FantasyOutsiders

2026 NFL usage report

Week 8 usage report

Covers weeks 1–8 in full, plus week 9 so far (14 of 15 games played). 102 talking points, each drawn from recorded game data and dated injury reports. Values marked Est. are FFO model estimates. Each card describes the weeks shown on that card, which may be older than this report's last week. Injury context is historical; check current team reports before making a lineup decision.

2026 season · Weeks 1–9 · Report built

Showing the saved fallback report. The latest report could not be confirmed; use the coverage and build date shown here.

Historical game data. Injury designations apply only to their stated report week; confirm current availability before setting a lineup.

The shortlist

The highest-ranked observations in this report, at most two of each kind. Their reporting windows can differ.

Jahmyr Gibbs

RBDETRed-zone role

Jahmyr Gibbs has 53 of DET's 105 red-zone opportunities (50%), including 15 carries inside the 5.

Red-zone opportunities
53
Team red-zone opportunities
105
Red-zone share
50%
Carries inside the 5
15

Observed: Weeks 1–5 and 7–9 · 8 games

Michael Wilson

WRARITouchdowns below usage

Michael Wilson has scored 2 touchdowns on modeled targets and carries that usually produce 9.2, per FFO's expected-points model.

Touchdowns
2
Expected touchdownsEst.
9.2
Expected PPR per gameEst.
19.8
PPR vs expected, per gameEst.
−6.4

Observed: Weeks 1–9 · 9 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Kenneth Walker III

RBKCRed-zone role

Kenneth Walker III has 43 of KC's 83 red-zone opportunities (52%), including 15 carries inside the 5.

Red-zone opportunities
43
Team red-zone opportunities
83
Red-zone share
52%
Carries inside the 5
15

Observed: Weeks 1–4 and 6–9 · 8 games

Tyler Allgeier

RBARIRole up

Tyler Allgeier's share of ARI carries rose to 94% in week 9 (17 carries), from 35% in weeks 1-8.

Carry share, week 9
94%
Carries, week 9
17
Carry share, weeks 1–8
35%

Observed: Weeks 1–9 · 9 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Jaxon Smith-Njigba

WRSEATouchdowns above usage

Jaxon Smith-Njigba has scored 9 touchdowns on modeled targets and carries that usually produce 5.2, per FFO's expected-points model.

Touchdowns
9
Expected touchdownsEst.
5.2
Expected PPR per gameEst.
19.5
PPR vs expected, per gameEst.
+6.3

Observed: Weeks 1–9 · 9 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Kyle Monangai

RBCHIRole up

Kyle Monangai's share of CHI carries rose to 56% in week 4 (30 carries), from 29% in weeks 1-3.

Carry share, week 4
56%
Carries, week 4
30
Carry share, weeks 1–3
29%

Observed: Weeks 1–4 · 4 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

DK Metcalf

WRPITVolume, not production

DK Metcalf has 38% of PIT's air yards but is scoring 4.7 PPR points a game below what that usage usually produces.

Air-yards share
38%
Targets
64
PPR vs expected, per gameEst.
−4.7

Observed: Weeks 1–8 · 8 games

Adonai Mitchell

WRNYJVolume, not production

Adonai Mitchell has 50% of NYJ's air yards but is scoring 3.6 PPR points a game below what that usage usually produces.

Air-yards share
50%
Targets
34
PPR vs expected, per gameEst.
−3.6

Observed: Weeks 1–2 and 7–9 · 5 games

Tee Higgins

WRCINTouchdowns above usage

Tee Higgins has scored 6 touchdowns on modeled targets and carries that usually produce 2.8, per FFO's expected-points model.

Touchdowns
6
Expected touchdownsEst.
2.8
Expected PPR per gameEst.
14.8
PPR vs expected, per gameEst.
+5.2

Observed: Weeks 1–5 and 7–9 · 8 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Malik Nabers

WRNYGTouchdowns below usage

Malik Nabers has scored 2 touchdowns on modeled targets and carries that usually produce 4.5, per FFO's expected-points model.

Touchdowns
2
Expected touchdownsEst.
4.5
Expected PPR per gameEst.
17.5
PPR vs expected, per gameEst.
−1.3

Observed: Weeks 1–7 and 9 · 8 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Drew Lock

QBSEAQB efficiency

Drew Lock is at +0.35 EPA per dropback over 78 dropbacks, 1st of 41 QBs with 50+.

EPA rank
1 of 41 qualified QBs
EPA per dropback
+0.35
Dropbacks
78

Observed: Weeks 1–2 and 9 · 3 games

Carnell Tate

WRTENRookie role

Rookie Carnell Tate has a 26% target share through 7 games.

Target share
26%
Targets
51

Observed: Weeks 1–7 · 7 games

Volume, not production

Michael Wilson

WRARIVolume, not production

Michael Wilson has 37% of ARI's air yards but is scoring 6.4 PPR points a game below what that usage usually produces.

Air-yards share
37%
Targets
88
PPR vs expected, per gameEst.
−6.4

Observed: Weeks 1–9 · 9 games

DK Metcalf

WRPITVolume, not production

DK Metcalf has 38% of PIT's air yards but is scoring 4.7 PPR points a game below what that usage usually produces.

Air-yards share
38%
Targets
64
PPR vs expected, per gameEst.
−4.7

Observed: Weeks 1–8 · 8 games

Adonai Mitchell

WRNYJVolume, not production

Adonai Mitchell has 50% of NYJ's air yards but is scoring 3.6 PPR points a game below what that usage usually produces.

