Rank the whole player pool
Search the complete current projection artifact and filter by position or confidence.
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- Player pool
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- Current model build
Rankings, projections, matchup models, and league-aware tools turn football data into clear decisions for your roster.


The FFO platform
Connect a league to move beyond generic lists. FFO reads your scoring, rosters, lineup needs, market, and opponents before it recommends a move.
These numbers are generated from the repository's current model manifest—not hand-written marketing copy. The same build step updates them whenever the data pipeline runs.
Inspect the methodologyCurrent projection artifact
Distinct jobs, not one opaque score
Recorded in the data manifest
371 rows · 2024 holdout
2026 PPR median projections with model-estimated low and high bands.
| Rank | Player | Projection | Range | Confidence |
|---|---|---|---|---|
| 01 | Drake MayeQB · NE | 295.4 pts | 175—383 | high |
| 02 | Patrick MahomesQB · KC | 289.7 pts | 174—344 | high |
| 03 | Josh AllenQB · BUF | 281.5 pts | 192—384 | high |
| 04 | Chris OlaveWR · NO | 268.6 pts | 166—323 | high |
| 05 | Trevor LawrenceQB · JAX | 267.3 pts | 167—400 | high |
| 06 | Justin HerbertQB · LAC | 267.2 pts | 165—357 | high |
Projection bands are model estimates, not guaranteed outcomes. Model build Aug 19, 2026; current model build.
A single composite rank can hide the evidence. FFO keeps each signal visible so you can see whether a player is talented, well-positioned, fairly priced, or simply a better fit for your roster.
Read the model guideWhat the player can do
What the role allows
What the range predicts
What leagues are pricing
What this week changes
What your team needs
Use public data first. Connect a league when the decision needs your scoring, roster, and opponents.
A plain-language guide to inputs, holdout testing, uncertainty bands, known limitations, and exactly what changes when the model refreshes.
Read the guideExplore the public board, or connect a Sleeper league for roster-aware recommendations.