WR vs. CB Matchups & Advice: Week 9 (2022 Fantasy Football)

WR vs. CB Matchups & Advice: Week 9 (2022 Fantasy Football)

We are officially at the halfway point of the season. As we have noted before between the extreme levels of parity across the board, and offensive production being on a downswing, it’s more important than ever to find value in our WR selections for the week. The hope is the models below will help you get there. Let’s jump right in.

Week 8 Results:

After a very strong week 7, we came back to earth with our first losing week on the season. 

NameFP SelectionProjectedActualNet
Garrett WilsonSTART10.417.5+7.1(W)
Gabriel DavisSTART12.85.5-7.3 (L)
Drake LondonSTART10.27.1-3.1 (L)
*Rashod BatemenSIT**
Terry McLaurinSIT12.616.6+4.0 (L)


Season Scored Card

Season Record: 33-20

*All stats based on Yahoo Fantasy Football ½ PPR

Week 9 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.
Drake London53.518.
D.K. Metcalf39.314.00.073.2913.8231318214
Chris Olave52.919.60.071.557.7314391418
Alec Pierce41.
A.J. Brown42.917.20.001.938.51220351120
Tee Higgins41.
Justin Jefferson39.914.
Mike Evans56.022.8-
Allen Lazard39.117.2-0.044.599.211686924
Equanimeous St. Brown41.
JuJu Smith-Schuster59.
Tyreek Hill39.619.40.00-1.7412.852068424
Julio Jones40.614.
Romeo Doubs52.719.
Jakobi Meyers39.114.7-0.054.2513.220698325
Sammy Watkins38.313.80.04-0.3315.4251659125
Garrett Wilson43.413.30.120.596.4286491825
Davante Adams40.
Cody Hollister38.810.40.003.725.35320132127
Tyler Lockett39.014.90.09-2.288.3177711227
Tre’Quan Smith40.413.9-0.013.1410.9245821527
Marquez Valdes-Scantling41.410.50.175.00-0.150445428
Jaylen Waddle39.816.90.00-1.799.01320691028
Amon-Ra St. Brown37.614.90.00-0.286.31620581928
Curtis Samuel39.512.10.24-0.666.9382601529
Damiere Byrd40.020.10.00-1.704.9220672629
Michael Pittman Jr.40.112.1-0.015.406.5376221730
Tyler Boyd41.113.4-0.022.9410.6276323630
Mack Hollins40.
Terrace Marshall Jr.38.810.10.003.833.05620123932
DeVonta Smith43.
Adam Thielen40.
Corey Davis37.910.
Keenan Allen42.818.3-
Parris Campbell40.
Terry McLaurin55.815.60.14-0.99-0.2145615534
Devin Duvernay41.614.9-0.01-0.269.2185957836
Mecole Hardman41.213.00.19-1.001.8293624936
Darnell Mooney42.012.50.08-0.062.53512554537
Marvin Jones Jr.
Stefon Diggs42.
Christian Kirk39.312.6-
Josh Palmer41.811.30.002.00-2.14320326039
Zay Jones39.510.50.003.563.14956143839
Cooper Kupp39.215.1-0.222.763.01576264039
Chris Godwin40.412.80.010.43-4.63017506541
Hunter Renfrow40.
Olamide Zaccheaus40.213.70.00-2.351.82620734842
K.J. Osborn40.29.00.00-0.253.76320563243
Trent Sherfield40.
D.J. Moore38.512.20.00-1.145.63657642044
Cam Sims41.
Demarcus Robinson41.511.4-0.110.865.34274462246
Josh Reynolds38.410.4-0.043.370.45167165347
Nick Westbrook-Ikhine38.
Isaiah McKenzie41.512.60.01-3.23-8.43418757049
Rondale Moore41.310.70.00-6.38-0.44420785650
Kendrick Bourne54.812.0-0.092.65-1.13973275950
Brandin Cooks38.19.30.09-1.37-3.36111656450
DeAndre Hopkins42.518.2-0.25-2.312.9978724250
Braxton Berrios37.88.10.00-2.182.66920704451
Kalif Raymond38.19.80.00-4.111.15720775051
Mike Thomas40.
Gabriel Davis42.010.4-0.063.42-4.75471156752
Nelson Agholor39.110.6-0.011.59-2.44761376252
DeAndre Carter42.010.20.00-4.00-0.75520765752
Robert Woods38.211.9-0.06-1.073.24070633753
James Proche41.
Van Jefferson39.
Phillip Dorsett38.27.40.09-1.42-6.07110666854
D’Wayne Eskridge39.09.20.00-2.38-2.26220746154
Shi Smith38.
Chase Claypool42.
Marquez Callaway40.58.8-0.082.36-2.46572286357
Chris Moore38.07.4-0.133.19-11.27075197259
Allen Robinson II39.78.2-0.242.78-4.66877256659
Quez Watkins42.
A.J. Green42.45.7-0.032.82-11.37666247360

