Ryan Newman | Wed, Dec 28th 2022, 12:14pm EST

WR vs. CB Matchups & Advice: Week 17 (2022 Fantasy Football)

If you’re reading this, congrats! I assume you’ve reached your league’s championship/at least something to play for this weekend. For those unfamiliar, this weekly article is a depiction of 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 the rest of our weekly fantasy football advice

Week 16 Results

At 3-2 on the week (3-0 if you ignore Dolphins WRs), we’re claiming victory in the form of magnitude. Despite the marginal victory, we netted you three points to the good per selection. I’ll take that any week!

Name	FP Selection	Projected	Actual	Net
Richie James Jr.	START	9.4	17.0	+7.6
Tee Higgins	START	13.7	26.8	+13.1
Tyreek Hill	START	23.8	14.3	-9.5
Jaylen Waddle	SIT	16.3	25.3	+9.0
DeAndre Hopkins	SIT	15.0	1.4	-13.6

Season Scored Card

Season Record: 55-35

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

Week 17 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.
Tee Higgins	40.3	14.1	0.00	5.00	7.8	21	27	3	11	16
Christian Watson	42.4	16.5	0.06	6.08	0.7	5	7	1	55	17
CeeDee Lamb	41.3	15.7	0.04	2.50	6.4	12	13	33	18	19
D.J. Chark Jr.	39.8	11.5	0.06	4.67	5.4	42	6	6	23	19
Drake London	45.3	15.2	0.00	3.51	6.4	15	27	19	19	20
Amon-Ra St. Brown	39.1	15.9	0.00	1.86	13.6	9	27	44	3	21
Tyreek Hill	39.2	18.3	0.00	1.05	10.9	1	27	53	4	21
DeSean Jackson	57.0	17.8	0.25	-0.85	6.5	2	1	72	17	23
D.K. Metcalf	39.8	12.0	0.12	4.23	1.9	39	4	9	44	24
Justin Jefferson	39.1	15.8	0.03	1.86	4.7	10	17	43	27	24
DeVante Parker	39.5	10.7	0.05	3.83	6.9	61	8	13	15	24
Davante Adams	39.4	15.8	0.00	1.55	5.7	11	27	49	22	27
Jaylen Waddle	39.4	15.4	0.00	0.92	7.5	13	27	58	13	28
Ja’Marr Chase	40.1	14.6	0.00	1.00	8.5	20	27	56	9	28
Amari Cooper	41.0	13.2	0.02	1.01	5.8	25	18	55	21	30
Chris Moore	38.4	11.3	0.00	2.09	9.6	46	27	38	8	30
Terry McLaurin	40.6	13.0	0.03	-0.26	7.9	27	16	71	10	31
DeVonta Smith	41.9	13.8	0.00	-0.22	10.9	23	27	70	5	31
Mike Williams	42.2	13.5	0.00	4.01	-0.7	24	27	11	64	32
Josh Reynolds	39.8	11.2	0.00	3.66	2.8	47	27	14	40	32
Jerry Jeudy	38.3	15.1	0.03	-0.87	5.1	16	15	73	25	32
Brandon Aiyuk	40.3	12.9	0.00	1.82	3.9	29	27	46	32	34
Parris Campbell	39.2	10.0	0.12	1.25	10.4	76	3	51	7	34
Rashid Shaheed	41.6	15.0	0.00	0.23	4.3	17	27	68	30	36
Chris Godwin	40.7	11.8	0.02	-1.75	14.4	41	19	82	1	36
Garrett Wilson	40.6	12.4	0.04	-2.04	6.7	32	12	85	16	36
Jakobi Meyers	39.3	13.9	-0.01	3.37	4.2	22	73	23	31	37
A.J. Brown	41.9	16.4	-0.07	0.94	13.6	6	84	57	2	37
Treylon Burks	45.0	14.9	0.00	-0.16	3.1	18	27	69	37	38
Laviska Shenault Jr.	38.3	17.3	-0.12	3.03	3.7	3	95	24	33	39
Stefon Diggs	42.0	16.3	-0.05	0.87	10.8	7	80	62	6	39
Michael Pittman Jr.	39.2	12.0	-0.07	4.06	4.4	35	83	10	28	39
Jauan Jennings	39.7	10.5	0.00	3.54	1.4	65	27	17	48	39
Julio Jones	41.0	10.7	0.05	0.90	4.3	59	10	59	29	39
Zay Jones	40.9	10.2	0.02	3.62	0.1	72	20	15	59	42
Tutu Atwell	41.7	13.2	0.00	-1.18	3.5	26	27	80	35	42
Tre’Quan Smith	39.3	11.5	-0.07	3.54	5.3	45	82	18	24	42
D.J. Moore	39.1	12.0	0.05	-0.92	1.3	36	9	76	50	43
George Pickens	42.5	10.8	0.00	1.76	2.0	57	24	47	43	43
Nelson Agholor	39.4	10.8	0.05	1.13	0.9	56	11	52	53	43
