Welcome to footix’s documentation!
Footix is your intelligent companion for sports analysis and prediction. Leveraging advanced machine learning algorithms and comprehensive data analysis, it helps you make data-driven decisions in sports betting and analysis.
Features
- Advanced Data Analysis
Import data from multiple sports databases
Clean and preprocess sports statistics
Comprehensive historical data analysis
- Smart Prediction Engine
Machine learning-powered outcome prediction
- Strategic Betting Tools
Risk assessment algorithms
Bankroll management system
Multiple betting strategy templates
Quick Start
from footix.models.bayesian import BayesianModel
from footix.data_io.footballdata import ScrapFootballData
# Load match data (example: Ligue 1 fixtures)
dataset = ScrapFootballData(
competition="FRA Ligue 1",
season="2024-2025",
path="./data",
force_reload=True
).get_fixtures()
# Initialize and fit the Bayesian model
model = BayesianModel(n_teams=18, n_goals=20)
model.fit(X_train=dataset)
# Predict probabilities for a specific match
probas = model.predict(home_team="Marseille", away_team="Lyon").return_probas()
print(f"Home: {probas[0]:.2f}, Draw: {probas[1]:.2f}, Away: {probas[2]:.2f}")