WR vs. CB Matchups & Advice: Week 13 (2022 Fantasy Football)
Another crazy week in the NFL, and here we go at another attempt trying to predict the NEARLY unpredictable. Weekly readers will likely jump straight to the charts/our picks, but if you are new to this piece (as we have picked up some steam of late), here is what you are looking at: leveraging advanced data, our models 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. We’ve been on fire lately and hope we help you towards a winning week.
Week 12 Results:
Another week, another winning board. We are especially proud of the call on Jauan Jennings, and have a couple similar plays for this week!
*Got hurt, not super fair…
Season Scored Card
Season Record: 45-28
*All stats based on Yahoo Fantasy Football ½ PPR
Week 13 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.|
|Amon-Ra St. Brown||38.3||16.5||0.00||3.01||20.8||8||29||26||1||16|
|D.J. Chark Jr.||39.0||11.1||0.07||4.03||0.4||53||9||14||61||34|
|Michael Pittman Jr.||39.0||12.8||-0.08||3.66||3.3||30||83||17||41||43|
|Equanimeous St. Brown||40.8||9.2||0.01||5.45||-2.3||77||25||3||79||46|
|Richie James Jr.||40.0||9.7||0.02||-0.52||5.4||72||22||69||22||46|
|Marvin Jones Jr.||39.8||10.3||0.00||1.69||0.3||66||29||44||62||50|
*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)
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 13, 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 goaline (and from 0-10 yardline) 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 middle section) a 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
|WR Details||WR Target Ownership Splits||Opponent Blitz/No Blitz & Man/Zone Splits||Net WR vs Opp expected value|
|Player||Team||no blitz %||BLITZ %||Blitz Bonus||zone %||MAN %||Man Bonus||W12 Opp||BLITZ Rate||BR > Avg||MAN RATE||MR>Avg||“Blitz” Bonus||“Man” Bonus||Total “bump”|
*Thanks to our friends at Sports Info Solutions, and their SIS Database for the info!
WR Matchups to Target in Week 13
*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)
- Corey Davis
Although it is a “supplemental” model, we’ve had a lot of success the last few weeks focusing on “coverage/blitz type splits”, and Davis has the strongest we’ve seen yet. In 2022, Davis basically does not get targeted when it’s man coverage. Yet, sees a 30% target share vs. zone, and the Vikings play zone 17% points (88%) more than the league average.
- Darius Slayton
Astute readers have noticed our pattern in the last few weeks, and Slayton fits the mold: “multiple models” pointing towards the same likely strong game. Slayton has a 25% target share when the Giants face zone, but a 36% share vs. man coverage. His opponent, the Commanders, play Man coverage 34% of pass snaps (or 5% points MORE than the league average). Couple that with a strong matchup, mainly due to a speed advantage (19th best of the week), which is mostly weighted from the pass snaps he will see against Bobby McCain (4.51 40-yard dash vs 4.39 for 23% of pass snaps expected), you have a recipe for a “boom” week.
- Marquez Valdes-Scantling
MVS has been a tough weekly play due to his inconsistency. However, we think we may have a few predictive variables that indicate the likelihood of a solid outing from the veteran WR. Valdes-Scantling is another of these “anomalies” we’ve seen that essentially do NOT get targeted when an opponent blitzes (31% target share vs 0%, seriously). Given that the Bengals blitz only 17% of the time (6% points less than the league average) our supplemental model likes MVS this week. His 76 inches of height also gives him more than 3 inches on both likely cover men Eli Apple (73 inches 36% snaps) and Mike Hilton (69 inches, 35% snaps).
WR Matchups to Avoid in Week 13
- Jerry Jeudy
Jeudy has a legitimate Man vs Zone target share split: 37% vs. Man and 16% vs Zone. This does not fare well for the young WR, as the Raiders run man 7% points less Man coverage than the league average. He also comes in with our base model’s 6th worst projection for the week. This mostly has to do with a league-low, net-weighted PFF grade based (mostly) on the 74% of expected coverage snaps he will see against 78.6 PFF-graded Malon Humphrey (vs. his own 69.2).
- AJ Brown
I will be the first to admit, it’s very tough to put Brown on ANY “do not start list” in 2022, yet our models do not like him in week 13. Yes, his overall matchup grade this week is “not terrible” (27th), BUT that is the lowest we have seen from the young star this year (mainly due to the speed the titans have to match/beat his own 4.5 40). Additionally, we’ve noticed although Brown demands a healthy target share regardless when defenses play “vanilla” (zone/no blitz) his rates dip a bit comparatively. Take his target share vs the blitz alone: he’s demanding a whopping 61% (vs 37% when NOT blitzed) when the defense brings 5+. Yet, his opponent, AND FORMER team (looking for some revenge) blitz only 10% of the time (and plays 4% points less man than the league average), meaning the chance for an explosive play (or two) out of Brown is less likely than usual.
We all know how critical these last couple weeks are for those fighting for playoff spots for their respective fantasy leagues, and hope this data helps bring you home a “W”!