NCAA Tournament Prediction Model
Python · Data Science
This personal data-science project uses Python and historical team metrics to explore NCAA men’s basketball tournament outcomes. The work brings data preparation, feature selection, and model evaluation into one reproducible workflow.
Tools
Python, historical tournament data, feature preparation, and model evaluation.
Goal
Build a transparent workflow for exploring the factors behind tournament outcomes.
From Historical Data to a Prediction Workflow
The project organizes historical team data into a usable model pipeline, making it easier to compare inputs, evaluate predictions, and refine the approach over time.