Fantasy Football Analytics & ML

About

Provides comprehensive guidance for building robust fantasy football projection models, focusing on domain-specific feature engineering and rigorous validation strategies. It assists users in creating advanced metrics such as age curves and opportunity shares, selecting the most effective ML algorithms for sports data, and implementing time-series splits to prevent data leakage. By integrating position-specific modeling and model interpretability via SHAP values, it enables the creation of sophisticated, data-driven insights tailored to the unique constraints of professional football statistics.

Key Features

• Specialized time-series validation strategies to ensure predictive accuracy without data leakage
• 0 GitHub stars
• Framework for selecting optimal ML models based on data size and interpretability needs
• Model interpretability techniques to explain projections through feature importance
• Position-specific modeling patterns for QBs, RBs, WRs, and TEs
• Advanced feature engineering for age curves, weighted opportunities, and efficiency metrics

Use Cases

• Identifying breakout candidates using advanced efficiency and opportunity metrics
• Refining machine learning models to handle small sample sizes and NFL regime changes
• Constructing a custom player projection system for seasonal or daily fantasy football