When the Clock Stops: How a Data Scientist Sees the Soul in a 39.7% Three-Pointer

The Last Shot Before Silence

I used to think basketball was just motion—until I learned it was grief.

At 29, I tracked every possession like a heartbeat. Mean points per game? 14. Three-point percentage? 39.7%. But in the clutch—when the crowd fell silent—I never left the floor.

Not because I was loyal to win.

Because I heard something deeper: the rhythm of a player choosing to stay, even when probability whispered it wasn’t worth more.

The Algorithm That Weeps

In Oxford’s old libraries and West London cafés at midnight, I’d sketch play-by-play models in coffee-stained notebooks.

I didn’t use TensorFlow to predict make-or-break decisions.

I used it to map hesitation—the tension between release and regret, the quiet math of a man who knew his value wasn’t in rebounds, but in stillness.

What Does It Mean to Be Human?

They call me cold—because my models are clean. But they don’t see how my father taught me silence is language, or how my Nigerian mother showed me that courage lives where logic bends toward love.

A three-pointer isn’t data—it’s an exhale before finality. The clock doesn’t stop because you’re behind—you stop because you chose to see what others ignored.

We build algorithms not for victory—but for meaning.