---
license: cc-by-nc-4.0
pretty_name: Free Synthetic Chess Games (25M)
size_categories:
  - 10M<n<100M
tags:
  - chess
  - games
  - synthetic-data
  - board-games
  - reinforcement-learning
---

# Free Synthetic Chess Games (25M)

A synthetic dataset of **25,003,202 individual chess moves** across **92,733 fully legal games**, generated move-by-move with real chess-rules validation (every move is legal, every game is genuinely playable from start to finish, and every move is recorded in standard algebraic notation).

**Important note on play quality:** these games are **fully legal but NOT master-level play** — each move is chosen uniformly at random from the set of legal moves available at that position, not selected by a chess engine or drawn from human games. This makes the dataset well suited for move-legality checking, board-state encoding, position/move parsers, and engine or tooling test harnesses — not for learning strong chess strategy. As a result of random play, draws are common (insufficient material, repetition, and move-limit draws all occur naturally).

No real player games, PGN databases, or copyrighted game records were used — every game here was generated from scratch.

## Schema

| Column | Type | Description |
|---|---|---|
| `game_id` | string | Unique identifier for the game this move belongs to |
| `move_number` | int | Full-move number (increments after each pair of White/Black moves) |
| `ply` | int | Half-move index within the game (1 = White's first move, 2 = Black's first move, ...) |
| `player` | string | Which side made the move — `white` or `black` |
| `move_san` | string | The move in Standard Algebraic Notation (e.g. `Nf3`, `exd5`, `O-O`) |
| `piece` | string | Piece type that moved — `pawn`, `knight`, `bishop`, `rook`, `queen`, or `king` |
| `from_square` | string | Origin square (e.g. `e2`) |
| `to_square` | string | Destination square (e.g. `e4`) |
| `is_capture` | bool | Whether the move captured an opposing piece |
| `is_check` | bool | Whether the move put the opposing king in check |
| `game_result` | string | Final result of the game this row belongs to — `1-0`, `0-1`, or `1/2-1/2` |

## Format

Single Parquet file, Snappy-compressed. One row per half-move (ply), so each game spans multiple consecutive rows sharing the same `game_id`.

## Quick start

```python
import pandas as pd
df = pd.read_parquet("chess_games_25M.parquet")

# Reconstruct one game's move sequence
game = df[df["game_id"] == df["game_id"].iloc[0]].sort_values("ply")
print(game[["ply", "player", "move_san"]])
```

```python
# Or with duckdb for larger-than-memory queries
import duckdb
duckdb.sql("SELECT game_result, COUNT(DISTINCT game_id) FROM 'chess_games_25M.parquet' GROUP BY game_result")
```

```python
# Or with the datasets library
from datasets import load_dataset
ds = load_dataset("ziadatalabs/FreeSyntheticChessGames25M")
```

## Notes

- Games are generated with uniform-random legal-move selection, not engine or human play — see the play-quality note above before using this for anything strategy-related.
- Every move is validated for legality at generation time, so full games replay cleanly from the `move_san` sequence.
- Draws are more frequent here than in typical human or engine games, which is an honest consequence of random play (not a data quality issue).
- This dataset is part of a growing collection of free synthetic datasets across security, finance, healthcare, retail, geospatial, and other domains.

## License & Usage

Licensed under **CC BY-NC 4.0** (Creative Commons Attribution-NonCommercial 4.0). Free to use for personal, research, and educational purposes with attribution. Not licensed for commercial use.

---

Published by **Zia Data Labs**. More free synthetic datasets at [huggingface.co/ziadatalabs](https://huggingface.co/ziadatalabs).

Want more free datasets? Hit the ❤️ and follow. And we take requests — tell us what synthetic data you need, and we'll build it.

Contact: zia.data.team@protonmail.com