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Scored 14 TDs on 54 red-zone opportunities — opportunity implies only about 8.03. Touchdown rates that far above expectation rarely repeat, and the market is paying for them.
Model rank
Market
—
Confidence
low
Position: Running backC Tier
Josh Jacobs
RB · GB · Bye 11
Age 285'10"223 lbs7 yr
FFT9987
Elite Profile
Calibrated public rating
RAW 67 · 96% cov
Projection
10.0
Half-PPR / game
Market ADP
28.3
Consensus overall
FFT fair value
32.7
Calibrated pick
Draft delta
-4.3
Market minus FFT
Draft recommendation
Market is aggressive
Risk / reliability
Low Risk
80
Reliability
80 / 99
Coverage
80%
2026 week 2
Weekly Outlook
Our projection
10.7
Weighted weekly consensus
BDL projection
—
BALLDONTLIE weekly
Sleeper projection
—
Sleeper weekly
Game status
Not reported
No injury description reported
Game market
Total — · Spread —
Implied team total — · cross-book median
Live draft market
ADP 120.5 · Rostered 85.9%
BDL change -0.7%
BALLDONTLIE data checked 9/20/2026, 6:37:40 PM ET. Sportsbook values are consensus context, not betting advice.
Measured 2026 · Regular season
Season Production
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Actual BALLDONTLIE box scores · FFT-computed fantasy points · Preseason excluded. Missing stats are not zeroes.
2026 / Player Game Center
Every play has a story.
Josh Jacobs · Recorded performance, game context, fantasy takeaways.
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Measured game log
Weekly Performance
Actual BALLDONTLIE box scores · FFT-computed fantasy points. Missing weeks are never filled with zeroes.
No 2026 regular-season stat line recorded for Josh Jacobs yet.
This view will populate automatically when measured games enter the data spine.
FFT Newsroom
Latest news for Josh Jacobs
Position-relative
FFT99 Pillar Scores
Opportunity / Workload
84
Strong
84
Top 6% at RB
Talent / Efficiency
62
Average
62
Top 27% at RB
Offensive Environment
60
Average
60
Top 42% at RB
OL / Run Environment
35
Watch
35
Top 83% at RB
QB / Game-Script Fit
52
Watch
52
Top 58% at RB
Fantasy Playoff Schedule
48
Watch
48
Top 51% at RB
Player Profile
Opportunity / Workload84
Talent / Efficiency62
Offensive Environment60
OL / Run Environment35
QB / Game-Script Fit52
Fantasy Playoff Schedule48
Games
15
Half-PPR
201.1
Total TD
14
Model Component Contributions
The measured inputs doing the most work inside this grade.
Rush Share
9%
Targets Per Game
9%
Vegas
7%
Snap
6%
Inside Ten
6%
Run Tendency
6%
Route
4%
Rz Carries
4%
Draft Economics
Value Over Replacement
-2.0
proj. half-PPR pts
Rank Delta
-13
position spots vs ADP
Value Grade
D
Reach
reachfair valuesteal
Market
28.3
FFT value
32.7
Board Δ
-4.3
Playoff Schedule
Week 15
vs MIA
Rank 7th
EliteWeek 16
@ CHI
Rank 19th
NeutralWeek 17
vs HOU
Rank 22nd
NeutralFFT99 vs ADP
Every dot is a real position peer with a market price.
Compare Players
Deep research dossier
Evidence, history and model transparency
The decision dashboard ends above. Open only the research sections you need below—the full evidence remains available without overwhelming the player overview.
The call record1 pre-registered
Claims written down before the season, sealed at registration, and graded in public — misses kept.
The call record1 pre-registered
Claims written down before the season, sealed at registration, and graded in public — misses kept.
Scored 14 TDs on 54 red-zone opportunities — opportunity implies only about 9.58. Touchdown rates that far above expectation rarely repeat, and the market is paying for them.
Model rank
39
Market ADP
28.3
Divergence
-10.8
Edge score
0.74
Every measured input behind this call
td_regressionbearish
Scored 14 TDs on 54 red-zone opportunities — opportunity implies only about 9.58. Touchdown rates that far above expectation rarely repeat, and the market is paying for them.