*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.


  • 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)


With 8 weeks of data its time to start looking at coverage situations. Given how elastic certain DCs are with their schemes, not to mention the lack of predictability when it comes to DB performance, we find it best to “batch” coverages by:

  • Man (M) no blitz (Cover 0, 1 with 4 or less rushers)
  • Man BLITZ (Cover 0, 1 with 5 or more rushers)
  • Zone (Z) no blitz (Cover 2, 3, 4 or 6 with 4 or less rushers)
  • Zone BLITZ (Cover 2, 3, 4 or 6 with 5 or more rushers)

Then we run a comparison on Target SHARE CHANGE among those 4 categories. This is a slight, purposeful change from last week as target share is more indicative of how a QB operates given these circumstances. In other words, we want to find “who he goes to when blitzed”. The target share will get us closer there.


  • The first 6 columns represent how THAT WR performs
  • The 7th-9th columns represent how much this week’s opponent runs Man (vs Zone) and Blitz (vs. not) compared to league average, in percentage points
  • The last 3 columns give an aggregate of how the WR performs relative to coverage and blitz schemes to expect
WR Target Share CHANGESOpponent
Rashod BatemanRavens27%25%2%15%45%-30%Saints14%-11%
Marquez Valdes-ScantlingChiefs33%37%-4%11%47%-36%Titans-2%-9%
Christian WatsonPackers5%6%-1%17%0%17%Lions7%14%
Kalif RaymondLions16%25%-9%30%17%13%Packers14%17%
Davante AdamsRaiders57%52%5%75%44%31%Jaguars0%4%
Allen LazardPackers32%28%4%37%28%9%Lions7%14%
Breshad PerrimanBuccaneers19%8%10%24%9%15%Rams-11%8%
DeAndre CarterChargers10%18%-8%7%20%-13%Falcons-2%-9%
Braxton BerriosJets6%7%-2%-3%9%-11%Bills-9%-10%
Darnell MooneyBears48%51%-3%59%45%14%Dolphins5%7%
Ja’Marr ChaseBengals44%34%10%54%35%19%Panthers-4%5%
JuJu Smith-SchusterChiefs25%30%-5%24%32%-9%Titans-2%-9%
Brandon PowellRams6%1%5%8%0%8%Buccaneers-6%10%
Juwann WinfreePackers6%2%4%7%2%5%Lions7%14%
DJ CharkLions7%29%-22%25%20%4%Packers14%17%
Trent SherfieldDolphins4%9%-5%6%12%-6%Bears1%-12%
DeAndre HopkinsCardinals25%13%13%11%21%-10%Seahawks-2%-7%
Nico CollinsTexans41%23%19%48%25%23%Eagles8%3%
Tutu AtwellRams0%15%-15%16%9%7%Buccaneers-6%10%
Dyami BrownCommanders14%10%4%4%16%-12%Vikings-15%-5%
Romeo DoubsPackers33%22%11%30%26%4%Lions7%14%
Julio JonesBuccaneers2%8%-7%14%7%7%Rams-11%8%
Tyler LockettSeahawks29%42%-13%48%40%8%Cardinals-9%7%
Jamison CrowderBills4%9%-5%4%9%-5%Jets-2%-12%
Russell GageBuccaneers21%6%15%15%8%7%Rams-11%8%
DJ MoorePanthers58%70%-12%49%66%-17%Bengals8%-3%
Marquise BrownCardinals36%48%-12%38%45%-7%Seahawks-2%-7%
Michael BandyChargers5%9%-4%3%9%-6%Falcons-2%-9%
Cooper KuppRams47%50%-2%51%46%5%Buccaneers-6%10%
Denzel MimsJets0%5%-5%0%4%-5%Bills-9%-10%
Parris CampbellColts10%19%-9%3%18%-15%Patriots14%-3%
James ProcheRavens0%9%-9%3%7%-4%Saints14%-11%
