Skip to content

lilre11/matchPred

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

1 Commit
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Spor Toto Prediction Bot

A machine learning-based prediction system for Turkish Spor Toto matches. This bot analyzes historical match data and team statistics to predict match outcomes (1-X-2).

Features

  • Data Collection: Scrapes match data from Turkish football leagues
  • Feature Engineering: Creates meaningful features from team statistics
  • ML Models: Multiple models (Random Forest, XGBoost, Neural Network)
  • Ensemble Prediction: Combines multiple models for better accuracy
  • Spor Toto Integration: Specifically designed for 15-match predictions
  • Performance Tracking: Monitors prediction accuracy over time

Project Structure

matchBet/
├── data/                  # Data storage
│   ├── raw/              # Raw scraped data
│   ├── processed/        # Cleaned and processed data
│   └── models/           # Saved ML models
├── src/                  # Source code
│   ├── data_collection/  # Data scraping modules
│   ├── preprocessing/    # Data cleaning and feature engineering
│   ├── models/          # ML model implementations
│   ├── prediction/      # Prediction logic
│   └── utils/           # Utility functions
├── notebooks/           # Jupyter notebooks for analysis
├── config/             # Configuration files
└── tests/              # Unit tests

Installation

  1. Clone the repository
  2. Install dependencies: pip install -r requirements.txt
  3. Configure API keys in config/settings.py
  4. Run data collection: python src/data_collection/scraper.py
  5. Train models: python src/models/train_models.py
  6. Make predictions: python src/prediction/predict.py

Usage

from src.prediction.predictor import SportTotoPredictor

predictor = SportTotoPredictor()
predictions = predictor.predict_weekly_matches()
print(f"Predicted outcomes: {predictions}")

Accuracy Target

  • Target: Predict at least 12 out of 15 matches correctly
  • Current best model accuracy: ~65-70% per match
  • Probability of 12+ correct: ~15-25% (varies by week)

Legal Notice

This tool is for educational and research purposes only. Gambling can be addictive. Please bet responsibly.

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors