Quarterback Projection Methodology: How We Forecast QB Output
Quarterback projections sit at the center of nearly every NFL fantasy decision — from draft boards to week-to-week lineup calls. This page explains the specific inputs, weighting logic, and adjustment layers that go into forecasting QB fantasy output, including how different scoring formats change the math and where projection models tend to be most and least reliable.
Definition and scope
A quarterback projection is a statistical forecast of a specific player's expected fantasy-scoring output for a given game, week, or season. The scope covers passing yards, passing touchdowns, interceptions, rushing yards, rushing touchdowns, and — in formats that penalize incompletions — completion rate. In standard ESPN or Yahoo scoring, a QB earns 1 point per 25 passing yards and 4 points per passing touchdown. In scoring formats that use PPR or 6-point passing TDs, the value distribution shifts meaningfully: a single touchdown swing from 4 to 6 points can separate two otherwise identical statistical lines by a full ranking tier.
The quarterback position also carries a uniquely wide floor-to-ceiling range. A quarterback like Lamar Jackson, who averaged 5.9 rushing yards per carry across the 2023 NFL season (Pro Football Reference), generates a rushing contribution that most pocket passers simply don't model. That dual-threat dimension requires a separate treatment within any honest projection framework — which is why floor and ceiling projections matter more at QB than at almost any other skill position.
How it works
QB projection models pull from three broad input categories, each carrying different predictive weight depending on the time horizon involved.
1. Historical performance baselines
The foundation of any QB projection is recent statistical output — typically a rolling weighted average across the prior 16 to 32 games, with more recent performance discounted less heavily. Raw box score data comes from sources like Pro Football Reference and NFL Next Gen Stats, which tracks air yards, time to throw, and completion percentage above expectation (CPOE). These advanced metrics separate genuine efficiency gains from variance-driven results.
2. Situational and contextual variables
This is where projections either earn their credibility or expose their weaknesses. The key variables modeled at this layer include:
- Opponent defensive ranking against the pass (both traditional and DVOA-adjusted, per Football Outsiders)
- Weather conditions for outdoor games, particularly wind speed above 15 mph, which correlates with reduced passing efficiency (see weather impact methodology)
3. Usage and role adjustments
Even at quarterback, usage rate adjustments apply. A QB with a high snap count baseline in a fast-tempo offense runs more plays per game, which mathematically increases opportunity volume independent of efficiency. Teams like the Kansas City Chiefs and San Francisco 49ers have consistently ranked in the top five for pace metrics, which inflates their QB's opportunity floor.
Vegas lines feed into this layer as well. When a game carries a high over/under — say, 50 or above — passing volume for both QBs tends to rise even when the game script starts balanced. The relationship between game totals and QB fantasy production is explored in depth at Vegas lines and fantasy projections.
Common scenarios
The matchup-friendly week: A QB facing a defense allowing the 28th-most fantasy points to the position gets a positive adjustment across passing yards and TD projections. This is a straightforward boost, though it often overfits to teams that surrendered points late in blowouts — a form of garbage-time inflation that distorts defensive rankings.
The mobile QB in a dome: Dual-threat quarterbacks in indoor venues remove weather variance entirely and retain their rushing upside. This scenario produces some of the highest projection confidence intervals in any given week — high floor, high ceiling.
The backup elevation: When a starter is ruled out and a backup steps into a full workload on 48 hours' notice, the projection model must pivot hard. Historical backup performance carries almost no predictive weight in week-specific models; instead, the team's offensive structure, offensive line quality, and receiver corps become the dominant inputs. This is precisely where in-season projections diverge most sharply from preseason baselines.
Decision boundaries
The most consequential split in QB projection methodology is mobile vs. pocket passer. These two archetypes are modeled with structurally different rushing contribution assumptions — pocket passers get a flat rushing floor of roughly 10–15 rushing yards per game in base projections, while dual-threat QBs receive a dynamic rushing component that scales with opponent defensive speed ratings and game script.
The second major boundary is superflex and two-QB formats vs. single-QB leagues. In superflex, the tier breaks shift dramatically — the gap between QB1 and QB12 compresses relative to the gap between QB12 and QB24, which has real implications for how projections should be applied to draft and waiver strategy.
Projections also behave differently across dynasty vs. redraft contexts. A dynasty model weights age curves and contract stability alongside weekly performance. A redraft model has no reason to care that a 34-year-old QB might decline in three years — only what happens in the next 17 weeks matters. The full Fantasy Projection Lab methodology overview covers how these distinctions apply across all modeled positions and time horizons.