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Sports Analytics Package
This Python package provides tools to perform statistical analysis and prediction modeling on sports data, with a focus on soccer/football match outcomes and team statistics. It includes a range of mathematical functions, machine learning models, and visualizations for analyzing match data.
Features
- Statistical Calculations: Functions for calculating expected values, Poisson distribution probabilities, variances, entropies, and more.
- Team Statistics: Calculate team performance metrics such as average goals scored and conceded, match outcomes, and more.
- Machine Learning Models: Training and prediction using various classifiers such as Random Forest, SVM, Naive Bayes, and others.
- Visualizations: Interactive plots for visualizing team statistics, match results, and predictive outcomes, including 3D plots.
- Gamma and Beta Functions: Access to essential mathematical functions, including Gamma, Beta, and Poisson distributions, for statistical modeling.
Installation
You can install this package using pip by running the following command:
pip install sports-analytics-package
git clone https://github.com/yourusername/sports-analytics-package.git
cd sports-analytics-package
pip install .
from sports_analysis_package import analiza_statystyczna, rysuj_wykresy
# Example data
druzyna1 = {'zdobyte': 30, 'stracone': 20}
druzyna2 = {'zdobyte': 25, 'stracone': 15}
mecze = 10
# Perform statistical analysis
statystyki1, statystyki2 = analiza_statystyczna(druzyna1, druzyna2, mecze)
# Visualize the results
rysuj_wykresy(statystyki1['średnia zdobytych'], statystyki1['średnia straconych'],
statystyki2['średnia zdobytych'], statystyki2['średnia straconych'])
### How to use:
1. Place the Python code you provided in a module or package folder (e.g., `sports_analysis_package`).
2. Include the above `__init__.py` in your main package folder.
3. Add the `README.md` to the root directory of your project to document the usage and installation steps.
Let me know if you need more details or assistance!
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