https://github.com/code-jl/nfl-kicker-predictor
A sophisticated Python application that provides real-time NFL kicker statistics and performance analysis with an intuitive graphical interface.
https://github.com/code-jl/nfl-kicker-predictor
beautifulsoup data-analysis data-visualization espn football gui nfl prediction python real-time-analytics real-time-data sport-analytics sports-data statistics tkinter web-scraping
Last synced: 4 months ago
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A sophisticated Python application that provides real-time NFL kicker statistics and performance analysis with an intuitive graphical interface.
- Host: GitHub
- URL: https://github.com/code-jl/nfl-kicker-predictor
- Owner: Code-JL
- License: mit
- Created: 2025-01-05T20:26:28.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2025-01-05T22:04:39.000Z (6 months ago)
- Last Synced: 2025-01-18T01:15:37.005Z (6 months ago)
- Topics: beautifulsoup, data-analysis, data-visualization, espn, football, gui, nfl, prediction, python, real-time-analytics, real-time-data, sport-analytics, sports-data, statistics, tkinter, web-scraping
- Language: Python
- Homepage:
- Size: 21.5 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# NFL Kicker Predictor
A sophisticated Python application that provides real-time NFL kicker statistics and performance analysis with an intuitive graphical interface.
## Features
- **Real-time Data**: Scrapes live NFL kicker statistics from ESPN
- **Offline Mode**: Load previously saved kicker data for offline analysis
- **Statistical Analysis**: Track and analyze key performance metrics including:
- Career & season field goal percentages
- Average attempts per game
- Average successful kicks per game
- Last game performance
- **Visual Performance Indicators**: Color-coded projections comparing historical averages
- **Data Persistence**: Save kicker statistics locally for future reference
## Installation
1. Clone the repository: ```bash git clone https://github.com/yourusername/NFL-Kicker-Predictor.git ```
2. Install required dependencies: ```bash pip install requests beautifulsoup4 tkinter ```
## Usage
1. Run the main application: ```bash python Kicker.py ```
2. Select data source:
- **From Network**: Fetches real-time data from ESPN
- **From Save**: Loads previously saved local data
4. Choose league (NFL currently supported)
5. Browse kickers and view their statistics
6. Enter projections to compare against historical performance:
- Green: Projection below historical average
- Red: Projection above historical average
## Project Structure
- `Classes/`: Core class definitions
- `Gui/`: User interface implementation
- `Local/`: Local data handling
- `Save/`: Data persistence operations
- `Scrape/`: Web scraping functionality
## Technical Details
- Built with Python 3.x
- Uses BeautifulSoup4 for web scraping
- Tkinter for GUI implementation
- Modular architecture for easy maintenance and expansion
## Contributing
1. Fork the repository
2. Create your feature branch (`git checkout -b feature/AmazingFeature`)
3. Commit your changes (`git commit -m 'Add some AmazingFeature'`)
4. Push to the branch (`git push origin feature/AmazingFeature`)
5. Open a Pull Request
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## Acknowledgments
- Data sourced from ESPN's NFL statistics
- Built with inspiration from sports analytics and statistical modeling
--- *Note: This project is for educational and analytical purposes only. All NFL data is property of their respective owners.*