WR vs. CB Matchups & Advice: Week 16 (2022 Fantasy Football)

WR vs. CB Matchups & Advice: Week 16 (2022 Fantasy Football)

Hopefully, if you’re reading this, you’re in your fantasy league playoffs and are inches away from that ring. For those unfamiliar, this weekly article depicts our models that leverage advanced data to hone in on player matchups AND defensive tendencies to predict what WRs are more or less likely to “boom” in a given week. The models take into account everything from height, speed advanced grading, and yards per route run and compare that to the (weighted, expected) corresponding defensive player’s respective data. We mesh that with some defensive tendencies we expect to see, along with how that WR has performed given those splits, and find players to start/sit for the given week.

Let’s jump right in.

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Week 15 Results

We possibly pushed the envelope on the Godwin pick but will take the 3-1 outcome no less.

Name FP Selection Projected Actual Net
Garrett Wilson START 13.8 13.8 –
Josh Palmer START 7.8 9.9 +2.1
Drake London START 8.4 12.0 +3.6
Chris Godwin SIT 15.1 22.3 +7.2
DeAndre Hopkins SIT 15.2 13.0 -2.2

Season Scored Card

Season Record: 52-33

*All stats based on Yahoo Fantasy Football 1/2 PPR


Week 16 WR vs. CB Model Scorecard

Raw Numbers Weekly Rank
Snaps Wt.ed Net pprr 40 Adv. HT Adv. nPFFwted Total Wt.ed Net pprr 40 Adv. HT Adv. nPFFwted Total Avg. Rk.
Christian Watson 30.9 12.6 0.12 5.58 4.5 25 5 4 27 15
Davante Adams 40.0 16.6 0.03 2.03 9.8 5 16 40 5 17
Stefon Diggs 47.8 20.0 0.03 0.30 11.4 2 14 59 3 20
Tyler Boyd 40.8 11.3 0.02 5.01 9.4 50 18 5 7 20
Garrett Wilson 68.0 21.9 0.00 1.38 9.5 1 25 49 6 20
Amon-Ra St. Brown 38.4 16.0 0.00 1.43 20.6 8 25 48 1 21
Tee Higgins 40.8 13.3 0.00 6.94 3.2 20 25 1 39 21
D.K. Metcalf 38.7 15.0 0.15 1.32 4.7 12 3 51 25 23
Chris Olave 46.7 16.8 0.01 0.51 7.8 4 22 57 10 23
Ja’Marr Chase 40.6 14.3 0.00 3.09 3.5 13 25 24 35 24
Michael Pittman Jr. 39.9 12.2 0.00 4.76 2.5 33 25 7 41 27
Drake London 43.7 14.1 0.00 2.87 2.6 15 25 27 40 27
A.J. Brown 41.7 16.3 0.00 -1.12 8.2 7 25 79 9 30
Jerry Jeudy 39.5 14.0 0.04 1.64 1.9 17 13 45 48 31
