Ryan Newman | Thu, Dec 22nd 2022, 9:54am EST

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.

Check out all of our weekly fantasy football content

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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