Air-yards share
50%
Targets
34
PPR vs expected, per gameEst.
−3.6

Observed: Weeks 1–2 and 7–9 · 5 games

A.J. Brown

WRNEVolume, not production

A.J. Brown has 35% of NE's air yards but is scoring 5.3 PPR points a game below what that usage usually produces.

Air-yards share
35%
Targets
20
PPR vs expected, per gameEst.
−5.3

Observed: Weeks 1 and 6–7 · 3 games

Emeka Egbuka

WRTBVolume, not production

Emeka Egbuka has 31% of TB's air yards but is scoring 3.0 PPR points a game below what that usage usually produces.

Air-yards share
31%
Targets
54
PPR vs expected, per gameEst.
−3.0

Observed: Weeks 1–6 and 9 · 7 games

Role up

Tyler Allgeier

RBARIRole up

Tyler Allgeier's share of ARI carries rose to 94% in week 9 (17 carries), from 35% in weeks 1-8.

Carry share, week 9
94%
Carries, week 9
17
Carry share, weeks 1–8
35%

Observed: Weeks 1–9 · 9 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Kyle Monangai

RBCHIRole up

Kyle Monangai's share of CHI carries rose to 56% in week 4 (30 carries), from 29% in weeks 1-3.

Carry share, week 4
56%
Carries, week 4
30
Carry share, weeks 1–3
29%

Observed: Weeks 1–4 · 4 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Devin Singletary

RBNYGRole up

Devin Singletary's share of NYG carries rose to 68% in week 9 (21 carries), from 16% in weeks 1-7.

Carry share, week 9
68%
Carries, week 9
21
Carry share, weeks 1–2 and 6–7
16%

Observed: Weeks 1–2, 6–7 and 9 · 5 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

CeeDee Lamb

WRDALRole up

CeeDee Lamb's target share rose to 47% in week 9 (16 targets), from 31% in weeks 1-8.

Target share, week 9
47%
Targets, week 9
16
Target share, weeks 1–8
31%
Targets, weeks 1–8
92

Observed: Weeks 1–9 · 9 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Jonah Coleman

RBDENRole up

Jonah Coleman's share of DEN carries rose to 63% in week 9 (17 carries), from 39% in weeks 2-8.

Carry share, week 9
63%
Carries, week 9
17
Carry share, weeks 2 and 7–8
39%

Observed: Weeks 2 and 7–9 · 4 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Ja'Marr Chase

WRCINRole up

Ja'Marr Chase's target share rose to 43% in week 9 (12 targets), from 23% in weeks 1-8.

Target share, week 9
43%
Targets, week 9
12
Target share, weeks 1–5 and 7–8
23%
Targets, weeks 1–5 and 7–8
61

Observed: Weeks 1–5 and 7–9 · 8 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Puka Nacua

WRLARole up

Puka Nacua's target share rose to 46% in week 9 (19 targets), from 34% in weeks 1-8.

Target share, week 9
46%
Targets, week 9
19
Target share, weeks 1 and 4–8
34%
Targets, weeks 1 and 4–8
74

Observed: Weeks 1 and 4–9 · 7 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Ollie Gordon II

RBMIARole up

Ollie Gordon II's share of MIA carries rose to 76% in week 9 (16 carries), from 52% in weeks 2-8.

Carry share, week 9
76%
Carries, week 9
16
Carry share, weeks 2–5 and 7–8
52%

Observed: Weeks 2–5 and 7–9 · 7 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Omar Cooper Jr.

WRNYJRole up

Omar Cooper Jr.'s target share rose to 37% in week 9 (11 targets), from 16% in weeks 1-7.

Target share, week 9
37%
Targets, week 9
11
Target share, weeks 1 and 6–7
16%
Targets, weeks 1 and 6–7
13

Observed: Weeks 1, 6–7 and 9 · 4 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Chris Olave

WRNORole up

Chris Olave's target share rose to 38% in week 9 (12 targets), from 27% in weeks 1-7.

Target share, week 9
38%
Targets, week 9
12
Target share, weeks 1–7
27%
Targets, weeks 1–7
71

Observed: Weeks 1–7 and 9 · 8 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Garrett Wilson

WRNYJRole up

Garrett Wilson's target share rose to 39% in week 8 (12 targets), from 26% in weeks 1-7.

Target share, week 8
39%
Targets, week 8
12
Target share, weeks 1–7
26%
Targets, weeks 1–7
51

Observed: Weeks 1–8 · 8 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Tank Bigsby

RBPHIRole up

Tank Bigsby's share of PHI carries rose to 52% in week 4 (14 carries), from 18% in weeks 1-3.

Carry share, week 4
52%
Carries, week 4
14
Carry share, weeks 1–3
18%

Observed: Weeks 1–4 · 4 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Tank Dell

WRHOURole up

Tank Dell's target share rose to 24% in week 9 (9 targets), from 4% in week 7.

Target share, week 9
24%
Targets, week 9
9
Target share, week 7
4%
Targets, week 7
1

Observed: Weeks 7 and 9 · 2 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Caleb Douglas

WRMIARole up

Caleb Douglas's target share rose to 38% in week 9 (8 targets), from 19% in weeks 1-8.