Tyreek Hill 39.4 18.9 0.00 -1.08 5.6 3 25 77 19 31
Rashid Shaheed 40.2 15.5 0.00 -0.79 6.0 10 25 75 16 32
Mack Hollins 40.1 11.0 0.05 4.71 1.7 56 12 8 52 32
Corey Davis 38.1 10.4 0.00 4.23 3.5 61 25 11 33 33
Justin Jefferson 40.0 16.5 -0.02 1.35 12.2 6 73 50 2 33
Chase Claypool 41.3 10.9 0.09 5.00 0.7 57 7 6 62 33
DeSean Jackson 42.1 14.0 0.06 -2.36 5.1 16 9 88 22 34
Adam Thielen 40.3 11.7 0.00 2.16 3.8 44 25 35 31 34
Equanimeous St. Brown 40.3 10.1 0.03 6.00 1.8 69 15 2 51 34
Randall Cobb 39.6 12.6 0.01 -0.40 4.3 26 21 68 29 36
Mike Williams 41.3 11.8 0.00 4.68 -0.8 40 25 9 71 36
Brandon Aiyuk 40.2 12.4 0.00 -0.11 4.5 31 23 65 28 37
Richie James Jr. 42.5 13.2 0.10 -2.44 3.7 21 6 90 32 37
CeeDee Lamb 41.0 14.1 -0.09 3.18 4.9 14 90 23 23 38
Amari Cooper 41.4 14.0 -0.03 0.89 10.1 18 77 52 4 38
Terrace Marshall Jr. 39.5 10.6 0.00 2.59 3.3 60 25 31 38 39
Isaiah McKenzie 34.5 11.3 0.09 -3.88 8.6 49 8 93 8 40
DeVonta Smith 41.7 12.8 0.00 -2.44 5.6 23 25 89 21 40
Jaylen Waddle 39.5 15.2 0.00 -0.93 1.9 11 25 76 47 40
Allen Lazard 38.7 11.7 -0.01 5.87 2.3 43 70 3 45 40
Keenan Allen 41.0 12.4 -0.03 2.43 5.6 30 78 33 20 40
Darius Slayton 40.3 12.1 0.13 0.06 0.6 35 4 61 64 41
K.J. Osborn 40.3 10.3 0.00 -0.07 7.5 64 25 64 12 41
Jakobi Meyers 39.2 12.5 -0.08 3.94 3.5 29 88 14 34 41
DeAndre Hopkins 41.9 15.5 -0.07 0.74 6.1 9 87 55 15 42
Marquez Valdes-Scantling 42.0 10.1 0.06 2.16 1.6 66 11 36 53 42
Mike Evans 40.3 11.7 -0.04 4.16 3.8 45 80 12 30 42
Terry McLaurin 39.9 12.5 0.00 0.27 1.4 27 25 60 55 42
D.J. Moore 39.2 12.0 0.02 -1.21 3.4 37 17 80 37 43
Gabriel Davis 42.6 11.8 -0.02 3.43 3.5 41 74 20 36 43
George Pickens 41.2 9.7 0.00 2.94 2.0 76 25 26 46 43
Devin Duvernay 42.0 11.8 0.06 -1.22 2.3 39 10 81 44 44
Treylon Burks 30.0 9.4 0.00 3.70 1.4 79 25 16 57 44
D.J. Chark Jr. 39.2 9.4 0.02 3.37 1.4 78 20 22 58 45
DeVante Parker 39.3 10.3 -0.05 3.45 7.5 62 84 19 13 45
Curtis Samuel 38.4 12.2 0.00 -0.01 1.1 34 25 62 60 45
Donovan Peoples-Jones 41.4 11.5 -0.07 1.87 7.2 47 86 43 14 48
Alec Pierce 38.5 9.9 0.00 3.38 -1.3 73 25 21 75 49
Zay Jones 39.9 11.0 0.00 2.04 -2.7 55 24 39 81 50
JuJu Smith-Schuster 42.2 13.5 -0.09 -0.76 5.9 19 92 72 17 50
Noah Brown 41.5 10.2 0.00 2.82 -3.3 65 25 28 84 51
