One popular example is “ShotProbability.io” — a tool that predicts the likelihood of a made basket based on defender distance, shot clock, and player hot streaks. The author’s GitHub repo includes the Python notebook used to train the model, along with a live frontend.
Using a simplified machine learning model (trained on Synergy data), users can paste a play-by-play string like “Curry receives screen from Green, drives right, floater.” The tool classifies it as P&R Ball Handler, Isolation, or Spot-Up—then suggests defensive counters. basketball github io
git init git add . git commit -m "First commit: A simple shooting arc" One popular example is “ShotProbability
If you're looking to build your own, most successful repos use a similar "starting lineup": basketball github io