https://github.com/hitthecodelabs/chessmovesanalysis
Python-based solution to analyze the accuracy of moves in a chess game
https://github.com/hitthecodelabs/chessmovesanalysis
Last synced: 10 months ago
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Python-based solution to analyze the accuracy of moves in a chess game
- Host: GitHub
- URL: https://github.com/hitthecodelabs/chessmovesanalysis
- Owner: hitthecodelabs
- License: mit
- Created: 2025-01-11T12:35:12.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-11T16:28:41.000Z (over 1 year ago)
- Last Synced: 2025-03-29T10:47:27.059Z (about 1 year ago)
- Language: Jupyter Notebook
- Homepage:
- Size: 123 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Chess Moves Analysis
This project provides a Python-based solution to analyze the accuracy of moves in a chess game by comparing each move to the best move suggested by the Stockfish engine. The accuracy is evaluated as a percentage, where 100% represents perfect play.
## Features
- Calculates move-by-move accuracy percentages.
- Plots move accuracy for each player (White and Black) separately.
- Highlights areas of deviation from optimal play.
## Requirements
Ensure you have the following installed:
- Python 3.7+
- Stockfish (a powerful open-source chess engine)
- Required Python libraries:
- `python-chess`
- `matplotlib`
You can install the necessary Python libraries using:
```bash
pip install python-chess matplotlib
```
## Setup
1. **Download Stockfish**:
- Download the appropriate version for your system from [Stockfish's official website](https://stockfishchess.org/download/).
- Place the executable in the working directory or note its path.
2. **Add PGN Game Data**:
- Input the moves of the chess game in PGN format.
3. **Update Path to Stockfish**:
- Update the variable `stockfish_path` in the script with the path to your Stockfish executable.
## How to Use
### Example Notebook
1. Define the game PGN and provide the Stockfish path:
```python
pgn_moves = """1. d4 d5 2. h3 Nc6 3. Nf3 Bf5 4. a3 h6 5. e3 a6 ..."""
stockfish_path = "path/to/stockfish"
```
2. Calculate accuracy:
```python
average_accuracy, accuracy_percentages = calculate_accuracy(pgn_moves, stockfish_path)
print(f"Average Accuracy: {average_accuracy:.2f}%")
```
3. Plot accuracy by player:
```python
plot_accuracy_by_player(accuracy_percentages)
```
### Functions
#### `calculate_accuracy(pgn_moves, stockfish_path, max_deviation=2000)`
- **Description**: Calculates the accuracy percentages for each move.
- **Parameters**:
- `pgn_moves`: PGN string of the chess game.
- `stockfish_path`: Path to the Stockfish executable.
- `max_deviation`: Maximum centipawn deviation for scaling accuracy percentages (default is 2000).
- **Returns**:
- `average_accuracy`: Overall average accuracy of the game.
- `accuracy_percentages`: List of accuracy percentages for each move.
#### `plot_accuracy_by_player(accuracy)`
- **Description**: Plots move-by-move accuracy for White and Black separately.
- **Parameters**:
- `accuracy`: List of move-by-move accuracy percentages.
## Visualization
The `plot_accuracy_by_player` function generates a graph separating White's and Black's move accuracies for better clarity.
## Example Output
```bash
Average Accuracy (Higher is better): 62.95%
Move-by-Move Accuracy: [97.15, 97.10, 98.70, 99.50, ...]
```
## License
This project is open-source and available under the MIT License.
## Acknowledgments
- Powered by [Stockfish](https://stockfishchess.org/)
- Built using the `python-chess` library.