| --- |
| 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`](https://huggingface.co/datasets/angeluriot/chess_games) |
| plus additional 2025 games extracted from |
| [Lumbras Giga Base](https://lumbrasgigabase.com/en/). |
|
|
| 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`](https://huggingface.co/datasets/angeluriot/chess_games), |
| which already includes games from multiple public chess sources. |
|
|
| The added 2025 games come from |
| [Lumbras Giga Base](https://lumbrasgigabase.com/en/), 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 |
|
|
| ```python |
| 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 |
|
|
| ```python |
| 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](https://creativecommons.org/licenses/by-nc-sa/4.0/) |
| 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. |
|
|