Keenan AllenChargers0%5%-5%0%5%-5%Falcons-2%-9%
Chris GodwinBuccaneers7%20%-13%21%15%6%Rams-11%8%
Curtis SamuelCommanders24%21%3%13%22%-8%Vikings-15%-5%
Christian KirkJaguars31%38%-8%28%36%-8%Raiders2%-5%
Terrace Marshall Jr.Panthers14%15%-1%3%17%-14%Bengals8%-3%
Kendrick BournePatriots13%9%4%10%14%-4%Colts1%-11%
Dante PettisBears27%10%17%21%15%6%Dolphins5%7%
Andy IsabellaCardinals0%6%-6%0%5%-5%Seahawks-2%-7%
Jeff SmithJets6%2%4%0%3%-3%Bills-9%-10%
Skyy MooreChiefs8%7%1%4%8%-4%Titans-2%-9%
Tyquan ThorntonPatriots10%9%2%5%8%-3%Colts1%-11%
Khalil ShakirBills8%9%0%6%8%-2%Jets-2%-12%
Jakobi MeyersPatriots32%27%5%29%31%-2%Colts1%-11%
Tee HigginsBengals25%30%-5%34%29%5%Panthers-4%5%
Tom KennedyLions9%4%5%7%6%1%Packers14%17%
River CracraftDolphins0%3%-3%0%2%-2%Bears1%-12%
Stefon DiggsBills53%41%12%44%46%-2%Jets-2%-12%
Dee EskridgeSeahawks12%2%10%7%4%3%Cardinals-9%7%
Nick Westbrook-IkhineTitans23%30%-7%12%33%-21%Chiefs-9%-1%
Corey DavisJets21%33%-12%29%31%-2%Bills-9%-10%
Michael Pittman Jr.Colts28%27%1%24%31%-7%Patriots14%-3%
Jason MooreChargers0%2%-2%0%2%-2%Falcons-2%-9%
A.J. BrownEagles57%43%14%48%52%-4%Texans-8%-5%
Ihmir Smith-MarsetteBears0%2%-2%4%1%3%Dolphins5%7%
Zay JonesJaguars25%25%0%22%26%-4%Raiders2%-5%
Demarcus RobinsonRavens13%34%-21%22%23%-2%Saints14%-11%
Rondale MooreCardinals8%12%-4%7%9%-2%Seahawks-2%-7%
Dezmon PatmonColts1%6%-5%0%5%-5%Patriots14%-3%
DeVonta SmithEagles22%42%-19%30%33%-3%Texans-8%-5%
Treylon BurksTitans19%20%-1%10%24%-14%Chiefs-9%-1%
Josh PalmerChargers20%27%-7%21%22%-2%Falcons-2%-9%
Chris ConleyTexans3%0%3%4%0%4%Eagles8%3%
Ashton DulinColts7%18%-10%11%15%-4%Patriots14%-3%
Drake LondonFalcons56%35%21%49%38%11%Chargers8%1%
Jake KumerowBills0%3%-3%3%4%-1%Jets-2%-12%
K.J. OsbornVikings13%13%0%11%21%-10%Commanders7%-1%
Dax MilneCommanders1%2%-1%0%2%-2%Vikings-15%-5%
DK MetcalfSeahawks44%48%-4%45%44%1%Cardinals-9%7%
Marquez CallawaySaints8%12%-5%6%16%-9%Ravens-3%-1%
Elijah MooreJets39%22%17%26%27%-1%Bills-9%-10%
Bryan EdwardsFalcons0%3%-3%9%1%8%Chargers8%1%
Jarvis LandrySaints4%9%-6%5%13%-8%Ravens-3%-1%
Rashid ShaheedSaints0%8%-8%0%7%-7%Ravens-3%-1%
Justin JeffersonVikings44%48%-5%36%43%-6%Commanders7%-1%
Jalen GuytonChargers0%6%-6%6%7%-1%Falcons-2%-9%
Tim JonesJaguars0%1%-1%-1%0%-1%Raiders2%-5%
Isaiah HodginsBills2%3%-2%1%1%0%Jets-2%-12%
Laviska ShenaultPanthers0%2%-2%0%1%-1%Bengals8%-3%
Cedrick WilsonDolphins0%5%-5%4%4%0%Bears1%-12%
Jalen ReagorVikings2%0%2%0%1%-1%Commanders7%-1%
Damiere ByrdFalcons7%25%-19%23%22%1%Chargers8%1%
Mason KinseyTitans0%1%-1%0%0%0%Chiefs-9%-1%
Michael ThomasSaints6%12%-5%8%9%0%Ravens-3%-1%
Deonte HartySaints0%1%-1%0%0%0%Ravens-3%-1%
Tyler JohnsonTexans0%0%0%0%0%0%Eagles8%3%
Van JeffersonRams0%0%0%0%0%0%Buccaneers-6%10%
Zach PascalEagles3%5%-2%4%4%0%Texans-8%-5%
Hunter RenfrowRaiders9%11%-2%7%7%-1%Jaguars0%4%
