GambitFlow/Opening-Database

♟️ GambitFlow: Elite Opening Theory (2000+ Elo)

📊 Dataset Overview

This dataset serves as the "Opening Memory" for the GambitFlow AI project (Synapse-Edge). It contains millions of chess positions extracted exclusively from Elite Level Games (Elo 2000+) played on Lichess.

The goal is to provide the AI with Grandmaster-level intuition during the opening phase, preventing early positional disadvantages.

• Source: Lichess Standard Rated Games (Jan 2017 - Apr 2024)
• Filter: White & Black Elo ≥ 2000
• Depth: First 35 plies (moves)
• Format: SQLite Database (.db)

📂 Dataset Structure

The data is stored in a positions table with the following schema:

Column	Type	Description
fen	TEXT (PK)	The board position in Forsyth–Edwards Notation (Cleaned: no move counters).
move_stats	JSON	Aggregated statistics of moves played in this position by elite players.

Example move_stats JSON:

{
  "e4": 15400,
  "d4": 12300,
  "Nf3": 5000
}

🛠️ Usage

import sqlite3
import json

conn = sqlite3.connect("opening_theory_v1.db")
cursor = conn.cursor()

# Get stats for the starting position
start_fen = "rnbqkbnr/pppppppp/8/8/8/8/PPPP1PPP/RNBQKBNR w KQkq - -"
cursor.execute("SELECT move_stats FROM opening_book WHERE fen=?", (start_fen,))
stats = json.loads(cursor.fetchone()[0])

print("Most popular elite move:", max(stats, key=stats.get))

⚖️ Credits & License

• Raw Data: Lichess Open Database
• Processed By: GambitFlow Team
• License: CC0 1.0 Universal (Public Domain)

We gratefully acknowledge Lichess.org for providing open access to millions of chess games.