Target share, week 9
38%
Targets, week 9
8
Target share, weeks 1–2 and 7–8
19%
Targets, weeks 1–2 and 7–8
19

Observed: Weeks 1–2 and 7–9 · 5 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Bijan Robinson

RBATLRole up

Bijan Robinson's target share rose to 26% in week 9 (7 targets), from 15% in weeks 1-8.

Target share, week 9
26%
Targets, week 9
7
Target share, weeks 1–8
15%
Targets, weeks 1–8
33

Observed: Weeks 1–9 · 9 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Shedeur Sanders

QBCLERole up

Shedeur Sanders's share of CLE carries rose to 29% in week 9 (10 carries), from 0% in weeks 3-8.

Carry share, week 9
29%
Carries, week 9
10
Carry share, weeks 3 and 8
0%

Observed: Weeks 3 and 8–9 · 3 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Tyquan Thornton

WRKCRole up

Tyquan Thornton's target share rose to 30% in week 4 (8 targets), from 8% in weeks 1-3.

Target share, week 4
30%
Targets, week 4
8
Target share, weeks 1–3
8%
Targets, weeks 1–3
7

Observed: Weeks 1–4 · 4 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Darren Waller

TECARRole up

Darren Waller's target share rose to 27% in week 9 (10 targets), from 10% in weeks 1-8.

Target share, week 9
27%
Targets, week 9
10
Target share, weeks 1–4 and 6–8
10%
Targets, weeks 1–4 and 6–8
25

Observed: Weeks 1–4 and 6–9 · 8 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Samaje Perine

RBCINRole up

Samaje Perine's share of CIN carries rose to 46% in week 9 (11 carries), from 23% in weeks 1-8.

Carry share, week 9
46%
Carries, week 9
11
Carry share, weeks 1–5 and 7–8
23%

Observed: Weeks 1–5 and 7–9 · 8 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Van Jefferson

WRWASRole up

Van Jefferson's target share rose to 21% in week 9 (7 targets), from 4% in week 8.

Target share, week 9
21%
Targets, week 9
7
Target share, week 8
4%
Targets, week 8
1

Observed: Weeks 8–9 · 2 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Darius Cooper

WRPHIRole up

Darius Cooper's target share rose to 24% in week 9 (8 targets), from 12% in weeks 2-8.

Target share, week 9
24%
Targets, week 9
8
Target share, weeks 2 and 4–8
12%
Targets, weeks 2 and 4–8
24

Observed: Weeks 2 and 4–9 · 7 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Courtland Sutton

WRDENRole up

Courtland Sutton's target share rose to 26% in week 9 (9 targets), from 16% in weeks 1-8.

Target share, week 9
26%
Targets, week 9
9
Target share, weeks 1–8
16%
Targets, weeks 1–8
37

Observed: Weeks 1–9 · 9 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Cade Otton

TETBRole up

Cade Otton's target share rose to 27% in week 9 (8 targets), from 15% in weeks 1-7.

Target share, week 9
27%
Targets, week 9
8
Target share, weeks 1–7
15%
Targets, weeks 1–7
30

Observed: Weeks 1–7 and 9 · 8 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Isaiah Bond

WRCLERole up

Isaiah Bond's target share rose to 22% in week 5 (7 targets), from 3% in weeks 2-4.

Target share, week 5
22%
Targets, week 5
7
Target share, weeks 2 and 4
3%
Targets, weeks 2 and 4
2

Observed: Weeks 2 and 4–5 · 3 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Gunnar Helm

TETENRole up

Gunnar Helm's target share rose to 23% in week 8 (9 targets), from 10% in weeks 1-7.

Target share, week 8
23%
Targets, week 8
9
Target share, weeks 1–5 and 7
10%
Targets, weeks 1–5 and 7
17

Observed: Weeks 1–5 and 7–8 · 7 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Role down

Chase Brown

RBCINRole down

Chase Brown's share of CIN carries fell to 38% in week 9 (9 carries), from 61% in weeks 1-8.

Carry share, week 9
38%
Carries, week 9
9
Carry share, weeks 1–5 and 7–8
61%

Observed: Weeks 1–5 and 7–9 · 8 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Jeremiyah Love

RBARIRole down

Jeremiyah Love's share of ARI carries fell to 33% in week 8 (9 carries), from 55% in weeks 1-5.

Carry share, week 8
33%
Carries, week 8
9
Carry share, weeks 1–5
55%

Observed: Weeks 1–5 and 8 · 6 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Braelon Allen

RBNYJRole down

Braelon Allen's share of NYJ carries fell to 32% in week 9 (8 carries), from 54% in weeks 1-8.

Carry share, week 9
32%
Carries, week 9
8
Carry share, weeks 1–8
54%

Observed: Weeks 1–9 · 9 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Tetairoa McMillan

WRCARRole down

Tetairoa McMillan's target share fell to 16% in week 9 (6 targets), from 26% in weeks 1-8.

Target share, week 9
16%
Targets, week 9
6
Target share, weeks 1–4 and 6–8
26%
Targets, weeks 1–4 and 6–8
65

Observed: Weeks 1–4 and 6–9 · 8 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Drake London

WRATLRole down

Drake London's target share fell to 19% in week 9 (5 targets), from 29% in weeks 1-8.

Target share, week 9
19%
Targets, week 9
5
Target share, weeks 1–8
29%
Targets, weeks 1–8
62

Observed: Weeks 1–9 · 9 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Nico Collins

WRHOURole down

Nico Collins's target share fell to 11% in week 9 (4 targets), from 22% in weeks 1-7.

