The Methodology
NFL Methodology
Position-specific factors, O-line impact, coordinator schemes
NBA Methodology
Development systems, roster fit, organizational patience
Why Context Matters
Traditional re-drafts treat players like fantasy assets — fixed values that can be reshuffled without consequence. But NFL history proves otherwise: the same player in different situations produces wildly different outcomes.
Tom Brady behind Cleveland's 2000 offensive line, with their coaching carousel and ownership instability? That's not a Hall of Famer — that's a career backup fighting for his roster spot.
The Formula
We calculate a Fit Score (0-100) for each player-team combination based on weighted factors that matter for that specific position.
Weight Categories
Team Environment (40%)
- • Head Coach — Win %, tenure, player development history
- • Coordinators — Scheme fit, QB/player development track record
- • Supporting Cast — O-line quality, skill weapons, defensive strength
- • Ownership — Stability, investment, front office quality
Position Development History (25%)
The Patriots can't develop WRs. The Packers are a QB factory. The Browns destroyed every QB from 1999-2017. This historical track record is our biggest differentiator.
N'Keal Harry, Chad Jackson, Aaron Dobson...
Favre → Rodgers → Love pipeline
Situational Factors (15%)
- • Draft Position Pressure — #1 picks get shorter leashes
- • Market Size — NYC scrutiny vs. small market patience
- • Team Mode — Win-now vs. rebuild affects patience
Player Factors (20%)
- • Pro Readiness — Can they contribute Day 1?
- • Scheme Dependency — Do they need a specific system?
- • Mental Makeup — How do they handle adversity?
Position-Specific Weights
Different positions care about different factors. A QB needs a good O-line; a WR needs a good QB.
| Position | Primary Factor (60%) | Secondary (30%) |
|---|---|---|
| QB | OC + O-Line | HC stability, Weapons |
| RB | O-Line + Scheme | Workload expectation |
| WR | QB Quality + Targets | OC scheme |
| EDGE | DC Scheme | Pass rush support |
| CB | Coverage scheme | Pass rush quality |
Data Sources
Every factor is backed by real data — no "I feel like..." assumptions.
- • Draft history: Pro Football Reference, Kaggle datasets
- • Player value: Pro Football Reference Approximate Value (AV)
- • O-line/Defense grades: rbsdm.com EPA metrics, PFF (where available)
- • Coaching records: Pro Football Reference career data
- • Coordinator history: Original research (our competitive advantage)
Score Interpretation
Excellent
Ceiling likely realized
Good
Solid development expected
Neutral
Outcome depends on player
Poor
Ceiling likely capped
Bad
High bust risk