Nick Westbrook-Ikhine 40.0 7.7 0.00 3.70 -0.9 90 25 17 72 51
Marquise Brown 41.8 12.5 0.00 -2.61 0.7 28 25 91 61 51
Dante Pettis 41.3 10.1 0.00 2.00 -1.1 68 25 41 73 52
Chris Godwin 40.1 12.8 -0.02 -1.80 4.8 24 75 85 24 52
Hunter Renfrow 40.0 9.4 0.02 -0.45 2.3 77 19 69 43 52
Parris Campbell 39.9 10.1 0.00 2.06 -2.3 67 25 38 78 52
Josh Palmer 41.2 10.0 0.00 2.67 -2.8 72 25 30 82 52
Jahan Dotson 38.7 11.2 0.00 -0.14 -0.5 52 25 66 69 53
Marquise Goodwin 38.4 11.9 0.17 -4.02 -2.4 38 2 94 79 53
Tutu Atwell 37.5 11.1 0.00 -1.63 1.8 54 25 84 50 53
Demarcus Robinson 42.0 12.9 -0.10 0.49 2.4 22 93 58 42 54
Robert Woods 39.7 8.5 0.00 1.58 1.4 87 25 47 56 54
Russell Gage 40.2 11.8 0.00 -1.60 -0.4 42 25 83 68 55
Bennett Skowronek 38.5 7.1 0.00 4.40 -6.1 94 25 10 90 55
Chris Moore 35.2 10.0 -0.01 2.22 1.9 70 71 34 49 56
Damiere Byrd 39.0 12.1 0.00 -4.85 -1.1 36 25 95 74 58
Trent Sherfield 40.0 9.8 0.00 1.92 -4.7 75 25 42 88 58
Jauan Jennings 39.3 10.0 -0.04 3.68 0.6 71 79 18 63 58
Christian Kirk 39.7 12.3 0.00 -0.20 0.5 32 69 67 66 59
Phillip Dorsett 38.2 8.5 0.21 -0.75 -1.9 86 1 71 77 59
Van Jefferson 40.2 8.7 0.00 1.78 -3.8 85 25 44 85 60
Amari Rodgers 37.9 10.8 0.00 -1.35 -1.7 58 25 82 76 60
Dareke Young 38.7 4.6 0.00 2.80 -7.5 95 25 29 92 60
Courtland Sutton 40.4 11.4 -0.09 3.94 -4.3 48 91 15 87 60
Josh Reynolds 39.2 9.9 -0.04 2.54 1.6 74 81 32 54 60
Ray-Ray McCloud III 39.8 8.8 -0.02 -0.78 7.6 84 72 74 11 60
Marvin Jones Jr. 39.9 8.1 0.00 2.06 -7.0 89 25 37 91 61
Diontae Johnson 41.4 11.1 -0.06 -2.23 5.6 53 85 87 18 61
Quez Watkins 41.3 11.3 0.00 -0.76 -10.9 51 25 73 96 61
Nelson Agholor 39.2 10.7 -0.03 0.80 1.4 59 76 53 59 62
Elijah Moore 38.4 8.9 0.00 -1.11 0.6 82 25 78 65 63
Olamide Zaccheaus 39.2 11.6 0.00 -6.43 -5.6 46 25 96 89 64
Justin Watson 35.0 7.7 0.00 -0.02 -2.5 91 25 63 80 65
David Bell 37.3 7.7 -0.26 1.60 4.6 92 96 46 26 65
A.J. Green 41.9 9.0 -0.05 4.16 -9.5 81 83 13 93 68
Isaiah Hodgins 29.9 8.4 -0.15 3.02 -0.7 88 95 25 70 70
Steven Sims 28.2 4.3 0.00 -0.74 -9.6 96 25 70 95 72
Shi Smith 39.4 8.8 0.00 -2.78 -9.5 83 25 92 94 74
Michael Gallup 41.5 9.0 -0.08 0.77 -4.0 80 89 54 86 77
Jarvis Landry 39.0 10.3 -0.12 -1.80 0.3 63 94 86 67 78
Freddie Swain 40.5 7.2 -0.05 0.59 -3.2 93 82 56 83 79