- priorTds
- 14
- expectedTds
- 9.58
- gap
- -4.42
- redzoneOpportunities
- 54
source: Sportradar red-zone opportunity + FFT finishing-rate model
Registered 2026-08-08T06:38:11.545Z against a board computed 2026-08-08T06:33:00.114Z, under fft-projection-1.0.0-beta / fft-edges-1.0.0. Scored pool 615, of which 160 carried a market price and formed the comparable pool this call is relative to. Market source: Consensus of the Yahoo, Sleeper and RTSports ADP columns in the static dataset snapshot bundled with the app at registration time — a snapshot, not a live feed. The ADP recorded on each call is the price the market was charging when the call was made.. Selection: EVERY directional verdict the board produced at boardComputedAt — all 15 BUY and 14 FADE from a scored pool of 615 players, 160 of whom carried a market price. No filtering by conviction, position or confidence, so the record cannot be flattered by selection. Witness: git commit only — see docs/methodology.md
Grading happens after the season against the pool frozen at registration. See the full record, including the misses →
2025 production
What he actually did last season. Measured, not projected.
2025 production
What he actually did last season. Measured, not projected.
Games
15
PPR pts
237.1
Half-PPR pts
201.1
PPR / game
15.8
Receiving
Targets
44
Receptions
36
Rec yards
282
Rec TDs
1
Target share
9.6%
Air yards share
-0.9%
WOPR
0.14
Rushing
Carries
234
Rush yards
929
Rush TDs
13
Yards / carry
3.97
Passing
Pass yards
0
Pass TDs
0
Interceptions
0
nflverse season totals for 2025, joined on normalised name and position (gsis 00-0035700). These are actuals — nothing here is modelled.
What the market says
Every ADP source we hold, side by side, and where our model sits against them.
What the market says
Every ADP source we hold, side by side, and where our model sits against them.
Consensus ADP
28.3
Median
29.0
Sources ranking him
3/4
Agreement
High
| Source | Rank / ADP |
|---|---|
| Yahoo ADP | 29.0 |
| Sleeper ADP | 27.0 |
| RTSports ADP | 29.0 |
| Fantasy Football Calculator ADP (live) | unranked |
The sources that ranked him disagree by 2.0 picks between highest and lowest (standard deviation 0.9).
Mean and median are computed across the sources that actually ranked him — an unranked source never enters the average, because a sentinel treated as a pick number would drag a real player hundreds of slots. Spread, deviation and agreement are null under two ranked sources rather than 0, since one source cannot agree with itself. The FFT model rank is our own output and is never folded in as if it were an outside source.
Week-to-week, 2025
Consistency and range — the part a season total hides.
Week-to-week, 2025
Consistency and range — the part a season total hides.
Weeks with a line
15
PPR / game
15.8
Std dev
8.7
Coeff. of variation
0.55
Boom rate
27% (4/15)
Bust rate
20% (3/15)
Best week
32.0 wk 6
Worst week
1.3 wk 17
Recent form — last 4 games with a line
11.6 PPR per game over weeks 14, 15, 16, 17 — -4.2 against his season average.
Every week (15 lines)
| Wk | Opp | PPR | Tgt | Rec | Yds | Car | RuYd | TD | RZ |
|---|---|---|---|---|---|---|---|---|---|
| 1 | DET | 14.0 | 1 | 1 | 4 | 19 | 66 | 1 | 5 |
| 2 | WAS | 14.4 | 0 | 0 | 0 | 23 | 84 | 1 | 6 |
| 3 | CLE | 12.4 | 9 | 5 | 44 | 16 | 30 | 0 | 4 |
| 4 | DAL | 31.7 | 4 | 4 | 71 | 22 | 86 | 2 | 7 |
| 6 | CIN | 32.0 | 5 | 5 | 57 | 18 | 93 | 2 | 4 |
| 7 | ARI | 18.8 | 1 | 1 | 3 | 13 | 55 | 2 | 5 |
| 8 | PIT | 13.5 | 3 | 3 | 12 | 13 | 33 | 1 | 4 |
| 9 | CAR | 20.0 | 5 | 4 | 13 | 17 | 87 | 1 | 4 |
| 10 | PHI | 19.7 | 6 | 5 | 33 | 21 | 74 | 1 | 2 |
| 11 | NYG | 4.0 | 1 | 0 | 0 | 7 | 40 | 0 | 3 |
| 13 | DET | 10.1 | 1 | 1 | 8 | 17 | 83 | 0 | 1 |
| 14 | CHI | 17.2 | 2 | 2 | 6 | 20 | 86 | 1 | 2 |
| 15 | DEN | 23.2 | 3 | 2 | 19 | 12 | 73 | 2 | 3 |
| 16 | CHI | 4.8 | 2 | 2 | 12 | 12 | 36 | 0 | 6 |
| 17 | BAL | 1.3 | 1 | 1 | 0 | 4 | 3 | 0 | 2 |
The weekly LINES are measured: 2025 game logs, joined on gsis id 00-0035700. Everything derived from them above — per-game, standard deviation, coefficient of variation, boom and bust rates, recent form — is computed by us and carries the FFT model (beta) label. It is not an observed stat.
