The production baseline
How V1 forecasts a player
A · PLAYER HISTORY
Start with what the player has done.
V1 uses historical NFL game performance. It evaluates short, medium, and longer recent-game windows, including 3-, 5-, and 10-game histories, plus longer recency-weighted history where newer games matter more. Partial history is valid; missing games are not filled with zero.
B · SEPARATE DECISIONS
Different statistics can use different histories.
Football Quant evaluates its historical approach separately by position and forecast statistic. QB passing attempts may behave differently from RB rushing attempts, WR targets, or receiving touchdowns. One lookback rule is not forced onto every forecast.
C · OPPONENT CONTEXT
Let the matchup make a modest adjustment.
The player's own history remains the primary signal. For the statistics where testing supported it, the upcoming defense can move the forecast modestly based on what that defense has historically allowed. Player history does the heavy lifting. The opponent provides a nudge.
D · FOOTBALL FIRST
V1 forecasts 15 player stats.
Fantasy scoring is applied afterward, so the same football forecast can support different league formats.
- Passing attempts
- Completions
- Passing yards
- Passing touchdowns
- Interceptions
- Sacks suffered
- Rushing attempts
- Rushing yards
- Rushing touchdowns
- Targets
- Receptions
- Receiving yards
- Receiving touchdowns
- Fumbles
- Fumbles lost
E · Honest nulls
If V1 does not have usable NFL history for a player, it does not invent a forecast.
The player receives no production forecast, not a fake zero. This most often matters for rookies and other players without usable NFL history.
Known boundaries
What V1 doesn't model yet
V1 is the current production baseline, not the final forecasting system. V2 research explores richer features and machine-learning approaches, but V1 remains in production until a challenger earns promotion through testing.
- Injuries and the probability of playing
- Depth-chart and role changes
- Rookies without usable NFL history
- Coaching changes, detailed scheme, and offensive-line quality
- Weather, betting markets, and sophisticated game-script context
- Many richer team and player context signals
The value layer
What is fQ?
Fantasy Quotient (fQ) measures expected fantasy value above replacement for a particular league and forecast horizon.
fQ = max(
projected fantasy points
- replacement-level projected fantasy points,
0
)Replacement level represents the type of player expected to remain available after the league's starting demand at that position is accounted for.
Deeper leagues and additional starting slots generally push replacement lower. That is why the same football player can have different fQ values in different league formats. fQ is not another fantasy-point projection; it adds scarcity and league context.
Use the right number
Projected points or fQ?
Projected fantasy points
Who is expected to score more?
Use projected points for lineup and start/sit decisions. If two players are competing for one lineup spot this week, their projected performance is generally the relevant comparison.
Projected Points = performance.
Fantasy Quotient
How valuable is this player to own in this league?
Use fQ to compare players across positions while accounting for positional scarcity and replacement level. Weekly fQ should not override projected points for FLEX or start/sit decisions.
fQ = asset value.
The horizon matters
Where fQ matters
CURRENT
Weekly fQ
Weekly forecast → weekly fantasy points → weekly replacement → Weekly fQ
Waivers, short-term player acquisition, and weekly roster value.
Weekly fQ measures player value for the upcoming forecast week using the selected league format.
IN PROGRESS
Draft fQ
Draft-day player value and positional scarcity.
Use Draft fQ to compare players across positions and understand the value of selecting a position now versus what may remain later.
IN PROGRESS
ROS fQ
Trades, waivers, and roster decisions for the rest of the season.
Use ROS fQ to compare player value over the remaining schedule rather than only the upcoming week.
IN PROGRESS
Dynasty fQ
Long-term trades and roster construction.
Use Dynasty fQ to compare player value over a longer horizon where age, future opportunity, and expected production matter.
THE STANDARD
Prediction first. Actual result later. Grade the model honestly.
Published Football Quant forecasts are intended to be frozen before games, then compared with actual results after those games are played.
Ready to use the current board?
Want the technical details? Read the Methodology.