*Again, thanks to our friends at PFF for the data

**To standardize all variables we are tracking (and make it easier to read), we included a RANK Display, respective of each data point to the right AND sorted by the average rank across variables.

Legend

  • Snaps: estimated total dropback snaps a WR will play in the coming matchup
  • Wt.ed Net PPRR: “Weighted Net Fantasy Points/Route Run.” Simply this is the net value of a WR’s PPRR average vs. the DB’s PPRR given up, weighted according to the DB each WR is expected to play.

Example:

  • Say Davante Adams averages 2.0 points/route run
  • DB1 (expected to face 50% of snaps) gives up 3.0 points/route run
  • DB2 (expected to face 30% of snaps) gives up 4.0 points/route run
  • DB3 (expected to face 20% of snaps) gives up 1.0 points/route run

This first model would predict Adams to produce 2.45 points/route run (Adams 2.0 vs. aggregate defenders averages weighted to 2.9)

  • *40 Adv: “40 Yard Dash Advantage” (weighted difference between WR 40 time and DB’s)
  • *HT Adv: “Height Advantage” (same as above, but with height)
  • nPFFwted Total: “Net PFF weighted Total Advantage.” Our core model, similar to the Wt.ed Net PPRR above, it compares the PFF grade between WR and likely DB, weighted by expected snaps he’ll see each respective DB

*Not all WRs and DBs have 40 times, and/or height measurements. When this occurs with ONE party, the model ignores the other (i.e., you need a WR and DB with a 40 time for this data point to populate)

Secondary/Bonus Chart

For this week, we included data points/a model to represent the target share CHANGES given specific circumstances (Blitz, Man) we expect the WR to see, given the opponent’s tendencies. As we’ve noted previously, how a QB operates and who he targets can change drastically given the defensive scheme, so keeping the data below in consideration for setting your lineup on a weekly basis is key.

NOTE: For Week 16, I spared you the players within +/-2% change, and the chart below ONLY displays players that have a (relatively) strong indication in either direction

A few notes on the data below:

  • ALL stats ignore game scripts of greater than a 16-point differential (either way), the goal line (and from 0-10 yard line), and 4th downs and quarters
  • All % next to a WR represent target SHARE given the circumstance (i.e., Nico Collins is seeing 24% of targets without a blitz and 62% when blitzed)
  • The first six columns represent how the respective WR performs, along with a “bonus” that’s reflective of target share increasing with Blitz (vs. non-Blitz) and Man (vs. Zone), meaning a negative number is not “bad,” but more so that the WR’s target share gets a bump with no Blitz or Zone respectively.
  • The middle columns represent the WR’s opponent’s tendencies, along with a (3rd and 5th row in the middle section) metric for how many percentage points above or below league average THAT defense sends blitz/runs Man.
  • The last three columns give an aggregate of how the WR performs relative to coverage and blitz schemes to expect
Player no blitz BLITZ zone MAN BLITZ bonus MAN bonus Opp BRAnflAVG MRAnflAVG Blitz bonus Man bonus net
Tyreek Hill 43% 75% 46% 49% 32% 3% Packers 17% 6% 6% 0% 6%
Justin Jefferson 62% 72% 59% 71% 10% 12% Giants 16% 16% 2% 2% 3%
Romeo Doubs 5% 29% 11% 12% 24% 1% Dolphins 11% 4% 3% 0% 3%
Chris Godwin 19% 42% 25% 16% 23% -9% Cardinals 7% -10% 2% 1% 3%
Nick Westbrook-Ikhine 26% 16% 31% 4% -10% -26% Texans -6% -7% 1% 2% 3%
Chris Moore 31% 11% 20% 20% -20% 0% Titans -12% -4% 2% 0% 2%
Cooper Kupp 38% 58% 44% 35% 20% -9% Broncos 10% -2% 2% 0% 2%
Josh Palmer 36% 17% 31% 19% -19% -11% Colts -12% 2% 2% 0% 2%
Brandin Cooks 31% 17% 25% 17% -13% -8% Titans -12% -4% 2% 0% 2%
Darius Slayton 47% 68% 46% 48% 21% 1% Vikings -6% -14% -1% 0% -2%
DeAndre Hopkins 47% 39% 36% 51% -7% 15% Buccaneers 6% -8% 0% -1% -2%
Marvin Jones 11% 26% 18% 11% 15% -7% Jets -11% 0% -2% 0% -2%
Jaylen Waddle 28% 23% 28% 16% -6% -12% Packers 17% 6% -1% -1% -2%
Darnell Mooney 30% 56% 26% 58% 26% 32% Bills -4% -2% -1% -1% -2%
K.J. Osborn 11% 3% 8% 5% -8% -4% Giants 16% 16% -1% -1% -2%
Phillip Dorsett 18% 32% 16% 20% 14% 4% Titans -12% -4% -2% 0% -2%
Allen Lazard 53% 29% 26% 43% -25% 17% Dolphins 11% 4% -3% 1% -2%
Jerry Jeudy 28% 30% 18% 40% 2% 22% Rams 3% -10% 0% -2% -2%
Amari Cooper 35% 61% 38% 40% 26% 2% Saints -11% 10% -3% 0% -3%

