Week 4 ProjectionBFIQ model
vs Steelers · Thu, Oct 1 · 8:15 PM ET
Solo Tackles1.3
Assist Tackles1
Sacks0.5
Backfield IQ model: 2025 per-game production adjusted for opponent defense.
Shared model
Joint roster forecast
Guarded specialist marginals across both complete rosters
Offensive snaps
1%
Defensive snaps
66%
Solo tackles1.11P10–P90 0.0–3.0
Assist tackles1.12P10–P90 0.0–3.0
Sacks0.13P10–P90 0.0–1.0
Strongest learned context
Ranges integrate uncertainty in game environment, team volume, participation, allocation, and conversion. Context links show learned attention, not isolated causal effects.
The game around the player
Role across game environments.
How the same player changes when the game script changes.
99%
Any-snap probability
DL
Pregame role
Sacks
opponent dropbacks change rush chances; participation, pressure allocation and finish remain player-specific
0.11 → 0.14
PIT controls · defensive · slow
One-score game · high scoring · fast
Solo tackles
opponent plays change tackle chances; defensive role and tackle-credit rate remain player-specific
1.02 → 1.20
PIT controls · defensive · slow
One-score game · high scoring · fast
Assisted tackles
opponent plays change tackle chances; defensive role and tackle-credit rate remain player-specific
1.02 → 1.21
PIT controls · defensive · slow
One-score game · high scoring · fast
Scenario means integrate back to the guarded player distribution. “Validated” is awarded per market; a descriptive forecast is not automatically a betting signal.
This season
2026 Game Log
Performance history