A machine learning model that predicts runs scored by cricket players based on historical performance, match conditions, and opponent strength. Built with Python, scikit-learn, and XGBoost to analyze player form and provide data-driven insights for team selection and strategy.

A full-stack web application for tracking fitness performance across multiple events. Node.js/Express backend handles user authentication, calculates fitness scores, and manages social features (friends, groups, leaderboards). React frontend provides real-time data visualization and interactive dashboards. PostgreSQL stores user data, event results, and relationships. Dockerized for scalable deployment.