As a Brooklyn-born data scientist raised on jazz, streetball, and Bayesian logic, I’ve watched the NBA’s win predictions turn from mystic lore into calibrated silence. This isn’t about star power—it’s about the rhythm of residuals in motion. I built an engine that sees what coaches ignore: the second unit’s unseen variance. At midnight, with code singing like a haiku, we found the truth—not in draft picks, but in the quiet pulse of possession.