Target share, week 9
11%
Targets, week 9
4
Target share, weeks 1 and 4–7
22%
Targets, weeks 1 and 4–7
35

Observed: Weeks 1, 4–7 and 9 · 6 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

KeAndre Lambert-Smith

WRLACRole down

KeAndre Lambert-Smith's target share fell to 13% in week 9 (4 targets), from 25% in week 6.

Target share, week 9
13%
Targets, week 9
4
Target share, week 6
25%
Targets, week 6
9

Observed: Weeks 6 and 9 · 2 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Dontayvion Wicks

WRPHIRole down

Dontayvion Wicks's target share fell to 9% in week 6 (4 targets), from 20% in weeks 1-5.

Target share, week 6
9%
Targets, week 6
4
Target share, weeks 1–5
20%
Targets, weeks 1–5
28

Observed: Weeks 1–6 · 6 games

  • Share of team targets/carries in games he played. Snap counts aren't in FFO's licensed data, so a low earlier share can mean limited playing time.

Red-zone role

Jahmyr Gibbs

RBDETRed-zone role

Jahmyr Gibbs has 53 of DET's 105 red-zone opportunities (50%), including 15 carries inside the 5.

Red-zone opportunities
53
Team red-zone opportunities
105
Red-zone share
50%
Carries inside the 5
15

Observed: Weeks 1–5 and 7–9 · 8 games

Kenneth Walker III

RBKCRed-zone role

Kenneth Walker III has 43 of KC's 83 red-zone opportunities (52%), including 15 carries inside the 5.

Red-zone opportunities
43
Team red-zone opportunities
83
Red-zone share
52%
Carries inside the 5
15

Observed: Weeks 1–4 and 6–9 · 8 games

Derrick Henry

RBBALRed-zone role

Derrick Henry has 41 of BAL's 81 red-zone opportunities (51%), including 16 carries inside the 5.

Red-zone opportunities
41
Team red-zone opportunities
81
Red-zone share
51%
Carries inside the 5
16

Observed: Weeks 1–9 · 9 games

Jonathan Taylor

RBINDRed-zone role

Jonathan Taylor has 34 of IND's 71 red-zone opportunities (48%), including 15 carries inside the 5.

Red-zone opportunities
34
Team red-zone opportunities
71
Red-zone share
48%
Carries inside the 5
15

Observed: Weeks 1–9 · 9 games

Bucky Irving

RBTBRed-zone role

Bucky Irving has 40 of TB's 89 red-zone opportunities (45%), including 7 carries inside the 5.

Red-zone opportunities
40
Team red-zone opportunities
89
Red-zone share
45%
Carries inside the 5
7

Observed: Weeks 1–9 · 9 games

Bijan Robinson

RBATLRed-zone role

Bijan Robinson has 32 of ATL's 72 red-zone opportunities (44%), including 8 carries inside the 5.

Red-zone opportunities
32
Team red-zone opportunities
72
Red-zone share
44%
Carries inside the 5
8

Observed: Weeks 1–9 · 9 games

Tony Pollard

RBTENRed-zone role

Tony Pollard has 30 of TEN's 73 red-zone opportunities (41%), including 10 carries inside the 5.

Red-zone opportunities
30
Team red-zone opportunities
73
Red-zone share
41%
Carries inside the 5
10

Observed: Weeks 1–8 · 8 games

Ollie Gordon II

RBMIARed-zone role

Ollie Gordon II has 27 of MIA's 56 red-zone opportunities (48%), including 10 carries inside the 5.

Red-zone opportunities
27
Team red-zone opportunities
56
Red-zone share
48%
Carries inside the 5
10

Observed: Weeks 2–5 and 7–9 · 7 games

Josh Jacobs

RBGBRed-zone role

Josh Jacobs has 17 of GB's 34 red-zone opportunities (50%), including 3 carries inside the 5.

Red-zone opportunities
17
Team red-zone opportunities
34
Red-zone share
50%
Carries inside the 5
3

Observed: Weeks 7–9 · 3 games

Quinshon Judkins

RBCLERed-zone role

Quinshon Judkins has 23 of CLE's 54 red-zone opportunities (43%), including 8 carries inside the 5.

Red-zone opportunities
23
Team red-zone opportunities
54
Red-zone share
43%
Carries inside the 5
8

Observed: Weeks 1–5 and 7–9 · 8 games

Dameon Pierce

RBPHIRed-zone role

Dameon Pierce has 8 of PHI's 17 red-zone opportunities (47%), including 4 carries inside the 5.

Red-zone opportunities
8
Team red-zone opportunities
17
Red-zone share
47%
Carries inside the 5
4

Observed: Weeks 5–7 · 3 games

Touchdowns above usage

Jaxon Smith-Njigba

WRSEATouchdowns above usage

Jaxon Smith-Njigba has scored 9 touchdowns on modeled targets and carries that usually produce 5.2, per FFO's expected-points model.

Touchdowns
9
Expected touchdownsEst.
5.2
Expected PPR per gameEst.
19.5
PPR vs expected, per gameEst.
+6.3

Observed: Weeks 1–9 · 9 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Tee Higgins

WRCINTouchdowns above usage

Tee Higgins has scored 6 touchdowns on modeled targets and carries that usually produce 2.8, per FFO's expected-points model.

