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Solving for Opportunity: Why Kamar Aiken Might Not Suck

Kamar Aiken is less exciting than UncleChaps reviewing a squatty potty. This is unquestioned. But even if he isn’t sexy, he’s still incredibly interesting simply because of what he represents.

In Aiken we have a league average athlete who was given his team’s WR1 targets due to injury and held his own. He’s an almost pure product of opportunity, and how you value Aiken in 2016 will almost precisely mirror how you approach player valuation in general.

If you think athletic talent and efficiency are indicators of future opportunity, you will be predisposed to fade Aiken. If you simply look at the sheer number of WRs on the Raven’s roster, their draft pedigrees and past production, you’ll also fade Aiken. If you are an honest analyst like 14teammocker and admit you just don’t know, you’ll probably fade Aiken.

Given all this, despite his 7.9 targets per game in 2015, it isn’t surprising to see his MFL10 ADP hovering around WR 61. Well below a 37-year-old Steve Smith and a guy with zero career receptions guy who will miss another season.1

Screen Shot 2016-06-08 at 2.42.05 PM

Solving for opportunity

Still there are reasons to like Aiken, even if you agree with Mocker2 that humility in the face of uncertainty is the best bet.

If we build a toy model 3 to try and predict Y+1 targets per game, we can take a stab at quantifying what coaches might be considering when making their playing time decisions.

Screen Shot 2016-06-10 at 12.16.00 PM

Each variable included makes intuitive sense. We can tell a credible story about each of them that tracks with our understanding of the game.4

  • Targets/Game from the previous season are the best predictor of future targets.
  • When a receiver scores a touchdown it stands out in a coach’s mind.
  • Pass Grades from Pro Football Focus have value if we believe teams are using them to make decisions, and there is evidence that they have. In an email recently sent to newsletter subscribers, Cris Collinsworth reports that PFF grades are now used by 22 of the 32 NFL teams.
  • Yards after catch and explosive plays5 are game changing stats. YAC plays make highlight reels and stand out in the film room. Explosive plays are similar. Since the 2000 season 65 percent of scoring drives in the NFL have included at least one explosive play. Coaches are very sensitive to players that can help them score and keep their jobs.

Finally this simple, flawed model correlates very well with 2016 ADP6. Fantasy players appear to use these same7 variables when drafting.

Just not for Kamar Aiken.

Embrace the Uncertainty

In 2015 Aiken had 7.9 targets/game, 0.31 TDs per game, a pass grade of 10, 214 yards after the catch, and 11 explosive plays. In the PFF era,8 no player to meet those rough thresholds ever went on to have an even moderately healthy season with less than six targets/game.9 That’s 96 targets over 16 games which equates to roughly a WR 30 level of opportunity.

There is nothing saying Aiken can’t have a worse year than six targets per game, but it would be unprecedented given his 2015 profile. Instead, it’s more likely that Aiken is simply mispriced and is being drafted well below his healthy floor.

More Reasons to Like Kamar Aiken

According to Baltimore Sun beat writer Jeff Zrebiec, Aiken is the first wide receiver in franchise history to haul in five or more receptions in nine straight games. That will get a coach’s attention.

Zrebiec also notes that Aiken is one of the team’s most popular players. I don’t have data on player likability, but I’m willing to bet that if I did a dummy variable for “locker room cancer,” it would be negatively correlated with Y+1 targets.

The Ravens are poised to be pass happy again next year under Marc Trestman, coupled with what will likely be a bottom-10 defense. Joe Flacco should be showering targets on WR1s and WR2s alike.

Lastly, Aiken’s upside is absolutely real and completely absent from his current market value. If Steve Smith or Perriman go down due to injury, if Perriman fails to meet expectations, and/or if Mike Wallace continues to be Mike Wallace, there is a plausible future world where Aiken gets more targets than he saw last season.

If that happens, he’ll go from an interesting but un-sexy preseason flier to a league winner.

fnamelnameseasonY+1 Targets/G
CalvinJohnson201211.2143
DemaryiusThomas201411.0625
CalvinJohnson201112.75
AntonioBrown201412.0625
JulioJones201412.6875
OdellBeckham Jr.201410.5333
CalvinJohnson20139.8462
BrandonMarshall200712.0667
BrandonMarshall201210.375
RandyMoss20077.875
AntonioBrown201311.375
LarryFitzgerald20079.6875
WesWelker201110.9375
A.J.Green201211.125
AndreJohnson201211.3125
LarryFitzgerald20119.75
DemaryiusThomas20128.9375
DemaryiusThomas201311.5625
AndreJohnson200910.6154
AndreJohnson20107.2857
AndreJohnson200810.75
ReggieWayne20078.1875
TerrellOwens20078.75
DezBryant20148
VincentJackson201210
BrandonMarshall20138.1538
JulioJones201211.8
EmmanuelSanders20149.1333
RandallCobb20148.0625
ReggieWayne20128.5714
MilesAustin20097.4375
AndreJohnson20139.7333
SteveSmith20088.6
MichaelCrabtree20126.6
SidneyRice20097
LarryFitzgerald200910.875
ReggieWayne200911
MarquesColston20078
A.J.Green20148.25
CalvinJohnson20149.3125
DwayneBowe20118.6923
RoddyWhite20127.4615
AnquanBoldin20138.1875
DeAndreHopkins201412
DeSeanJackson20136.3333
WesWelker20079.4375
KeenanAllen20138.6429
JordyNelson20139.4375
PercyHarvin20119.4444
JordyNelson20116.1667
MarquesColston20118.125
VincentJackson20096
DwayneBowe20079.8125
SantonioHolmes20077.6
BobbyEngram20076.2308
MarquesColston20136.6
DerrickMason20088.375

  1. Editor’s note: This article was submitted prior to news of Perriman’s likely season-ending injury.  (back)
  2. Like I do.  (back)
  3. Not all multiple linear regression assumptions are satisfied – multicollinearity especially.  (back)
  4. And perhaps most importantly, each of these variables was hypothesis tested prior to being included. No p-hacking, although fumbles, pass blocking grade, penalty grade, and receiving yards per game were included, found to not be significant, and removed.  (back)
  5. Defined as plays gaining greater than 20 yards.  (back)
  6. Predicted Y+1 targets per game and 2016 WR ADP have a correlation of 0.82  (back)
  7. Or similarly correlated.  (back)
  8. 2007-2015.  (back)
  9. See table below for the full list.  (back)

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