Fantasy Points Data (@fantasyptsdata) 's Twitter Profile
Fantasy Points Data

@fantasyptsdata

Data & Research Department of @FantasyPts | Premium Stats & Tools | data.fantasypoints.com

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calendar_today07-04-2022 20:38:53

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Fantasy Points Data (@fantasyptsdata) 's Twitter Profile Photo

Zach Ertz is dusty. But he’s always been/still is a great separator. Last year, Ertz ranked 2nd-best among TEs in ASS (0.129) In 20 full games with Kliff Kingsbury, Ertz has averaged: +7.5 targets (~TE4) +12.0 FPG (~TE8) He’s a free early-season streamer.

Fantasy Points Data (@fantasyptsdata) 's Twitter Profile Photo

The Packers ran the 5th-most single high looks last year (61.2%). New DC Jeff Hafley heavily utilized them at Boston College. A.J. Brown against single high last year had a: +45% boost in first-read target share (42.2%, ~WR1) +85% boost in fantasy points/route (0.72, ~WR2)

Ryan Heath (@ryanj_heath) 's Twitter Profile Photo

My latest: Average Separation Score stats that will blow your mind. +Kenny Pickett ignored open receivers more than any other QB last year +Garrett Wilson was responsible for a whopping 44% of the Jets’ separation wins +Sleepers you can STILL add fantasypoints.com/nfl/articles/2…

Fantasy Points Data (@fantasyptsdata) 's Twitter Profile Photo

"How good of a stat is Average Separation Score? Does it actually line up with the eye test/who is good?" Don't ask us. Ask NFL decision-makers. The bottom-10 was littered with players who lost their jobs:

"How good of a stat is Average Separation Score? Does it actually line up with the eye test/who is good?"

Don't ask us. Ask NFL decision-makers.

The bottom-10 was littered with players who lost their jobs:
Ryan Heath (@ryanj_heath) 's Twitter Profile Photo

We cashed on Rashee last night. Tonight, I am taking A.J. Brown OVER 71.5 receiving yards against what’s likely to be a single-high heavy defense. These Fantasy Points Data stats are crazy 👀

Fantasy Points Data (@fantasyptsdata) 's Twitter Profile Photo

Rashee Rice by Route Type [Week 1] Slant: 6 targets, 94 yards Out: 1 target, 8 yards Screen: 1 target, 1 yard Other: 0 targets, 0 yards 18% of Rice's routes came on the slant. CeeDee Lamb (16.2%) was the only WR over 14% last year. Is Rashee Rice the new Michael Thomas?

Rashee Rice by Route Type [Week 1]

Slant: 6 targets, 94 yards
Out: 1 target, 8 yards
Screen: 1 target, 1 yard
Other: 0 targets, 0 yards

18% of Rice's routes came on the slant. CeeDee Lamb (16.2%) was the only WR over 14% last year.

Is Rashee Rice the new Michael Thomas?
Fantasy Points Data (@fantasyptsdata) 's Twitter Profile Photo

Ravens Receiving Yards + minus checkdowns and designed targets Isaiah Likely: 102 Rashod Bateman: 53 Zay Flowers: 23 Mark Andrews: 14 Nelson Agholor: 6 Justice Hill: 1

Fantasy Points Data (@fantasyptsdata) 's Twitter Profile Photo

Ravens OL was horrible against the pass last night. Lamar Jackson was under pressure on 47% of his dropbacks. But (silver lining) they weren't terrible on the ground. Derrick Henry averaged 1.77 YBC/A last night, much better than his numbers with Tennessee last year (1.11)

Fantasy Points Data (@fantasyptsdata) 's Twitter Profile Photo

Bengals WR Andrei Iosivas: +30th of 144 qualifying WRs in average separation score (0.137) +19th of 168 qualifiers on slot routes (0.182) +Has clearly won the Bengals’ WR3 role over Jermaine Burton +Year 2 breakout appeal on a top-5 offense

Bengals WR Andrei Iosivas:

+30th of 144 qualifying WRs in average separation score (0.137)

+19th of 168 qualifiers on slot routes (0.182)

+Has clearly won the Bengals’ WR3 role over Jermaine Burton

+Year 2 breakout appeal on a top-5 offense
Scott Barrett (@scottbarrettdfb) 's Twitter Profile Photo

Notes from the Fantasy Points Data film experts: + Likely feasted on checkdowns and underneath routes. He ran a lot of routes that would typically earn a zero grade from us (not asking/requiring the receiver to separate) + Andrews was running real downfield routes, and not a lot of

Scott Barrett (@scottbarrettdfb) 's Twitter Profile Photo

2023 WR Leaders by Win Share aka Route Win Rate Market Share 1. Garrett Wilson (44.3%) 2. Diontae Johnbson (42.6%) 3. Drake London (42.3%) 4. DeAnde Hopkins (41.5) ... 40. Rashod Bateman (32.7%) H/T: Fantasy Points Data

Scott Barrett (@scottbarrettdfb) 's Twitter Profile Photo

Instances where two TEs on the same team ran >30 routes in the same game: 2024: 1 (Ravens with Andrews/Likely) 2023: 4 (Falcons twice, Patriots twice) 2022: 1 (Giants once) It's so rare to find a team capable of supporting two fantasy-relevant TEs. The only real examples are

Ryan Heath (@ryanj_heath) 's Twitter Profile Photo

A lot of you have been asking me: how can I get an edge from the Fantasy Points Data Suite? My answer: ADVANCED MATCHUPS WEEK 1 IS LIVE - Contrarian DFS plays - Matchup and scheme-informed prop bets *Updated for Higgins and Chase looking shaky to play* fantasypoints.com/nfl/articles/2…

Jacob Gibbs (@jagibbs_23) 's Twitter Profile Photo

Here, you can see exactly how this Jets defense differs from the rest of the league. You also can see how cool what Fantasy Points Data is offering is! Jets defense in 2023: - League-low target rate to out-wide receivers - League-low opponent first-read target share - 8th highest

Here, you can see exactly how this Jets defense differs from the rest of the league.

You also can see how cool what <a href="/FantasyPtsData/">Fantasy Points Data</a> is offering is!

Jets defense in 2023:
- League-low target rate to out-wide receivers
- League-low opponent first-read target share
- 8th highest
Jacob Gibbs (@jagibbs_23) 's Twitter Profile Photo

Thursday night football first-read target rates, per Fantasy Points Data: 38% — Rashee Rice 35% — Isaiah Likely 30% — Zay Flowers 14% — Xavier Worthy 14% — Travis Kelce 10% — Isiah Pacheco 10% — Samaje Perine 10% — Noah Gray 9% — Justice Hill 9% — Rashod Bateman 9% — Mark Andrews

Thomas Tipple (@elnostrathomas) 's Twitter Profile Photo

In the words of Ryan Heath, it’s “a quantifiable, film-based evaluation of how well each player executed on their routes in 2024, supplying a data point entirely free from the influence of QB play and target competition.”