Touchdowns
6
Expected touchdownsEst.
2.8
Expected PPR per gameEst.
14.8
PPR vs expected, per gameEst.
+5.2

Observed: Weeks 1–5 and 7–9 · 8 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Christian Watson

WRGBTouchdowns above usage

Christian Watson has scored 7 touchdowns on modeled targets and carries that usually produce 3.9, per FFO's expected-points model.

Touchdowns
7
Expected touchdownsEst.
3.9
Expected PPR per gameEst.
14.9
PPR vs expected, per gameEst.
+5.0

Observed: Weeks 1–9 · 9 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Isaiah Likely

TENYGTouchdowns above usage

Isaiah Likely has scored 6 touchdowns on modeled targets and carries that usually produce 3.1, per FFO's expected-points model.

Touchdowns
6
Expected touchdownsEst.
3.1
Expected PPR per gameEst.
14.6
PPR vs expected, per gameEst.
+1.3

Observed: Weeks 1–7 and 9 · 8 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Ja'Marr Chase

WRCINTouchdowns above usage

Ja'Marr Chase has scored 7 touchdowns on modeled targets and carries that usually produce 4.7, per FFO's expected-points model.

Touchdowns
7
Expected touchdownsEst.
4.7
Expected PPR per gameEst.
16.4
PPR vs expected, per gameEst.
+3.6

Observed: Weeks 1–5 and 7–9 · 8 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Bucky Irving

RBTBTouchdowns above usage

Bucky Irving has scored 8 touchdowns on modeled targets and carries that usually produce 5.7, per FFO's expected-points model.

Touchdowns
8
Expected touchdownsEst.
5.7
Expected PPR per gameEst.
15.9
PPR vs expected, per gameEst.
+2.3

Observed: Weeks 1–9 · 9 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Brock Bowers

TELVTouchdowns above usage

Brock Bowers has scored 6 touchdowns on modeled targets and carries that usually produce 4.2, per FFO's expected-points model.

Touchdowns
6
Expected touchdownsEst.
4.2
Expected PPR per gameEst.
17.8
PPR vs expected, per gameEst.
+3.6

Observed: Weeks 3–9 · 7 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Jahmyr Gibbs

RBDETTouchdowns above usage

Jahmyr Gibbs has scored 11 touchdowns on modeled targets and carries that usually produce 9.4, per FFO's expected-points model.

Touchdowns
11
Expected touchdownsEst.
9.4
Expected PPR per gameEst.
23.7
PPR vs expected, per gameEst.
+2.9

Observed: Weeks 1–5 and 7–9 · 8 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Bhayshul Tuten

RBJAXTouchdowns above usage

Bhayshul Tuten has scored 7 touchdowns on modeled targets and carries that usually produce 4.6, per FFO's expected-points model.

Touchdowns
7
Expected touchdownsEst.
4.6
Expected PPR per gameEst.
12.5
PPR vs expected, per gameEst.
+3.4

Observed: Weeks 1–6 and 8–9 · 8 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Chuba Hubbard

RBCARTouchdowns above usage

Chuba Hubbard has scored 7 touchdowns on modeled targets and carries that usually produce 5.3, per FFO's expected-points model.

Touchdowns
7
Expected touchdownsEst.
5.3
Expected PPR per gameEst.
16.3
PPR vs expected, per gameEst.
+2.0

Observed: Weeks 1–4 and 6–9 · 8 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

James Cook

RBBUFTouchdowns above usage

James Cook has scored 7 touchdowns on modeled targets and carries that usually produce 5.4, per FFO's expected-points model.

Touchdowns
7
Expected touchdownsEst.
5.4
Expected PPR per gameEst.
16.2
PPR vs expected, per gameEst.
+3.2

Observed: Weeks 1–6 and 8 · 7 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Zay Flowers

WRBALTouchdowns above usage

Zay Flowers has scored 3 touchdowns on modeled targets and carries that usually produce 1.2, per FFO's expected-points model.

Touchdowns
3
Expected touchdownsEst.
1.2
Expected PPR per gameEst.
13.0
PPR vs expected, per gameEst.
+3.0

Observed: Weeks 1 and 3–9 · 8 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Stefon Diggs

WRWASTouchdowns above usage

Stefon Diggs has scored 5 touchdowns on modeled targets and carries that usually produce 3.1, per FFO's expected-points model.

Touchdowns
5
Expected touchdownsEst.
3.1
Expected PPR per gameEst.
12.4
PPR vs expected, per gameEst.
+0.5

Observed: Weeks 1–4, 6 and 8–9 · 7 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Blake Corum

RBLATouchdowns above usage

Blake Corum has scored 5 touchdowns on modeled targets and carries that usually produce 2.4, per FFO's expected-points model.

Touchdowns
5
Expected touchdownsEst.
2.4
Expected PPR per gameEst.
8.4
PPR vs expected, per gameEst.
+2.1

Observed: Weeks 1–9 · 9 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Justin Jefferson

WRMINTouchdowns above usage

Justin Jefferson has scored 4 touchdowns on modeled targets and carries that usually produce 2.3, per FFO's expected-points model.

Touchdowns
4
Expected touchdownsEst.
2.3
Expected PPR per gameEst.
12.1
PPR vs expected, per gameEst.
+2.0

Observed: Weeks 1–3, 5 and 7–8 · 6 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Pat Freiermuth

TEPITTouchdowns above usage

Pat Freiermuth has scored 5 touchdowns on modeled targets and carries that usually produce 2.8, per FFO's expected-points model.