Keith KirkwoodSaints3%0%3%3%0%3%Ravens-3%-1%
Lil’Jordan HumphreyPatriots0%3%-3%2%1%0%Colts1%-11%
Chris OlaveSaints52%46%6%50%45%5%Ravens-3%-1%
Isaiah McKenzieBills8%8%0%8%8%0%Jets-2%-12%
Jaelon DardenBuccaneers3%0%3%0%1%-1%Rams-11%8%
Tre’Quan SmithSaints28%9%19%19%11%8%Ravens-3%-1%
Chris MooreTexans14%10%5%11%13%-3%Eagles8%3%
Olamide ZaccheausFalcons18%28%-11%19%27%-8%Chargers8%1%
Kevin WhiteSaints0%3%-3%9%0%9%Ravens-3%-1%
Cam SimsCommanders8%8%0%11%9%2%Vikings-15%-5%
KhaDarel HodgeFalcons19%8%12%1%12%-11%Chargers8%1%
Nelson AgholorPatriots13%20%-7%14%13%1%Colts1%-11%
Cody HollisterTitans4%8%-4%15%4%11%Chiefs-9%-1%
Robert WoodsTitans35%32%3%42%30%12%Chiefs-9%-1%
Kyle PhilipsTitans19%6%12%21%7%15%Chiefs-9%-1%
Quintez CephusLions1%1%1%0%1%-1%Packers14%17%
Adam ThielenVikings41%39%2%52%36%17%Commanders7%-1%
Shi SmithPanthers28%13%15%22%15%7%Bengals8%-3%
Jamal AgnewJaguars14%4%9%10%5%5%Raiders2%-5%
N’Keal HarryBears4%2%1%0%3%-3%Dolphins5%7%
Andre BaccelliaCardinals3%2%1%5%2%3%Seahawks-2%-7%
Mike ThomasBengals10%6%4%3%8%-5%Panthers-4%5%
Tylan WallaceRavens2%10%-8%9%7%3%Saints14%-11%
Michael StrachanColts6%5%1%14%4%10%Patriots14%-3%
Quez WatkinsEagles18%10%7%18%12%6%Texans-8%-5%
Jahan DotsonCommanders14%17%-3%21%15%6%Vikings-15%-5%
Phillip DorsettTexans7%17%-10%5%16%-11%Eagles8%3%
Jaylen WaddleDolphins30%35%-5%33%30%3%Bears1%-12%
Marvin JonesJaguars31%32%-1%41%33%8%Raiders2%-5%
Brandin CooksTexans34%50%-17%31%45%-14%Eagles8%3%
Byron PringleBears0%7%-7%0%6%-6%Dolphins5%7%
Keelan ColeRaiders10%7%2%0%13%-13%Jaguars0%4%
Greg DortchCardinals5%9%-4%14%6%8%Seahawks-2%-7%
Alec PierceColts48%25%23%49%27%21%Patriots14%-3%
Equanimeous St. BrownBears12%29%-17%16%25%-9%Dolphins5%7%
Terry McLaurinCommanders41%42%-2%51%37%14%Vikings-15%-5%
Mack HollinsRaiders25%30%-6%18%35%-17%Jaguars0%4%
Tyreek HillDolphins66%47%19%57%51%6%Bears1%-12%
DeVante ParkerPatriots31%32%-1%39%32%7%Colts1%-11%
Samouri TourePackers0%10%-10%0%6%-6%Lions7%14%
Marquise GoodwinSeahawks16%7%8%1%13%-12%Cardinals-9%7%
Tyler BoydBengals20%28%-7%10%27%-17%Panthers-4%5%
Amon-Ra St. BrownLions22%17%5%13%18%-5%Packers14%17%
A.J. GreenCardinals23%10%13%25%12%13%Seahawks-2%-7%
Ben SkowronekRams14%17%-3%10%19%-9%Buccaneers-6%10%
Gabriel DavisBills23%27%-4%32%25%8%Jets-2%-12%
Amari RodgersPackers0%8%-8%0%7%-7%Lions7%14%
Scotty MillerBuccaneers12%17%-4%5%18%-12%Rams-11%8%
Allen RobinsonRams32%17%15%15%26%-10%Buccaneers-6%10%
Randall CobbPackers16%14%2%9%19%-10%Lions7%14%
Justin WatsonChiefs10%10%0%21%4%17%Titans-2%-9%
Mike EvansBuccaneers35%41%-6%20%43%-23%Rams-11%8%
Sammy WatkinsPackers8%11%-3%0%13%-13%Lions7%14%
Josh ReynoldsLions43%24%19%26%38%-12%Packers14%17%
Garrett WilsonJets28%31%-2%48%25%22%Bills-9%-10%
Mike WilliamsChargers65%32%32%62%34%28%Falcons-2%-9%
Mecole HardmanChiefs23%16%7%40%9%31%Titans-2%-9%
Devin DuvernayRavens58%22%36%51%18%33%Saints14%-11%

