Can AI Predict Who Gets Drafted? The 46% Chance, 69% First Round, and the Court That Shaped My Soul

The Court Was My First Lab

I grew up where the pavement cracked under streetlights—where every dribble carried weight beyond stats. At fifteen, I watched my cousin get cut from the tryout roster—not because he wasn’t good enough, but because the system didn’t see him. Now I use Python to map what they ignored: Green Room picks at #46%,首轮 at #69%, second round at #31%. This isn’t luck. It’s logic dressed in leather.

Data Doesn’t Care About Your Name

The NBA draft isn’t a lottery—it’s a pipeline of bias disguised as opportunity. Teams like the Thunder (#15), Wolves (#17), Nets (#19), Jazz (#21), Hawks (#22), Pacers (#23) all have algorithms behind their decisions. But when you look at the raw signals—the ones no scout wants to acknowledge—you see kids with calloused hands and quiet dreams. They don’t need invitations. They need visibility.

The Algorithm That Saw Me

My mother said: “If they can’t see you on paper, don’t wait for an invite.” So I built models that turn noise into narrative. Using Tableau, I visualized how #44 was labeled as “too late”—while #17 was labeled as “hope.” But hope doesn’t come from spreadsheets—it comes from midnight sessions on concrete courts in Englewood.

Why This Matters Beyond Draft Night

AI isn’t here to replace scouts—it’s here to remember them. When we reduce redundancy in data, we restore dignity to players who never got a shot but kept shooting anyway. You think it’s about talent? No. It’s about systems that filter out voices like mine.

And if you ask me: Who decides who gets picked? I’ll show you the code—and then hand you back the ball.