Chess position datasets

Two position databases of chess positions, plus their variance reports. Each is published in two forms: a partitioned Parquet dataset for columnar scans, and the VPD1 SQLite container it was built from for indexed single-position lookup.

Positions carry no evaluation. Each row is a legal six-field FEN with derived board features. The result column records the source game's outcome as metadata; it is not a position label.

lc0-selfplay-2m

2,000,000 positions sampled from Leela Chess Zero self-play training data published at storage.lczero.org/files/training_data, drawn from 252,686 distinct games across 56 archives and 9 runs spanning 2018-09 to 2026-08.

Partitioned by generation quality, since the networks producing the games get weaker down the list:

test71 is excluded: it is the Chess960 run, measured at 30-36% Chess960 against at most 1.2% in every other run. Chess960 positions are excluded throughout, so every FEN is legal standard chess.

Records were converted with the LC0 rescorer without tablebase rescoring or deblundering, and without the position filtering the Stockfish NNUE path applies. Up to 12 positions were taken per game.

lichess-elite-300k

300,000 positions from 180,510 games in the Lichess Elite Database, which filters the Lichess standard database to games where a 2400+ player faced a 2200+ player. Twelve months are sampled evenly, spread across 2020-06 to 2025-10, at three positions per game.

This is strong human blitz: roughly 88% of eligible games are 3+0 or 3+2, 5% rapid, under 1% classical, White Elo median 2550. Bullet and ultrabullet are excluded. Draws are 12.3% of source games, against 44.7% in the self-play set — human blitz is substantially more decisive than engine self-play, so this set supplies sharper and less balanced positions. Per-month speed composition is recorded in the SQLite metadata table.

Layout

Parquet is partitioned Hive-style by source_split and phase, Zstandard compressed, in 65,536-row groups. _manifest.json in each dataset carries the source checksum plus per-file row counts, sizes, ID bounds and checksums.

source_split and phase are encoded in the directory paths rather than repeated per row. phase is opening, middlegame or endgame, held to a 15/60/25 ratio within every partition.

FENs are unique within each dataset. Across the two, 4,851 FENs appear in both, almost entirely common opening positions.

Verification

Every row was re-checked against python-chess: all FENs parse as legal standard chess, and side_to_move, piece_count, in_check and legal_moves were recomputed and matched on sampled subsets. Parquet and SQLite forms were confirmed to hold identical FEN sets.

The *-variance.json reports record distribution statistics and threshold checks for each database.