Touchdowns
5
Expected touchdownsEst.
2.8
Expected PPR per gameEst.
8.5
PPR vs expected, per gameEst.
+1.4

Observed: Weeks 1–8 · 8 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Harold Fannin Jr.

TECLETouchdowns above usage

Harold Fannin Jr. has scored 4 touchdowns on modeled targets and carries that usually produce 2.3, per FFO's expected-points model.

Touchdowns
4
Expected touchdownsEst.
2.3
Expected PPR per gameEst.
9.8
PPR vs expected, per gameEst.
+2.0

Observed: Weeks 1–9 · 9 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Darius Cooper

WRPHITouchdowns above usage

Darius Cooper has scored 4 touchdowns on modeled targets and carries that usually produce 2.2, per FFO's expected-points model.

Touchdowns
4
Expected touchdownsEst.
2.2
Expected PPR per gameEst.
8.6
PPR vs expected, per gameEst.
−0.5

Observed: Weeks 2 and 4–9 · 7 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Rashee Rice

WRKCTouchdowns above usage

Rashee Rice has scored 2 touchdowns on modeled targets and carries that usually produce 0.4, per FFO's expected-points model.

Touchdowns
2
Expected touchdownsEst.
0.4
Expected PPR per gameEst.
9.8
PPR vs expected, per gameEst.
+3.5

Observed: Weeks 1–3 and 8–9 · 5 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

DeMario Douglas

WRNETouchdowns above usage

DeMario Douglas has scored 4 touchdowns on modeled targets and carries that usually produce 2.3, per FFO's expected-points model.

Touchdowns
4
Expected touchdownsEst.
2.3
Expected PPR per gameEst.
9.0
PPR vs expected, per gameEst.
+2.0

Observed: Weeks 1–9 · 9 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Touchdowns below usage

Michael Wilson

WRARITouchdowns below usage

Michael Wilson has scored 2 touchdowns on modeled targets and carries that usually produce 9.2, per FFO's expected-points model.

Touchdowns
2
Expected touchdownsEst.
9.2
Expected PPR per gameEst.
19.8
PPR vs expected, per gameEst.
−6.4

Observed: Weeks 1–9 · 9 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Malik Nabers

WRNYGTouchdowns below usage

Malik Nabers has scored 2 touchdowns on modeled targets and carries that usually produce 4.5, per FFO's expected-points model.

Touchdowns
2
Expected touchdownsEst.
4.5
Expected PPR per gameEst.
17.5
PPR vs expected, per gameEst.
−1.3

Observed: Weeks 1–7 and 9 · 8 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Ashton Jeanty

RBLVTouchdowns below usage

Ashton Jeanty has scored 4 touchdowns on modeled targets and carries that usually produce 6.0, per FFO's expected-points model.

Touchdowns
4
Expected touchdownsEst.
6.0
Expected PPR per gameEst.
17.7
PPR vs expected, per gameEst.
−2.2

Observed: Weeks 1–9 · 9 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Chase Brown

RBCINTouchdowns below usage

Chase Brown has scored 1 touchdown on modeled targets and carries that usually produce 3.3, per FFO's expected-points model.

Touchdowns
1
Expected touchdownsEst.
3.3
Expected PPR per gameEst.
15.6
PPR vs expected, per gameEst.
−2.4

Observed: Weeks 1–5 and 7–9 · 8 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

DK Metcalf

WRPITTouchdowns below usage

DK Metcalf has scored 1 touchdown on modeled targets and carries that usually produce 3.4, per FFO's expected-points model.

Touchdowns
1
Expected touchdownsEst.
3.4
Expected PPR per gameEst.
14.4
PPR vs expected, per gameEst.
−4.7

Observed: Weeks 1–8 · 8 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Quinshon Judkins

RBCLETouchdowns below usage

Quinshon Judkins has scored 3 touchdowns on modeled targets and carries that usually produce 5.3, per FFO's expected-points model.

Touchdowns
3
Expected touchdownsEst.
5.3
Expected PPR per gameEst.
14.0
PPR vs expected, per gameEst.
−2.5

Observed: Weeks 1–5 and 7–9 · 8 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Chris Olave

WRNOTouchdowns below usage

Chris Olave has scored 2 touchdowns on modeled targets and carries that usually produce 3.5, per FFO's expected-points model.

Touchdowns
2
Expected touchdownsEst.
3.5
Expected PPR per gameEst.
18.0
PPR vs expected, per gameEst.
−0.3

Observed: Weeks 1–7 and 9 · 8 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Adonai Mitchell

WRNYJTouchdowns below usage

Adonai Mitchell has scored 1 touchdown on modeled targets and carries that usually produce 2.9, per FFO's expected-points model.

Touchdowns
1
Expected touchdownsEst.
2.9
Expected PPR per gameEst.
13.3
PPR vs expected, per gameEst.
−3.6

Observed: Weeks 1–2 and 7–9 · 5 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Tetairoa McMillan

WRCARTouchdowns below usage

Tetairoa McMillan has scored 3 touchdowns on modeled targets and carries that usually produce 4.5, per FFO's expected-points model.

Touchdowns
3
Expected touchdownsEst.
4.5
Expected PPR per gameEst.
16.2
PPR vs expected, per gameEst.
−0.4

Observed: Weeks 1–4 and 6–9 · 8 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Rome Odunze

WRCHITouchdowns below usage

Rome Odunze has scored 1 touchdown on modeled targets and carries that usually produce 3.3, per FFO's expected-points model.

