 C. Latimer Indiana 1.5 64.23% 7.08%
2010 D. Williams USC 2 64.23% 7.08%
2007 A. Gonzalez Ohio State 0.5 64.23% 7.08%
2009 M. Massaquoi Georgia 2 65.08% 6.86%
2008 M. Kelly Oklahoma 0 65.50% 6.76%
2008 E. Bennett Vanderbilt 4 66.99% 6.38%
2006 D. Hagan Arizona State 0.5 67.20% 6.33%
2015 P. Dorsett Miami 2.5 67.83% 6.17%
2011 J. Baldwin Pittsburgh 0 68.47% 6.01%
2015 D. Funchess Michigan 6.5 69.53% 5.74%
2007 C. Davis LSU 2 70.59% 5.48%
2009 P. Turner USC 0.5 70.59% 5.48%
2014 M. Lee USC 6.5 71.86% 5.16%
2008 H. Douglas Louisville 4 72.50% 5.00%
2008 A. Caldwell Florida 3 72.50% 5.00%
2008 D. Jackson California 9.5 73.77% 4.68%
2015 C. Conley Georgia 3 74.20% 4.57%
2011 J. Jernigan Troy 1 74.62% 4.46%
2009 M. Wallace Mississippi 8.5 75.68% 4.19%
2015 D. Parker Louisville 3.5 75.89% 4.14%
2010 T. Price Ohio State 0 76.53% 3.98%
2009 D. Butler Penn State 0 76.95% 3.87%
2009 D. Heyward-Bey Maryland 6 78.01% 3.61%
2014 D. Moncrief Mississippi 3 78.44% 3.50%
2010 E. Decker Minnesota 11.5 79.71% 3.18%
2006 S. Moss Miami 1 79.92% 3.13%
GROUP: Very High Risk (Projected Bust Chance: 80-99.99%)
Results: 94.74% (18/19) Busts
2013 C. Patterson Tennessee 3.5 81.83% 2.65%
2008 E. Doucet LSU 3.5 82.46% 2.49%
2013 A. Dobson Marshall 0.5 83.95% 2.11%
2015 S. Coates Auburn 0 84.37% 2.01%
2007 J. Hill Washington State 2 85.86% 1.63%
2011 R. Cobb Kentucky 10 86.28% 1.53%
2008 E. Royal Virginia Tech 3.5 87.13% 1.31%
2010 A. Benn Illinois 0 88.61% <1.00%
2009 D. Williams Penn State 0 89.25% <1.00%
2012 T.J. Graham N.C. State 0.5 90.73% <1.00%
2006 W. Reid Florida State 0 97.73% <1.00%
2007 Y. Figurs Kansas State 0 99.64% <1.00%
2013 M. Goodwin Texas 2 >99.90% <1.00%
2008 L. Sweed Texas 0 >99.90% <1.00%
2006 T. Wilson Oklahoma 0 >99.90% <1.00%
2011 G. Little North Carolina 2 >99.90% <1.00%
2012 D. Posey Ohio State 0 >99.90% <1.00%
2007 P. Williams Fresno State 0 >99.90% <1.00%
2009 B. Tate North Carolina 1.5 >99.90% <1.00%

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In what world is Tavon Austin NOT a bust? LMAO.
In what world are PERCY HARVIN, HAKEEM NICKS, MICHAEL CRABTREE, and RANDALL COBB better than CALVIN JOHNSON.
Amari Cooper isn't a bust...
When you consider where he was drafted, Sammy Watkins is in fact a bust.

This AV stat is far from reliable/accurate. There are far more players on the list that could be argued for/against.

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8 hours ago, Danger said:

In what world is Tavon Austin NOT a bust? LMAO.
In what world are PERCY HARVIN, HAKEEM NICKS, MICHAEL CRABTREE, and RANDALL COBB better than CALVIN JOHNSON.
Amari Cooper isn't a bust...
When you consider where he was drafted, Sammy Watkins is in fact a bust.

This AV stat is far from reliable/accurate. There are far more players on the list that could be argued for/against.

AV does a good enough job for what it's supposed to do, which is in this case give a close estimate for a large sample that can be used to find results for a smaller sample. 

The Amari Cooper one though, was a mistake. His AV was 7, I put 4 for whatever reason. 

I also decided to use the average of their years 3-4 AV because it's still on their first contract, so it represents value the team got out of the draft pick itself. If you take Megatron's literally-almost-any-other-years, he's off the charts. But like I said, it's not perfect, and it doesn't have to be. It's called "Approximate" for a reason.

If you don't like AV, take it up with ProFootballReference. If you don't like my designation of what number is a bust, cool. 

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I made a mistake in the original model with a single player's data (Amari Cooper), but it was enough to throw off the entire data set. I had to redo the model for this slight correlation, so here are the new projections:

2019 WR Class Projections
Player Projected AV Bust Chance PB Chance
A. Isabella 5.26 32.63% 14.23%
M. Brown 4.72 43.36% 11.77%
J.J. Whiteside 4.48 52.98% 9.57%
N. Harry 4.51 52.98% 9.57%
P. Campbell 4.31 56.78% 8.70%
A.J. Brown 4.27 60.13% 7.93%
D. Samuel 4.11 62.37% 7.42%
M. Boykin 3.57 74.22% 4.70%
D. Johnson 3.42 76.24% 4.24%
J. Hurd 3.44 78.70% 3.68%
M. Hardman 3.19 81.83% 2.96%
T. McLaurin 3.16 84.73% 2.30%
D.K. Metcalf 2.69 97.48% <1.00%

Things look even bleaker for D.K. Metcalf (or for this model, if he succeeds).

Edited by AlNFL19

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