NBA analytics,built for people who actually watch the game.
Metric Hoops began in July 2025 as my first major personal project, a way to apply data science concepts to a sport I love using large-scale, real-world data. It started off small, focusing only on playoff game predictions. When I entered the project solo into the Institute for Insight AI & Analytics Conference a few months later, I felt entirely out of my comfort zone competing against full teams. Winning first place was a massive surprise and the ultimate turning point. I began to gain interest in creating something more than just a simple prediction tool. Months of deep research, technical hurdles, and continuous learning expanded the once simple project into the comprehensive platform it is today.
At its core, it's a full-stack NBA analytics platform designed to decode every layer of the game. Engineered to bring together live game intelligence, predictive modeling, interactive shot charts, and deep team breakdowns into one cohesive ecosystem, it centralizes the advanced metrics required to move past the box score. Whether you're a die-hard fan, an analyst, or just curious to go deeper, this is everything you need to follow the game with true context.
Growing up playing soccer, I always had a deep appreciation for competitive sports, but basketball was the game I loved to watch as a fan. For years, I was just a casual basketball fan, only focusing on the obvious parts of the game. However, during my Master's program in Data Science and Analytics, the lens through which I view the sport completely changed. I found myself looking past the box score and diving into the deeper mechanics of the play. That shift turned my casual fandom into a deep fascination with data-driven basketball analytics, where every possession is a data point and every game is a puzzle to solve. Outside of data and basketball, you can usually find me out playing soccer, on the pickleball court, or just walking my two cute dogs.
