JUNE 2026 REFRESH · TARGET INTEL · CURRENT ROSTERS · 825-PLAYER BOARD
YOUR DRAFT IS RIGGED.
ADP is a popularity contest dressed up as a projection. Our model explains 10× more variance in actual fantasy points, beats ADP by 41% on mean error, and ships with calibrated 80% confidence intervals. The War Room adds Target Intel that adapts to roster settings, live picks, VBD, ADP, and whether a player is likely to make it back. Walk-forward validated 2022-2025. No leakage. No excuses.
OverADP Model
0.63
R² — variance explained (walk-forward 2022-2025)
✓ 10× BETTER
VS
ADP (Market Consensus)
0.06
R² — same metric, same data (walk-forward 2022-2025)
✗ NOISE
Proof
We Called It. ADP Didn't.
Walk-forward validated on the 2024 NFL season. Here's what happened when our model disagreed with ADP consensus.
Walk-forward validated 2022-2025 — we train on the past and test on the future, never the reverse. Our model explains 63% of variance in actual fantasy points. ADP explains 6%. The current MAE edges: TE −43.8%, RB −41.5%, WR −40.3%, QB −39.7%.
Performance Audit
The Full Numbers
Walk-forward validated on 2022-2025 NFL seasons. 763 skill players plus 62 K/DEF entries on the current board. All features are strictly lagged to prevent leakage. Refreshed June 2026 with current roster/depth data, draft-value rookie signals, prior-year contract features, and conformal prediction intervals.
| Metric | OverADP | ADP | Delta | |
|---|---|---|---|---|
| Avg R² (variance explained) | 0.63 | 0.06 | 10× better | |
| Avg MAE (points off per player) | 39.0 pts | 65.9 pts | -41% error | |
| 80% CI empirical coverage | ~81-82% | — | CQR calibrated | |
| QB MAE edge | -39.7% | R² 0.57 vs 0.00 | ADP is noise at QB | |
| RB MAE edge | -41.5% | R² 0.66 vs 0.12 | crowd misses RBs | |
| WR MAE edge | -40.3% | R² 0.66 vs 0.10 | target-share wins | |
| TE MAE edge | -43.8% | R² 0.64 vs 0.03 | biggest R² lift |
Position Breakdown
We Win At Every Position
ADP is essentially noise at QB (R² 0.00). At every position, our model explains far more variance than ADP — powered by current roster/depth overlays, teammate target competition, contract signals, and a college/draft pipeline for rookies.
Quarterback
0.57
model R²
ADP R²: 0.00 → −39.7% MAE
Running Back
0.66
model R²
ADP R²: 0.12 → −41.5% MAE
Wide Receiver
0.66
model R²
ADP R²: 0.10 → −40.3% MAE
Tight End
0.64
model R²
ADP R²: 0.03 → −43.8% MAE
Arsenal
Your Draft Weapons
Calibrated intervals. Depth-chart awareness. College pipeline for rookies. Opportunity-cost Target Intel. Live draft tracking. No guessing. No reaching.
College/Draft Pipeline
Draft capital, draft-pick value, combine athleticism, college production per game, and Power 5 conference flags. The model knows your rookies before they take a snap — college data helps project players with no NFL track record.
Roster, Depth & Competition
WR1 vs WR3 isn't a footnote — it's the whole story. We overlay current Sleeper roster/depth data so post-draft movement gets reflected on the board. We also compute teammate target competition from prior-season production on the current roster — strictly no leakage.
Value-Based Draft Board
Players ranked by Value Based Drafting — not raw points. Knows when positions are running thin. Draft the right position at the right time.
Target Intel Policy
Opportunity-cost math decides when to lean into ADP, VBD, roster needs, flex paths, scarcity, and next-turn availability. In the War Room it updates instantly after every DRAFT, TAKEN, undo, reset, or roster-setting change.
Sleeper Detection
When our model ranks a player far above their ADP, that's a sleeper. We flag players ADP undervalues — especially where the model sees a 40%+ error edge over the market.
Bust Alerts
ADP overvalues name recognition. Our model spots players the market is overpaying for — before you waste a pick on them.
Positional Scarcity
See which positions have the steepest talent cliffs. If TE drops off a cliff after the top 5, you know to grab one early.
Injury-Adjusted Regression
Not every decline is a bust. The model detects injury-driven drops and dampens regression signals — so injured stars get projected for bounce-backs, not collapse.
Contract Context
Prior-year contract signals help separate stable roles from shaky market assumptions, especially in the WR/TE experiments that improved the current build.
Conformal 80% Confidence Intervals
Most tools slap an error bar on projections and hope. We use Conformalized Quantile Regression — when we say a player's 80% CI is 110–180 points, the truth actually lands inside that range ~80% of the time, validated on held-out seasons. Know which projections are rock-solid and which are coin flips.
Handcuff Alerts
Automatically finds backup RBs on the same team as your starters. Draft insurance for your 1st-round picks.
Bye Week Conflict Detection
Warns when drafting a player creates a bye week hole in your lineup. Never start a week with an empty roster spot.