Tyler Boyd	40.3	12.0	-0.08	3.00	4.9	38	85	25	26	44
Donovan Peoples-Jones	40.9	10.3	0.01	2.01	1.5	69	22	39	46	44
Michael Gallup	41.8	12.2	0.00	1.92	-2.3	34	26	41	76	44
Trent Sherfield	39.8	9.6	0.00	3.99	-0.1	83	27	12	61	46
Mike Evans	41.0	11.2	-0.08	2.81	5.9	48	87	28	20	46
Byron Pringle	56.8	16.3	-0.02	0.89	2.9	8	75	61	39	46
DeAndre Hopkins	41.2	15.3	-0.12	0.31	7.7	14	92	66	12	46
Terrace Marshall Jr.	39.3	10.1	0.00	3.39	-0.3	75	27	22	62	47
Curtis Samuel	39.1	10.8	0.04	-1.98	3.7	55	14	84	34	47
Marquise Brown	41.2	12.9	0.00	-3.29	2.5	28	27	90	42	47
Jahan Dotson	40.5	12.4	0.01	-1.84	1.2	33	21	83	51	47
Christian Kirk	40.6	10.4	0.00	0.89	3.3	68	25	60	36	47
Mack Hollins	39.4	9.7	0.00	4.66	-1.6	82	27	8	72	47
Noah Brown	41.8	11.0	0.00	2.62	-2.3	53	27	32	77	47
Allen Lazard	38.8	11.0	-0.05	6.00	0.5	54	79	2	56	48
Josh Palmer	42.1	11.5	0.00	2.31	-4.0	43	27	34	87	48
Sammy Watkins	42.1	10.0	0.13	1.88	-1.4	78	2	42	70	48
Brandin Cooks	38.6	11.1	0.00	-0.96	2.8	52	27	77	41	49
Marquez Valdes-Scantling	41.9	9.0	0.01	4.67	-3.6	86	23	7	82	50
Gabriel Davis	41.8	11.2	-0.12	3.51	3.0	51	93	20	38	51
Van Jefferson	39.8	10.2	0.00	2.16	-0.9	73	27	37	68	51
JuJu Smith-Schuster	58.5	16.8	-0.03	1.47	-1.9	4	78	50	73	51
Equanimeous St. Brown	40.9	9.9	-0.02	4.78	1.7	80	77	4	45	52
Romeo Doubs	37.2	10.3	0.00	2.85	-3.6	70	27	27	83	52
Adam Thielen	39.4	10.6	0.00	2.25	-3.7	62	27	35	84	52
Demarcus Robinson	41.8	12.0	-0.02	1.74	1.4	37	74	48	49	52
Greg Dortch	40.7	12.7	0.00	-5.07	0.1	30	27	94	58	52
Alec Pierce	43.9	11.5	-0.02	2.63	-0.8	44	76	30	67	54
Corey Davis	37.6	9.4	0.00	1.03	1.2	85	27	54	52	55
Damiere Byrd	40.1	11.9	0.00	-4.20	-0.1	40	27	93	60	55
Marvin Jones Jr.	40.8	7.6	0.00	3.59	-3.9	91	27	16	86	55
Keenan Allen	41.9	14.7	-0.16	2.70	-2.9	19	96	29	79	56
Courtland Sutton	39.1	10.7	-0.08	3.43	-0.8	60	86	21	65	58
Dante Pettis	42.0	10.2	0.00	0.56	-1.4	71	27	64	71	58
Isaiah Hodgins	35.0	10.0	-0.11	4.76	-0.8	77	91	5	66	60
Nick Westbrook-Ikhine	40.4	10.5	0.00	0.36	-3.3	66	27	65	81	60
Justin Watson	35.7	6.9	0.00	2.62	-7.2	93	27	31	92	61
Robert Woods	40.1	10.5	0.00	-2.14	-0.4	67	27	86	63	61
Hunter Renfrow	39.4	11.2	0.00	-1.12	-4.0	50	27	78	88	61
Richie James Jr.	43.9	12.7	-0.01	-2.82	0.8	31	72	88	54	61
Quez Watkins	41.5	9.9	-0.10	0.61	7.4	79	89	63	14	61
Darius Slayton	40.1	10.8	0.00	1.84	-2.0	58	70	45	74	62
Olamide Zaccheaus	40.3	11.2	0.00	-5.98	-2.2	49	27	96	75	62
Brandon Powell	32.6	10.1	0.00	-3.50	0.3	74	27	91	57	62
Laquon Treadwell	39.7	5.7	0.00	2.21	-8.1	96	27	36	94	63
Marquise Goodwin	39.5	9.6	0.12	-2.58	-3.7	84	5	87	85	65
Phillip Dorsett	38.8	8.0	0.00	-0.89	-2.3	88	27	74	78	67
K.J. Osborn	39.4	9.8	0.00	0.24	-7.6	81	27	67	93	67
Elijah Moore	37.9	8.0	0.00	-3.99	-1.2	89	27	92	69	69
Ray-Ray McCloud III	39.8	8.1	0.00	-1.17	-6.3	87	27	79	91	71
Diontae Johnson	40.7	10.6	-0.09	-2.84	1.4	63	88	89	47	72
Isaiah McKenzie	41.7	10.6	-0.01	-1.60	-3.3	64	71	81	80	74
David Bell	37.9	6.0	-0.12	2.95	-5.2	95	94	26	90	76
Marquez Callaway	39.4	7.8	-0.10	1.97	-5.1	90	90	40	89	77
Steven Sims	29.4	6.4	0.00	-5.20	-15.6	94	27	95	96	78
Freddie Swain	39.2	7.0	-0.05	-0.90	-9.9	92	81	75	95	86

