Current Projects
What I'm actively working on right now. These aren't finished yet, but this page shows what I'm building and what I'm focused on learning.
Most of what I'm building right now is in the sports analytics space — it's a good domain for practicing real data engineering because the data is messy, constantly updated, and there's a clear way to evaluate whether your model is actually working.
A machine learning model for predicting MLB game outcomes using pitcher stats, team batting trends, and opponent-adjusted metrics. Built around a SQLite database with a modular Python pipeline.
A player props prediction system using hoopR data. Instead of predicting raw stats, the model predicts each player's output as a percentage of their season average — which reduces bias across player tiers.
This site. I'm continuing to build it out — adding project pages, improving the design, and eventually connecting it to some of the model outputs as live demos.