This repository contains my submission for the Kaggle March Machine Learning Mania 2026 competition.
The goal of this competition is to predict the probability of every possible matchup in the 2026 NCAA Division I Men's and Women's Basketball Tournaments.
In this initial version, I established a Baseline Model using a 50/50 probability strategy (0.5) across all matchups. This serves as a benchmark for future iterations where I will implement more complex Machine Learning algorithms like XGBoost or Random Forests.
- Current Global Rank: 1036
- Status: Successfully submitted and ranked on the official Kaggle Leaderboard.
- Language: Python
- Libraries: Pandas, NumPy, OS
- Platform: Kaggle Notebooks
Created by [Abdul Musawir] - BS IT Student at Superior University.