Touchdowns
1
Expected touchdownsEst.
3.3
Expected PPR per gameEst.
10.7
PPR vs expected, per gameEst.
−0.6

Observed: Weeks 1–9 · 9 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Xavier Worthy

WRKCTouchdowns below usage

Xavier Worthy has scored 1 touchdown on modeled targets and carries that usually produce 2.6, per FFO's expected-points model.

Touchdowns
1
Expected touchdownsEst.
2.6
Expected PPR per gameEst.
10.1
PPR vs expected, per gameEst.
−1.7

Observed: Weeks 1–4 and 6–9 · 8 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Courtland Sutton

WRDENTouchdowns below usage

Courtland Sutton has scored 2 touchdowns on modeled targets and carries that usually produce 3.5, per FFO's expected-points model.

Touchdowns
2
Expected touchdownsEst.
3.5
Expected PPR per gameEst.
9.5
PPR vs expected, per gameEst.
−2.5

Observed: Weeks 1–9 · 9 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Jalen Brooks

WRARITouchdowns below usage

Jalen Brooks has scored 0 touchdowns on modeled targets and carries that usually produce 1.7, per FFO's expected-points model.

Touchdowns
0
Expected touchdownsEst.
1.7
Expected PPR per gameEst.
8.4
PPR vs expected, per gameEst.
−5.2

Observed: Weeks 3 and 5–7 · 4 games

  • Model estimate, not a forecast: v1 predicts about as well as raw points.

Injury opening

Cam Skattebo

RBNYGHistorical injury context

Cam Skattebo is listed doubtful (hamstring) on the week 9 report. He has 54% of NYG's carries. Other RBs by share: Devin Singletary (27%), Najee Harris (24%).

Week 9 official injury report
Doubtful (hamstring)
Carry share
54%
Next by share
Devin Singletary 27%, Najee Harris 24%

Observed: Weeks 1–5 and 7 · 6 games

The designation below belongs to its stated report week. It does not confirm current availability.

DeVonta Smith

WRPHIHistorical injury context

DeVonta Smith is listed out (hamstring) on the week 9 report. He has 33% of PHI's targets. Other WRs by share: Makai Lemon (19%), Dontayvion Wicks (17%).

Week 9 official injury report
Out (hamstring)
Target share
33%
Next by share
Makai Lemon 19%, Dontayvion Wicks 17%

Observed: Weeks 1–3 and 6 · 4 games

The designation below belongs to its stated report week. It does not confirm current availability.

David Montgomery

RBHOUHistorical injury context

David Montgomery is listed out (groin) on the week 9 report. He has 44% of HOU's carries. Other RBs by share: Woody Marks (49%), Jawhar Jordan (24%).

Week 9 official injury report
Out (groin)
Carry share
44%
Next by share
Woody Marks 49%, Jawhar Jordan 24%

Observed: Weeks 1–5 · 5 games

The designation below belongs to its stated report week. It does not confirm current availability.

Garrett Wilson

WRNYJHistorical injury context

Garrett Wilson is listed out (concussion) on the week 9 report. He has 28% of NYJ's targets. Other WRs by share: Adonai Mitchell (23%), Omar Cooper Jr. (22%).

Week 9 official injury report
Out (concussion)
Target share
28%
Next by share
Adonai Mitchell 23%, Omar Cooper Jr. 22%

Observed: Weeks 1–8 · 8 games

The designation below belongs to its stated report week. It does not confirm current availability.

Mike Evans

WRSFHistorical injury context

Mike Evans is listed out (ribs) on the week 9 report. He has 23% of SF's targets. Other WRs by share: Deebo Samuel Sr. (15%), Demarcus Robinson (13%).

Week 9 official injury report
Out (ribs)
Target share
23%
Next by share
Deebo Samuel Sr. 15%, Demarcus Robinson 13%

Observed: Weeks 1–6 · 6 games

The designation below belongs to its stated report week. It does not confirm current availability.

A.J. Brown

WRNEHistorical injury context

A.J. Brown is listed out (ankle) on the week 9 report. He has 22% of NE's targets. Other WRs by share: DeMario Douglas (17%), Mack Hollins (17%).

Week 9 official injury report
Out (ankle)
Target share
22%
Next by share
DeMario Douglas 17%, Mack Hollins 17%

Observed: Weeks 1 and 6–7 · 3 games

The designation below belongs to its stated report week. It does not confirm current availability.

QB efficiency

Drew Lock

QBSEAQB efficiency

Drew Lock is at +0.35 EPA per dropback over 78 dropbacks, 1st of 41 QBs with 50+.

EPA rank
1 of 41 qualified QBs
EPA per dropback
+0.35
Dropbacks
78

Observed: Weeks 1–2 and 9 · 3 games

Lamar Jackson

QBBALQB efficiency

Lamar Jackson is at +0.35 EPA per dropback over 104 dropbacks, 2nd of 41 QBs with 50+.

EPA rank
2 of 41 qualified QBs
EPA per dropback
+0.35
Dropbacks
104

Observed: Weeks 1–4 and 8 · 5 games

Baker Mayfield

QBTBQB efficiency

Baker Mayfield is at -0.29 EPA per dropback over 160 dropbacks, 41st of 41 QBs with 50+.

