WR vs. CB Matchups & Advice: Week 3 (2022 Fantasy Football)

WR vs. CB Matchups & Advice: Week 3 (2022 Fantasy Football)

We’re only a couple weeks into the NFL season and we have already had 

  • The “Least Likely Loser” in PGWE (postgame winning expectation) since Football Outsiders started tracking it
  • A Super Bowl Loser that has lost 2 straight games to start the season as a 7-point or better favorite for the first time ever
  • Of course a WR1 Ranking Table that includes: Amon-Ra St Brown, Jahan Dotson and Devin Duvernay. 

And that’s really what brings you here today. Like anyone trying to predict ANYTHING there will be variance, and there will be a level of luck, but the purpose of this article and research is to help maximize your chances of finding that WR1 for your weekly fantasy lineup.

As we mentioned in last week’s WR vs. CB Matchups & Advice: Week 2 (2022 Fantasy Football, and have hammered home to you by now:  “Coverage Predicting Models” are barely causal, and should not be taken as gospel. Instead, use this data as a tie-breaking system when you have 50/50 decisions. With all the self-loathing out of the way, I will say the model will only get better throughout the year, as the sample sizes of the relevant data points increase

Take that along with our success in the first two weeks, and you kind of have to pay attention, right?

Week 2 Results:

As always, win/lose/or draw we will start with last week’s performance, along with an ongoing scorecard for the season as a whole.

Week 2 brought us a “wishy-washy” 4-4 record, but with a +22.4 Net points gained vs. the projection between 8 players. Frankly, much of that was an “easy” pick on a player everyone is starting anyway (Diggs). Beyond that, we are just as proud of the Drake London pick as we are disappointed in the DJ Chark choice.

NameFP SelectionProjectedActualNet
DJ CharkSTART11.80-11.8 (L)
Chase ClaypoolSTART12.16.6-5.6 (L)
Tee HigginsSTART15.219.1+3.9 (W)
Drake LondonSTART10.924.6+13.7 (W)
Stefon DiggsSTART18.144.8+27.6 (W)
Deebo SamuelSIT16.514.7-1.8 (W)
Devonta SmithSIT9.915.0+5.1 (L)
Josh PalmerSIT10.913.0+2.1 (L)

Season Scored Card

Season Record: 11-7
Total Net Points: 50.5
Net Points/Selection: +2.97

*All stats based on Yahoo Fantasy Football ½ PPR

*Note, based on feedback we made a few changes to the table:

  1. We aggregated all data into one spot (likely so you can copy and paste in to your own spreadsheet, you rascals, you)
  2. We made an executive decision to STILL track our “coverage bonuses” (who a QB targets more/less when blitzed/not blitzed and when facing zone/man), but not display and/or add to the model until we can incorporate 2022 data (likely in week 3-4)
  3. 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.

