A modern web application focused on ingesting, processing, and visualizing data from the official NHL API. This project serves as a **Data Engineering** showcase in a Python/Django environment.
Developed a smart "Merge Logic" system that combines data from multiple NHL API endpoints. If the API lacks pre-processed team statistics for live games, the system autonomously calculates them by aggregating individual player performances in real-time.
To handle thousands of historical records efficiently (e.g., complete Canadian rosters from the league's inception), I implemented aggressive HTML fragment caching in Redis, reducing response times from seconds to milliseconds.
Created custom metrics like Draft ROI (return on scouting investment), which scans the entire league to attribute points to players' original drafting clubs—providing insights often missing from mainstream sports portals.