*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 17, 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 6 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 3 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
Justin Jefferson	62%	72%	59%	71%	10%	12%	Packers	17%	6%	2%	1%	3%
Curtis Samuel	37%	-3%	30%	17%	-40%	-14%	Browns	-5%	-1%	2%	0%	2%
Chris Godwin	19%	42%	25%	16%	23%	-9%	Panthers	6%	-7%	1%	1%	2%
Ben Skowronek	15%	27%	13%	26%	13%	14%	Chargers	3%	9%	0%	1%	2%
Elijah Moore	29%	14%	24%	18%	-16%	-6%	Seahawks	-9%	-4%	1%	0%	2%
DeVante Parker	31%	49%	33%	22%	19%	-11%	Dolphins	11%	4%	2%	0%	2%
Romeo Doubs	5%	29%	11%	12%	24%	1%	Vikings	-6%	-14%	-2%	0%	-2%
K.J. Osborn	11%	3%	8%	5%	-8%	-4%	Packers	17%	6%	-1%	0%	-2%
Michael Pittman Jr.	35%	36%	36%	25%	1%	-12%	Giants	16%	16%	0%	-2%	-2%
Jakobi Meyers	37%	19%	30%	30%	-18%	0%	Dolphins	11%	4%	-2%	0%	-2%
Demarcus Robinson	27%	15%	25%	11%	-12%	-15%	Steelers	5%	9%	-1%	-1%	-2%
Marquise Brown	22%	46%	23%	33%	25%	10%	Falcons	-7%	-3%	-2%	0%	-2%
Equanimeous St. Brown	26%	15%	29%	8%	-11%	-21%	Lions	9%	6%	-1%	-1%	-2%
Nick Westbrook-Ikhine	26%	16%	31%	4%	-10%	-26%	Cowboys	1%	9%	0%	-2%	-2%
Darius Slayton	47%	68%	46%	48%	21%	1%	Colts	-12%	2%	-3%	0%	-2%
Garrett Wilson	31%	54%	34%	54%	23%	21%	Seahawks	-9%	-4%	-2%	-1%	-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 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 17

