Chess Game Analyzer

A Python application that analyzes chess games using the Stockfish engine to provide insights into game phases, move quality, and player aggression.

Features

• Opening Theory: Identify opening moves that match established chess theory.
• Move Quality: Evaluate the quality of each move based on positional impact.
• Game Phase Analysis: Break down games into opening, middlegame, and endgame phases.
• Position Evaluation: Provide Stockfish-based evaluations of board positions.
• Aggression Metrics: Measure player aggression through move types and tactical patterns.

Example Output

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Setup

1. Clone the Repository

git clone https://github.com/vinny-ho/chess-data-analysis.git
cd chess-data-analysis-main

2. Install Dependencies

Make sure you have Python installed. Install required packages using:

pip install -r requirements.txt

3. Run the Application

Start the Streamlit application:

streamlit run main.py

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Usage

1. Upload PGN File:

   • Upload a PGN file containing chess games from Chess.com.

2. Enter Your Chess.com Username:

   • Provide your username to analyze your games specifically.

3. View Analysis:

   • Insights include:
     • Opening Theory: Compare openings to established theory.
     • Move Quality: Identify mistakes, inaccuracies, and great moves.
     • Game Phase Analysis: Understand how you play across different phases of the game.
     • Position Evaluation: See Stockfish’s evaluation of key positions.
     • Aggression Metrics: Assess tactical patterns and playing style.

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Metrics System

Move Quality

Moves are evaluated based on their impact on the position’s evaluation:

class MoveType(Enum):
    BLUNDER = -3.0     # Major mistake that loses significant advantage
    MISTAKE = -1.0     # Clear mistake that loses advantage
    INACCURACY = -0.5  # Small mistake that loses some advantage
    GREAT_MOVE = 1.0   # Move that gains significant advantage
    GOOD_MOVE = 0.5    # Move that gains some advantage
    BOOK_MOVE = 0      # Standard opening theory move

Aggression Score

Aggression is quantified by the nature of moves:

class AggressionMoveType(Enum):
    CAPTURE = 1.0        # Taking an opponent's piece
    RECAPTURE = 0.2      # Taking back a piece immediately after losing one
    SACRIFICE = 3.0      # Giving up material for positional advantage
    CHECK = 1.5          # Attacking the enemy king
    CENTER = 1.5         # Controlling central squares
    PROMOTION = 3.0      # Promoting a pawn
    CENTER_ATTACK = 0.3  # Attacking central squares

The aggression score identifies tactical patterns and playing styles.

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Dependencies

Ensure the following packages are installed (managed via requirements.txt):

• chess==1.11.1
• pandas==2.2.3
• plotly==5.24.1
• streamlit==1.41.1

Install all dependencies with:

pip install -r requirements.txt

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Libraries Used

• Stockfish Chess Engine: For providing position evaluation.
• Python-Chess: For handling chess PGN game data.
• Pandas: For data manipulation and analysis.
• Plotly: For creating visualizations.
• Streamlit: For building web application interface.

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Improvements

• Better Phase Evaluation: Dynamic phase evaluations of opening/middlegame/endgame based on piece activation/value.
• Better Aggression Evaluation: Add forks/pins/King safety to try and analyze playstyle better.

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Contribution

Contributions are welcomed.

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License

This project is licensed under the MIT License. See the LICENSE file for details.

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