*thanks to SIS and their datahub for the stats
**All data was taken ONLY during first 3 quarters, first 3 downs, middle 80 yards of the field and game scripts within +-16 points

WR Matchups to Target in Week 9

*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)

  • Marquez Valdes-Scantling

Our secondary model is very excited about MVS this week. Its no secret that he and QB Mahomes have found some chemistry the last couple games, but we are more excited about his matchup this week. You will notice on the second chart that his target share is only 11% when a defense brings a blitz, yet a whopping 47% when the defense only rushes 4 or less. For what it is worth, this is the inverse for Mercole Hardman, but it tells us that MVS is Mahomes guy when NOT blitzed. Take that, and the fact opponent Titanss blitz 9% points less than average in the NFL, we are all over MVS this week.

  • Devin Duvernay

Duvernay has had a bit of an up and down season. However, we believe we found a variable to help predict when those “bang” (vs. bust) games will come: Man Coverage. Right now, Duvernay owns a measly 22% target share in zone, but almost tripples that to 58% vs Man. Given that opponent, Saints, run man 14% points higher than league average Duvernay should be in for a great game.

  • Alec Pierce

Pierce comes into week with multiple models pointing upward. For starters, using our base model, we find that Pierce has a top 20 matchup in height, speed and net PFF grade. This is heavily weighted toward an expected matchup vs Jalen Mills (52% pass snaps expected), giving up 3 inches (75 vs 72), .2 in the 40 (4.41 vs 4.61) and a PFF grade of 65.8 vs 35.8. Additionally, similar to Duvernay above, Pierce’s target share spikes (48 vs 25%) when he faces man coverage, and the Patriots deploy Cover 1/0 14% more than league average.

WR Matchups to Avoid in Week 9

  • Allen Robinson

Robinson has not had the start to the season most drafters hoped. Despite this, he is getting a bit of a bump given the Cooper Kupp injury. However, our models do not like the matchup this week. To be fair, it’s hard to peg down a MOST likely cover man he will likely go up against this week, but our numbers show a 37% expected pass share vs. Jamel Dean. Dean has a 83.1 PFF grade, vs Robinson’s 62.2. And this is all not to mention a strong speed advantage and only a 2 inch height difference.

  • DeAndre Hopkins

Hopkins draws rookie Tariq Woolen in this week’s matchup (estimated 77% pass snaps). Given the pff scores come close to a wash, believe it or not this is mainly a “physical mismatch”. Woolen bring 76 inches of height, and a blazing 4.26 40 yard dash. Both numbers could be enough to neutralize Hopkins’ 73 inches and 4.57 40. 

We’re hoping to get back in the win colum this week. Here’s to a perfect lineup!

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