*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)

DeVante Parker

Parker comes into the week with an interesting schematic advantage, amplified by an inverse finding applied to fellow Patriot WR Jakobi Meyers (that our models are relatively fading this week). Parker has proven to be the Patriots QB WR of choice when faced with the blitz. Parker sees a 49% target share (compared to 31% without a blitz), which is enticing as he faces the Dolphins this week, that blitz 11% points more than the league average. As noted, what makes this play even stronger, is the additional “layer of evidence” we see in the fact that “typical target share king” Jakobi Meyers has an inverse relationship when blitzed, seeing a 37% target share when NOT blitzed, but only 19% when blitzed. In other words, from a predictive standpoint, it’s fairly easy to point to targets “typically” going Meyer’s way, which are re-routed to Parker when blitzed.

Tee Higgins

Higgins is another WR we have keyed in on for multiple weeks this season (which is usually a good sign, meaning we have a “feel for what variables correlate to his fantasy success”). For this week, our base model really likes Higgins’ individual matchup. Coming in at our “best” matchup overall for the week, the veteran WR has all 4 indicators pointing up, including BOTH advanced analytic plays. This is especially true for his net PFF (weighted) grade for the week. We expect Higgins to face a few different cover men on the week. Still, the majority of snaps should be against Tre’Davious White (43% pass snaps), who, despite being considered a quality DB, has only a 58.1 PFF Grade vs. Higgins’ 80.4.

WR Matchups to Avoid in Week 17

Darius Slayton

Slayton is another “frequent flier” on our start/sit lists, but typically in the other direction. Here, our secondary model does not like his schematic splits relating to the defense bringing the blitz. All accidental rhyming aside, despite Slayton having healthy target shares in almost any circumstance, relatively speaking, he sees his “monster shares” vs. the Blitz (68% vs. 47%). And given the Colts have one of the league’s lowest blitz rates (12 percentage points below league average), for a WR that has been relatively “boom or bust” of late, we are fading him this week.

Michael Pittman Jr

It’s hard to make a case for another WR that has fallen so far from the top during his early season fantasy success than Pittman. Along that overall trend, our base model does not like his “physical matchup” this week. Specifically his matchup vs. CB Faian Moreau. With an expected 37% of his pass snaps going up against Moreau, it’s tough to see Pittman gaining much separation with his 4.52 40 going up against Moreau’s 4.35. Take this along with a slight schematic disadvantage (see secondary chart), and we’re keeping Pittman on the bench this week.

Marquise Brown

Not bragging, but after back-to-back weeks spotting a DeAndre Hopkins fade, we feel we’ve gained some insight into what makes the Cardinals WRs produce. This is particularly this weekend when you consider the potential scheme Brown’s likely to face. Brown more than doubles his target share from 22% to 46% when blitzed. This is not great for the downfield speedster, as the Falcons send the house 7 percentage points less than the league average.

Hopefully, this data helps you build the ideal lineup to propel you through the championship weeks!

See you all next week.

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