*ONLY WRs with > +- 2% Included in chart above

**Thanks to our friends at Sports Info Solutions and their SIS Database for the info!
***NEW NOTE: the “target share” is not “target ONLY,” but Intended Air Yard share (IAY share) as this gives us a clearer picture not only of the target share but the potential magnitude of said share
****Players that have played on 2 separate teams in 2022 are excluded (as they blur the percentage shares)

WR Matchups to Target in Week 16

*For the matchup sections below, we refrain from “obvious recommendations” and/or players you are starting no matter what (and the opposite for players recommended to sit)

Richie James Jr. (WR – NYG)

Richie burned us earlier in the season, but we still like his outlook this weekend. From a schematic standpoint, James really hasn’t been targeted vs. Man Coverage (9% share), yet sees a 2x share bump (21%) vs. Zone. This is especially significant this week, as the Vikings deploy zone coverage 14% points MORE than the league average. James also comes in with a favorable individual matchup, with a strong speed advantage (4.48 vs. 4.6 40-yard dash) along with respectable Weighted Net Points/Route Run (WNP/RR) and net PFF grade (65 vs. 59.5) vs. likely counterpart Chandon Sullivan (83% expected pass snaps).

Tee Higgins (WR – CIN)

The opponent Patriots are a “Man Defense,” using Cover 1/0 6 percentage points more than the league average. This is a good sign for the veteran WR as his target share nearly doubles from 24% to 46% vs. Man. Additionally, Higgins comes in with our base model’s 7th best individual matchup for the week. This is mainly driven by the #1 height advantage of the week, along with a solid WNP/RR. Higgins standing at 76 inches, dwarfs all likely cover men (Marcus Jones (36%), Myles Bryant (21%), and Jonathan Jones (43%) of expected pass snaps) by at least six inches.

*Tyreek Hill (WR – MIA)

I know I promised to only use “borderline starters” in this section, but we HAD to include Hill here, as we may never have had a stronger indication of predicted stellar performance. Let’s start with the scheme: Hill is quite literally “the guy” that his QB targets when facing a blitz, garnering a whopping 75% target share (vs. 43% without a blitz) when a defense brings 5+. This is big for the young WR, as the Packers send blitz 17% points MORE than the league average. To top that off, our model expects Hill to face Keisean Nixon (51%) in the majority of pass snaps, which bodes well for Hill and his 3.47 WNP/RR vs. Nixon’s 1.39.

WR Matchups to Avoid in Week 16

Jaylen Waddle (WR – MIA)

This fade selection ties in with the previous “start selection” of Hill. Simply put, given the monster share of targets Hill gets vs. blitz and how much the Packers will need to manufacture pressure with said blitz, we believe Waddle will get the short end of the stick for the game as a whole. Beyond that, our model only sees a moderate comparative advantage between Waddle’s (very respectable) 82.6 PFF grade against likely cover men Nixon’s (46% pass snaps) 79 grade and Jaire Alexander‘s (31%) 74.6 grade.

DeAndre Hopkins (WR – ARI)

Yes, for weekly readers, this is a repeat from last week, BUT one that we cashed in on. So we are “going back to the well.” Schematically, as noted last week, Hopkins sees a jump from 36% target share to 51% when facing a blitz. As the Buccaneers bring 5+ 8 percentage points less than the league average, we likely won’t see any “scheme-based boost” for Hopkins here. Not AS important, but still worth noting: Hopkins also comes in with bottom 10% “physical advantages” due to “on-paper” speed and height disadvantages. We have enough of a sample to know “physical disadvantages” don’t really stop Hopkins, but when you consider the scheme disadvantage and the marginal effectiveness compared to OTHER WRs, we’re fading him again this week.

Hopefully, this data helps you build the ideal lineup to propel you through the playoffs! See you all next week.

If you want to dive deeper into fantasy football, be sure to check out our award-winning slate of Fantasy Football Tools as you navigate your season. From our Start/Sit Assistant – which provides your optimal lineup based on accurate consensus projections – to our Waiver Wire Assistant – which allows you to quickly see which available players will improve your team and by how much – we’ve got you covered this fantasy football season.

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