Datasets:

mrmlengineer
/

chess_games

pretty_name: Chess Games Dataset
license: cc-by-nc-sa-4.0
size_categories:
  - 10M<n<100M
tags:
  - chess
  - chess-games
  - uci
  - parquet
  - lumbras-giga-base
  - machine-learning
  - datasets
configs:
  - config_name: default
    default: true
    data_files:
      - split: train
        path: part-*.parquet

Chess Games Dataset

This dataset is a compact, ML-oriented chess game dataset generated from angeluriot/chess_games plus additional 2025 games extracted from Lumbras Giga Base.

It keeps only the move sequence in UCI notation, a derived minimum Elo field, and a source label. This makes the dataset smaller and simpler to consume than the base dataset when the downstream task only needs legal move sequences and a coarse player-strength signal.

Dataset Summary

Games: 15,272,234
Files: 8 Parquet shards
Compressed size: 2.48 GiB
Split: train
Format: Parquet

Data Sources

Source	Games	Share
`LichessEliteDatabase`	5,525,245	36.18%
`LumbrasGigaBase`	4,785,121	31.33%
`PGNMentor`	3,431,537	22.47%
`TWIC`	858,163	5.62%
`Masters`	322,166	2.11%
`LichessBroadcast`	105,329	0.69%
`ChessOK`	62,895	0.41%
`Britbase`	60,148	0.39%
`Kingbase`	59,317	0.39%
`Convekta`	37,536	0.25%
`ChessNostalgia`	24,592	0.16%
`Chessopolis`	123	0.00%
`GamesOfGMs`	62	0.00%
Total	15,272,234	100.00%

The base dataset is angeluriot/chess_games, which already includes games from multiple public chess sources.

The added 2025 games come from Lumbras Giga Base, using the 2025 OTB and Online PGN files. Special thanks to Lumbras Giga Base for collecting and curating the chess game sources used by the base dataset and this extension.

Dataset Structure

Each row represents one chess game.

Field	Type	Description
`moves_uci`	`list[string]`	Mainline game moves in Universal Chess Interface notation, for example `e2e4`.
`min_elo`	`int64` or `null`	Minimum of White Elo and Black Elo when both ratings are available; otherwise `null`.
`source`	`string`	Source label preserved from the base dataset when available; added 2025 Lumbras games use `LumbrasGigaBase`.

Rows with null min_elo: 2,053,362.

Differences From `angeluriot/chess_games`

This dataset is not a full mirror of the base dataset. It intentionally removes metadata that is not needed for the target training workflows.

Removed fields:

date
white_elo
black_elo
end_type
winner
moves_san
moves_custom

Added or changed fields:

min_elo is derived from white_elo and black_elo.
source preserves the original base-dataset source label when available.
2025 Lumbras Giga Base OTB and Online PGN games are appended.
Rows are sorted by descending min_elo, with null values last.

Usage

Hugging Face Datasets

from datasets import load_dataset

dataset = load_dataset("mrmlengineer/chess_games")

game = dataset["train"][0]
print(game["moves_uci"])
print(game["min_elo"])
print(game["source"])

Streaming

from datasets import load_dataset

dataset = load_dataset(
    "mrmlengineer/chess_games",
    streaming=True,
)

for game in dataset["train"]:
    print(game["moves_uci"])
    break

License

This combined dataset is released under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International because Lumbras Giga Base states that its work is licensed under CC BY-NC-SA 4.0. The base dataset angeluriot/chess_games is distributed on Hugging Face with an MIT license.

Users should respect the terms of both upstream sources.

Limitations

The dataset has a single train split; no validation or test split is provided.
min_elo is null when either player Elo is unavailable.
Only the mainline UCI move sequence is included.
Commercial use is restricted by the CC BY-NC-SA 4.0 license.