Datasets:
metadata
license: cc0-1.0
task_categories:
- text-generation
- reinforcement-learning
language:
- en
tags:
- chess
- games
- lichess
- pgn
- openings
pretty_name: Lichess Elite Database
size_categories:
- 10M<n<100M
Lichess Elite Database
A curated collection of high-level chess games from Lichess.org, extracted from the Lichess Elite Database by nikonoel.
Dataset Description
This dataset contains 26.3 million games played by strong players on Lichess, filtered to include only:
- White player: rated 2400+ (2500+ from Dec 2021)
- Black player: rated 2200+ (2300+ from Dec 2021)
- Time controls: Rapid and Blitz (bullet excluded)
- Variant: Standard chess only
Source
Original data compiled by nikonoel from the Lichess Open Database.
Dataset Structure
| Column | Type | Description |
|---|---|---|
event |
string | Game event (e.g., "Rated Blitz game") |
site |
string | Lichess game URL |
white |
string | White player username |
black |
string | Black player username |
result |
string | Game result: 1-0, 0-1, 1/2-1/2 |
utcdate |
string | Game date (YYYY.MM.DD) |
utctime |
string | Game start time (HH:MM:SS) |
whiteelo |
int | White player's rating |
blackelo |
int | Black player's rating |
whiteratingdiff |
string | White's rating change |
blackratingdiff |
string | Black's rating change |
eco |
string | ECO opening code |
opening |
string | Opening name |
timecontrol |
string | Time control (e.g., "180+0", "600+0") |
termination |
string | How game ended (Normal, Time forfeit, etc.) |
moves |
string | Full game in SAN notation |
Use Cases
- Opening preparation: Study how strong players handle specific openings
- Chess engine training: Train or fine-tune chess models
- Game analysis: Statistical analysis of high-level play
- Move prediction: Sequence modeling for next-move prediction
- Style analysis: Study playing patterns of titled players
Usage
from datasets import load_dataset
dataset = load_dataset("nuriyev/lichess-elite")
# Filter by opening
sicilian = dataset["train"].filter(lambda x: x["eco"].startswith("B"))
# Filter by rating
super_gm = dataset["train"].filter(lambda x: x["whiteelo"] >= 2700)
Citation
If you use this dataset, please credit the original source:
@misc{lichess_elite_database,
author = {nikonoel},
title = {Lichess Elite Database},
year = {2020-2025},
url = {https://database.nikonoel.fr/}
}
License
The original Lichess game data is released under CC0 1.0.
Acknowledgments
- nikonoel for curating and maintaining the Lichess Elite Database
- Lichess.org for making game data freely available