Week 3 WR vs CB Model Scorecard

Raw NumbersWeekly Rank
SnapsWt.ed Net pprr40 Adv.HT Adv.nPFFwted TotalWt.ed Net pprr40 Adv.HT Adv.nPFFwted TotalAvg. Rk.
Courtland Sutton57.717.60.004.485.8292852021
Devin Duvernay35.818.
Stefon Diggs56.741.
Amon-Ra St. Brown49.
Equanimeous St. Brown37.
Nelson Agholor69.936.20.020.815.8320581925
Drake London54.923.00.001.388.7142851725
D.K. Metcalf54.520.20.022.922.61817293826
Rashod Bateman48.
Amari Cooper54.420.90.110.455.7175642127
Justin Jefferson61.
Zay Jones47.915.
Julio Jones43.913.00.073.422.9548153628
Gabriel Davis35.915.80.022.943.63821273430
Tee Higgins54.815.80.003.990.63928105032
Robbie Anderson57.417.70.003.340.32828185432
Corey Davis45.513.30.003.452.45128124033
Mike Williams55.817.80.004.03-0.8272896933
Marvin Jones Jr.56.916.
Jaylen Waddle73.536.70.00-1.266.2228891734
Jerry Jeudy50.718.00.002.581.62628364634
Tyreek Hill67.335.20.00-1.897.7428921234
Cooper Kupp62.831.7-0.082.4513.459338235
Tyler Lockett58.228.00.01-3.167.9724971135
Michael Pittman Jr.59.523.0-0.033.304.11279193035
Michael Pittman Jr.59.523.0-0.033.304.11279193035
Christian Kirk51.620.20.001.518.01968481036
Jakobi Meyers51.625.0-0.092.4413.399639337
Dante Pettis46.
DeVante Parker52.
Chase Claypool50.713.90.003.40-0.14527166438
Marquez Valdes-Scantling47.411.30.064.22-1.161987438
Garrett Wilson35.
Michael Thomas54.618.0-0.083.444.72495132740
Noah Brown31.910.50.002.535.07228372340
DeVonta Smith62.
Donovan Peoples-Jones53.713.10.051.430.55212505141
Brandin Cooks54.718.00.16-1.650.8253914942
Mecole Hardman50.818.50.06-1.211.62310884742
Davante Adams58.021.5-0.041.624.41581462943
Marquise Brown83.829.90.00-2.871.7628954544
A.J. Brown56.421.2-0.050.2711.3168767444
Olamide Zaccheaus39.919.40.00-5.654.821281012644
A.J. Green54.411.2-0.014.902.5647133944
Nico Collins43.
Greg Dortch45.716.10.00-4.176.23628991645
Curtis Samuel42.315.20.100.84-1.2416577545
Sterling Shepard47.917.00.01-0.772.93323873745
Ja’Marr Chase63.416.60.000.450.33528635545
DeAndre Carter39.814.80.00-3.006.04228961846
Isaiah McKenzie25.510.80.01-4.6213.76522100147
Allen Robinson II53.810.8-0.072.978.8669126647
D.J. Chark Jr.50.610.60.182.73-4.8681349149
Demarcus Robinson40.813.4-0.112.337.55097401450
Robert Woods81.917.40.000.80-2.43028598450
Chris Moore30.512.4-
JuJu Smith-Schuster49.117.0-0.033.02-1.13276257352
Bennett Skowronek35.
Josh Palmer34.
CeeDee Lamb54.513.0-0.032.771.85577334452
Adam Thielen59.
Breshad Perriman36.
Terry McLaurin57.714.10.050.54-5.24413629453
Jauan Jennings41.29.3-0.064.801.9779044354
Alec Pierce34.
Nick Westbrook-Ikhine39.
Diontae Johnson58.520.0-0.16-2.607.720101941357
Darnell Mooney60.
Kadarius Toney36.88.40.00-0.560.48328825362
D.J. Moore56.613.6-0.04-0.603.94783853262
Mack Hollins32.88.2-0.013.86-1.88572117962
Allen Lazard46.612.7-0.125.32-4.9569929262
Jahan Dotson60.617.00.00-0.56-0.63169816862
K.J. Hamler0.
Laviska Shenault Jr.
Kenny Golladay0.
Mike Evans0.
Byron Pringle0.
Kyle Philips0.
Dennis Houston0.
Bryan Edwards46.
George Pickens56.312.4-0.052.64-1.05788357263
Josh Reynolds49.
Tyler Boyd60.411.6-0.012.89-7.45970309764
David Sills29.37.2-0.124.26-0.1889876565
Brandon Aiyuk54.013.1-
Parris Campbell45.48.90.15-0.69-5.1804869366
Marquise Goodwin30.78.90.06-3.31-1.28111987667
K.J. Osborn49.110.60.00-0.47-4.27028808967
Elijah Moore42.17.90.00-1.55-0.58628906768
Russell Gage49.09.30.00-0.60-2.77828848569
Quez Watkins47.010.7-0.02-2.092.06774934269
Chris Olave51.29.9-0.031.87-1.97378448169
Deebo Samuel53.010.6-0.040.68-2.36982608374
Cedrick Wilson39.66.3-0.042.83-8.09185319876
Sammy Watkins35.29.4-0.060.42-4.37689659080
Jarvis Landry50.911.2-0.08-0.14-3.36294798680
Michael Gallup50.34.9-0.041.16-26.892865310183
Hunter Renfrow50.810.5-0.07-0.13-5.77192789684
Randall Cobb36.87.4-0.02-0.57-5.68773839585
David Bell24.74.3-0.141.54-8.893100479985

*Again thanks to our friends at PFF for the data


  • Snaps: estimated total drop back 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. 


  • 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 datapoint to populate)

WR Matchups to Target in Week 3

*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)

  • Equanimeous St Brown

Before everyone laughs at us for recommending the 2nd-3rd WR on a team that threw 11 passes (in a negative game script to boot) last week, hear us out. For starters, it’s hard to not see the Bears total passes going up this week (as they really can not go down). But more importantly this has to do with a great weekly ranking in our base model (5th highest ranking, buoyed mainly by the #1 height advantage this week) and a new angle we included as a bonus this week:

Bonus Chart: Most Targeted Rookie CBs

We’ve always FIGURED that coaches target young CBs, so we thought we’d look into this and try to glean some additional insight based on trying to “think like an OC”. 

