Combined Bukmacherska
Combined Bukmacherska is a comprehensive project that provides tools for analyzing sports statistics and using machine learning to assist in betting strategies. The package offers utilities for training machine learning models, statistical analysis, and data visualization.
Features
- Train Machine Learning Models: A suite of classifiers, including Random Forest, Gradient Boosting, SVM, and more.
- Statistical Analysis: Analyze team performance metrics like average goals scored/conceded.
- Mathematical Utilities: Tools for Gamma distribution, Beta distribution, and Poisson probabilities.
- Visualizations: Generate line, bar, and 3D plots for data analysis.
Installation
Clone the repository and install dependencies:
git clone <repository-url>
cd combined_bukmacherska
pip install -r requirements.txt
Usage Examples
Train Machine Learning Models
from combined_bukmacherska.train_models import train_models, predict_with_models
# Example data
X_train, X_test, y_train, y_test = ... # Replace with your dataset
models = train_models(X_train, y_train)
predictions = predict_with_models(models, X_test)
from combined_bukmacherska.statistics import analiza_statystyczna, oblicz_statystyki_druzyny
druzyna1 = {'zdobyte': 30, 'stracone': 20}
druzyna2 = {'zdobyte': 25, 'stracone': 15}
mecze = 10
statystyki1, statystyki2 = analiza_statystyczna(druzyna1, druzyna2, mecze)
from combined_bukmacherska.visualizations import rysuj_wykresy
rysuj_wykresy(statystyki1['średnia zdobytych'], statystyki1['średnia straconych'],
statystyki2['średnia zdobytych'], statystyki2['średnia straconych'])
git clone https://github.com/your-repository/combined_bukmacherska2.git
from combined_bukmacherska2 import train_models
# Example usage
X_train, y_train = ... # Your training data
models = train_models(X_train, y_train)
from combined_bukmacherska2 import predict_with_models
# Example usage
X_test = ... # Your test data
predictions = predict_with_models(models, X_test)
from combined_bukmacherska2 import plot_results
# Example usage
plot_results(predictions, team1_lambda, team2_lambda, team1_avg_conceded, team2_avg_conceded)
Release files for combined-bukmacherska 0.9.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| combined_bukmacherska-0.9.0.tar.gz | 9.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| combined_bukmacherska-0.9.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 21.8 kB
Release files / combined_bukmacherska-0.9.0.tar.gz
| Download URL | combined_bukmacherska-0.9.0.tar.gz |
|---|---|
| Size | 9.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/6.1.0 CPython/3.11.9
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Release files / combined_bukmacherska-0.9.0-py3-none-any.whl
| Download URL | combined_bukmacherska-0.9.0-py3-none-any.whl |
|---|---|
| Size | 12.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.11.9
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