FutureSightML

ML-powered Pokemon team builder that predicts win rates from team composition alone.

Pre-trained models for 61 competitive formats across Generations 1-9.

Downloads

• Windows Desktop App (CUDA): FutureSightML-win-x64.zip (~3 GB) — Extract and run. Models download automatically on first launch.
• Model Data: model-data.tar.gz (~300 MB) — For running from source.

Architecture

Neural transformer encoder with pairwise matchup matrix branch, ensembled with XGBoost (640+ hand-engineered features). Per-format calibrated weights. Generation-aware mechanics (Mega Evolution, Z-Moves, Dynamax, Tera types).

Performance

Team-only AUC on held-out test sets (ratings equalized, no Elo leakage):

Format	Neural AUC	XGB AUC
Gen 3 OU	0.859	0.828
Gen 4 OU	0.853	0.841
Gen 9 AG	0.845	0.772
Gen 8 Ubers	0.830	0.805
Gen 9 Ubers	0.812	0.752
Gen 9 OU	0.760	0.688

For context: Dota 2 draft prediction AUC is 0.66-0.71, Hearthstone deck prediction AUC is 0.65-0.68.

Source Code

github.com/HotHams/FutureSightML