Roster Advice
Model → real add/drop/read decisions for a posted roster (composes with Sleeper sync).
Intelligence engines
Does the grade actually predict?
Anyone can publish a rating. We backtest ours. Build the process grade on the first half of the season, then measure how well it ranks second-half production — against the obvious baseline, past production predicting future production. If the grade adds lift, it carries forward signal.
How we read it
- Grade ρ — does the grade rank the future?
- Spearman rank correlation between the first-half process grade and second-half production, within position. Higher is better.
- Lift — does it beat the past?
- Grade ρ minus baseline ρ (past production → future production). Positive means the grade adds signal the box score didn't already have.
- Call hit-rate — were buy/sell right?
- Of first-half buy-lows, how many rose; of sell-highs, how many fell. Read against the 50% coin flip.
Grade ρ (overall)
0.63
vs 0.61 past-production baseline
Lift over the past
+0.02
211 players · 2024
Sell-high hit-rate
63%
buy-low 44% · vs 50% coin flip
2024 · trained on weeks 1–9 · tested on weeks 10–18
The backtest, by position
First-half process grade ranks second-half production at ρ≈0.63 and adds 0.02 of rank-correlation lift over past production alone. In-sample, single-season — a directional proof, not a guarantee.
| Overall | 211 | 0.63 | 0.61 | +0.02 | 44%n=27 | 63%n=32 |
| QB | 32 | 0.57 | 0.58 | -0.01 | 100%n=6 | 50%n=4 |
| RB | 62 | 0.73 | 0.82 | -0.09 | 29%n=7 | 63%n=8 |
| WR | 82 | 0.72 | 0.63 | +0.09 | 40%n=10 | 69%n=13 |
| TE | 35 | 0.33 | 0.24 | +0.09 | 0%n=4 | 57%n=7 |
Split-half backtest on real nflverse weekly data: build the process grade on the first half of the season, then measure how it ranks second-half production vs the past-production baseline. Buy-low/sell-high calls are scored against the coin-flip line. In-sample, single-season — directional proof.
Out-of-sample · trained on 2023 · tested on 2024
The draft test: does last year's grade predict this year?
Grade built on 2023 ranks 2024 production at ρ≈0.63 (it does not beat raw 2023 production this pair). Out-of-sample, across seasons — the real draft test.
| Overall | 251 | 0.63 | 0.68 | -0.05 | 42%n=19 | 52%n=27 |
| QB | 29 | 0.54 | 0.67 | -0.13 | 0%n=1 | 33%n=6 |
| RB | 66 | 0.61 | 0.70 | -0.09 | 38%n=8 | 63%n=8 |
| WR | 103 | 0.69 | 0.68 | +0.01 | 80%n=5 | 63%n=8 |
| TE | 53 | 0.57 | 0.71 | -0.14 | 20%n=5 | 40%n=5 |
Year-over-year is the harder, more honest test: players change teams, age, and get hurt. Where the grade beats raw prior-season production (positive lift), it carries signal the box score didn't.
Multi-year stacked · out-of-sample · pooled pairs 2021→2022 · 2022→2023 · 2023→2024
The multi-year test: pool several seasons for real statistical power.
Pooling 737 player-seasons across 3 consecutive train→test pairs (2021→2022, 2022→2023, 2023→2024), the prior-season grade ranks next-season production at ρ≈0.60 — and it does NOT beat raw prior-season production over the pool. Multi-year, out-of-sample — the strongest, highest-power form of the draft test.
| Overall | 737 | 0.60 | 0.64 | -0.04 | 49%n=73 | 66%n=110 |
| QB | 90 | 0.35 | 0.55 | -0.20 | 20%n=5 | 58%n=26 |
| RB | 186 | 0.57 | 0.60 | -0.03 | 57%n=23 | 76%n=33 |
| WR | 306 | 0.69 | 0.69 | 0.00 | 44%n=27 | 69%n=35 |
| TE | 155 | 0.61 | 0.65 | -0.04 | 56%n=18 | 56%n=16 |
Each train→test pair is normalized within its own seasons (percentiles per pair), then the pairs are pooled — never re-ranked across seasons. Out-of-sample throughout; where it beats the baseline (positive lift), that is the strongest evidence the grade carries forward signal.
Data via nflverse (nflverse-data), licensed CC BY 4.0. How we source data
More engines & APIs
Engines without a standalone board
Some engines are POST-only or founder-gated, and three player engines render on the player boards under /players. They stay indexed and reachable here.
Graded Pool
Composes the model + xFP + team environment (real schemeFit from neutral-script offensive EPA) + QB-forward passing signal into a real graded pool that drives every fantasy tool when the founder enables it.
QB Consensus
ESPN QBR (results) vs Next Gen CPOE (accuracy), triangulated — disagreement surfaced, not averaged.
Rushing Efficiency
RYOE/att vs volume with stacked-box context — bell-cow / buy-low / volume-dependent.
Receiving Opportunity (WOPR)
Air-yards & target share → WOPR, with opportunity-vs-production buy/sell.