College Football Playoff Predictor

Objective
A machine-learning based predictor for College Football Playoff outcomes built in a Kaggle notebook. The project uses historical college football data to model team performance and estimate playoff participation.
Technology used
- Random Forest Classifier
- XGBoost Classifier
- Pandas, NumPy, Scikit-learn
Skills Developed
- Data preprocessing and feature engineering from historical season data
- Trains and evaluates a predictive model for CFP selection
- Generates probabilities and comparative insights for playoff teams
View the Source Code