EPA rank
41 of 41 qualified QBs
EPA per dropback
−0.29
Dropbacks
160

Observed: Weeks 1–3 and 7–9 · 6 games

Justin Herbert

QBLACQB efficiency

Justin Herbert is at -0.27 EPA per dropback over 266 dropbacks, 40th of 41 QBs with 50+.

EPA rank
40 of 41 qualified QBs
EPA per dropback
−0.27
Dropbacks
266

Observed: Weeks 1–6 and 8–9 · 8 games

Rookie role

Carnell Tate

WRTENRookie role

Rookie Carnell Tate has a 26% target share through 7 games.

Target share
26%
Targets
51

Observed: Weeks 1–7 · 7 games

Jonah Coleman

RBDENRookie role

Rookie Jonah Coleman has 45% of DEN's carries through 4 games.

Target share
12%
Carry share
45%
Targets
14
Carries
47

Observed: Weeks 2 and 7–9 · 4 games

Jeremiyah Love

RBARIRookie role

Rookie Jeremiyah Love has 51% of ARI's carries through 6 games.

Target share
6%
Carry share
51%
Targets
14
Carries
76

Observed: Weeks 1–5 and 8 · 6 games

Denzel Boston

WRCLERookie role

Rookie Denzel Boston has a 22% target share through 9 games.

Target share
22%
Targets
60

Observed: Weeks 1–9 · 9 games

Omar Cooper Jr.

WRNYJRookie role

Rookie Omar Cooper Jr. has a 22% target share through 4 games.

Target share
22%
Targets
24

Observed: Weeks 1, 6–7 and 9 · 4 games

Caleb Douglas

WRMIARookie role

Rookie Caleb Douglas has a 22% target share through 5 games.

Target share
22%
Targets
27

Observed: Weeks 1–2 and 7–9 · 5 games

KC Concepcion

WRCLERookie role

Rookie KC Concepcion has a 20% target share through 9 games.

Target share
20%
Carry share
4%
Targets
55
Carries
10

Observed: Weeks 1–9 · 9 games

Makai Lemon

WRPHIRookie role

Rookie Makai Lemon has a 19% target share through 9 games.

Target share
19%
Carry share
0%
Targets
54
Carries
1

Observed: Weeks 1–9 · 9 games

Jadarian Price

RBSEARookie role

Rookie Jadarian Price has 36% of SEA's carries through 5 games.

Target share
10%
Carry share
36%
Targets
15
Carries
47

Observed: Weeks 1–3 and 8–9 · 5 games

Germie Bernard

WRPITRookie role

Rookie Germie Bernard has a 18% target share through 7 games.

Target share
18%
Carry share
1%
Targets
42
Carries
1

Observed: Weeks 2–8 · 7 games

Opportunity and performance

Explore target quality, rushing efficiency, quarterback decisions, kicking and defense. Start with the sample size, then compare the recorded results.

Wide receivers · Average depth of target

Mean air yards on targeted passes with recorded air yards, including incomplete and intercepted passes.

Largest samples first. A dash means no eligible sample; it does not mean zero. Source: nflverse.

Average depth of target for wide receivers, sorted by sample size
PlayerValueSample
CeeDee LambDAL9.9 yds92
Jaxon Smith-NjigbaSEA10.5 yds89
Matthew GoldenGB14.2 yds82
Michael WilsonARI11.4 yds81
Amon-Ra St. BrownDET8.4 yds76
Puka NacuaLA7.7 yds74
Chris OlaveNO12.3 yds71
Malik NabersNYG11.6 yds70
Christian WatsonGB13.4 yds66
Tetairoa McMillanCAR10.7 yds65
DK MetcalfPIT12.6 yds64
Garrett WilsonNYJ10.4 yds63
Drake LondonATL10.0 yds62
George PickensDAL11.6 yds62
Ja'Marr ChaseCIN10.4 yds61
Tee HigginsCIN13.6 yds61
Zay FlowersBAL8.2 yds58
Luther Burden IIICHI7.9 yds56
Denzel BostonCLE15.1 yds53
Carnell TateTEN12.7 yds51
Jaylen WaddleDEN9.8 yds51
Josh DownsIND10.4 yds51
Keenan AllenIND7.3 yds50
Wan'Dale RobinsonTEN5.8 yds50
Davante AdamsLA15.5 yds49
Emeka EgbukaTB9.7 yds49
KC ConcepcionCLE7.4 yds49
Devaughn VeleNO9.9 yds48
Parker WashingtonJAX12.9 yds48
Tre TuckerLV13.4 yds48

Sample: targets with air yards.

Updated Nov 9, 2026. Completed regular-season weeks only; samples can differ by metric.

Play-by-play: Weeks 1–8, 121 games. Games through Nov 2, 2026.

FTN charting: Weeks 1–8, 121 games (partial coverage). Charting pulled Nov 4, 2026. Excluded catchability/drop values on 16 contradictory charted plays. Other known charting remains available.

nflverse; calculations by Fantasy Football Outsiders (CC-BY-4.0).

FTN Data via nflverse; joined and aggregated by Fantasy Football Outsiders. FTN-derived metrics: CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/).

Data we do not have yet
  • Routes run and targets per route: The approved free feeds do not include every player's routes, including untargeted routes.
  • Separation and route grade: No approved free all-route tracking or route-grade dataset is available. Public NFL Next Gen Stats redistribution rights are not cleared.
  • Pressure rate: Sacks and numbers of rushers do not measure all pressures.

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