Below is a chart thanks to PFF, of Rookie CBs, by total targets seen this season.

If we filter this list down, excluding any DBs that have have a good coverage grade, and have less than 50 coverage snaps over the first two weeks that leaves us with:

“Bad Targeted CB”Highest Expected WR OpponentCoverage Snap % ExpectationBase Model Wk 3 Rank
Derek StingleyROWR Equanimeous St Brown29%6
Kyler GordonSWR Chris Moore75%60
Damarion WilliamsSWR Jakobi Meyers22%24
Sauce GardnerOWR Tee Higgins43%8
Christian BenfordROWR Tyrek Hill45%14

Admittedly this angle is most fruitful when you have a veteran QB and/or OC that “have been around the block”, and will know to attack this. However, with the amount of film coaches watch, you’d have to think this will at minimum be a positive EV approach, especially tied in with our base model.

Back to St Brown for a minute: beyond a great rank in our base model, he’s likely to be matched up vs Derek Stingley (the MOST, relatively speaking) this week, who has been targeted at a “almost double digit rate” in each of his first two NFL games (with a bad grade). Cleary teams are targeting him, and the Bears coaching staff, although: not smart, can’t be this dumb either.

Put it all together and you have an excellent environment to “boom” this week.

  • Tee Higgins

Yes we went back to this well last week, but this is a similar play to the one above. Higgins literally checks all the boxes, and has an excellent matchup vs a rookie CB (see bonus chart above) in Sauce Gardner. Gardner should be facing Higgins on just under half of his snaps, and regardless of production, can be in line for a big volume bump.

  • Nelson Agholor

Agholor was actually a streamer for us last week, identifying opposing CB, Whiterspoon after he had been targeted 9 times in week 1, and being the LCB for 92% of snaps, and sure enough Agholor caught the deep touchdown over him. 

Mind you, this is the same WR that the Patriots have invested a lot of money in, and has the 3rd best Net points per route run (vs. covered) of any WR this week. All of this is not to mention a matchup with a Rookie CB himself, in Damarion Williams. (Note: we recommend the same play, for the same reasoning for Jakobi Meyers if you’re looking for someone with a higher floor).

Others to consider bumping up this week:

  • Marvin Jones Jr.
  • Zay Jones

WR Matchups to Avoid in Week 2

  • Tyler Boyd

This is an interesting play for us, as it’s the first time we recommended a “Sit” and a “Start” WR from the same team. I’ll be honest, I don’t know if that’s a good thing, or a bad thing. Nonetheless, this selection has a lot to do with the heavy (89% snaps expected) matchup with CB Michael Carter II. Carter out “PFF grades” Boyd 66 to 57 and out “Yards Per Route Run” (YPRRs) him .53 (Boyd) to .21 (Carter, low is good for a CB). There is a lot here, not the least of which is the “transitive property between Boyd (being predicted as doing “Bad”) and Higgins (being predicted as doing “Good”) pointing to the negative for Boyd.

It also really hurts that he’s only expected to see 5% of his coverage snaps vs. the rookie Sauce Gardner. 

  • Jahan Dotson

This may be cheating a bit, since everyone and their grandma know that, although talented, Dotson’s WR1 ranking through 2 weeks is really just propped up by TDs. Either way, he grades pretty badly in all matchups, especially sporting one of our worst height disadvantages of the week with both CBs Darius Slay and James Bradberry having at least an inch on him, which should encompass 71% of his total pass snaps.

  • Diontae Johnson

This selection is based on an unusual split WITHIN our model. His metrics for Net Grade and YPRR actually out-duel his likely matchup values, however he has an abysmal speed and height net matchup. At 70 inches tall, and running a 4.6 40 he will see 93% of his snaps collectively vs. Denzel Ward (71 Inches, 4.32 40) and Martin Emerson (74 inches, 4.53 40). In other words, this is as pure a PHYSICAL mis-match “sit” as we have ever recommended.

Others to consider sitting:

  • Mike Evans
  • DJ Moore

Hopefully this model and its selections help you to a winning week, but definitely check back next week when we will have enough data to begin to include coverage/blitz data to our model. Best of luck this weekend!

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