This whole block is on the PPR scale, including the thresholds — the artifact publishes boom and bust in PPR (RB: boom ≥ 20, bust ≤ 8) and converting only the points would leave the rates measured against a different ruler than the one they were defined on. The hero above is half-PPR because that is what the model ranks on. Two rulers, each labelled, rather than one silently mixed. Rates need at least 4 games to carry weight; recent form is the last 4.
Advanced usage & efficiency
Route concepts, red-zone opportunity, and separation-adjusted catch rate.
Advanced usage & efficiency
Route concepts, red-zone opportunity, and separation-adjusted catch rate.
Red-zone opportunity
Scoring upsideRZ targets
6
RZ carries
58
RZ TDs
13
aDOT
—
Concept EPA / target
0.223
Classified targets
47
Catch residual
—
YAC over expected
—
Most-run concept: SCREEN on 48.9% of his classified targets.
Every field is derived by FFT from openly-licensed nflverse play-by-play, or taken from the free public NFL Next Gen Stats endpoint. No licensed trial data (Sportradar, BALLDONTLIE) is included, which is why this file can be committed and shipped with the build. Red zone: Plays snapped inside the opponent 20-yard line. Red-zone usage measures opportunity; this repo’s own backtest shows it adds little on top of plain volume, so it is retained as context and is deliberately not described as an edge.
How the model gets there
The component projection behind the headline number, and what it was built from.
How the model gets there
The component projection behind the headline number, and what it was built from.
Projected games
13.5
Half-PPR (season)
135.3
PPR (season)
146.3
Confidence
high
Proj targets
27.8
Proj receptions
21.9
Proj rec yards
176
Proj rec TDs
1.0
Proj carries
149.7
Proj rush yards
645
Proj rush TDs
6.2
Proj pass yards
0
Proj pass TDs
0.0
Proj INTs
0.0
Touchdown regression
He actually scored 14 touchdowns last season. Against his measured opportunity the model expects a change of -6.8. The gap between what a player scored and what his opportunity implies is one of the four signals the edge engine reads.
What this projection was built from
15 g in 2025, 15.6 car/g, 2.9 tgt/g, 59% snaps (regressed to the role, not the position), RB4 on depth chart, age 29, -6.8 TD vs 2025 on red-zone opportunity
fft-projection-2.3.0-beta. The model reads measured production, opportunity and age, and reads no ADP field at any stage — so it can disagree with the market, which is the only reason a disagreement is worth anything. Draft capital was not resolved for this player, which the model treats as unknown rather than as undrafted.
What this page is standing on
Which sources answered for this player, and which did not.
What this page is standing on
Which sources answered for this player, and which did not.
- Identity join: Resolved to gsis 00-0035700 via the 2025 nflverse season file. The weekly log and advanced splits are keyed on that id.
- Market ADP: A bundled snapshot of platform ADP, not a live feed. Shown for comparison and never read by the projection model.
- Headshot: Resolved from exact-name.
- Vitals: Height, weight, college and jersey are read from nflverse and keyed on gsis id 00-0035700 — not on name. Name keying matches players to relatives who share one: "Marvin Harrison Jr." also matches his father's 1996 row, and whichever came first in the file would win.
- Not shown: draft round and pick. The bundled player file carries them on roughly 48% of rows and populates them late, so a blank is equally consistent with a genuine undrafted free agent and with a first-rounder nobody has ingested yet. The model’s own three-state read is used instead, above.
Model run caveats
- No usable red-zone RECEIVING fit for QB — receiving touchdowns at that position come from the shrunk per-target rate alone.
- Rookie draft capital on this run: 82 drafted (projected from round/pick), 141 confirmed undrafted, 177 with capital UNKNOWN.
- 177 of 400 rookie projections (44%) have NO KNOWN DRAFT CAPITAL because this draft class has not been ingested by any source the model can read. For those players the draft-capital path did not run: a first-round pick and a camp arm receive the same number, separated only by depth-chart order. Those projections are flagged `isPositionalFloor` and must be read as a floor for the role, not as a valuation of the player.
How the model works
Inputs, method, and the forbidden-inputs list. It reads no ADP at any stage.
Where it loses
Pre-registered calls, graded in public, misses kept on the page.
Model Rankings
Every player, with the model's BUY / FADE call against consensus ADP built into the board.