When the Bulls Broke: A Data Analyst’s Cold Take on NBA Playoff Chaos

The Numbers Don’t Lie

I’ve spent ten seasons dissecting NBA playoffs not as a fan, but as a data detective. My desk in Chicago is littered with heatmaps of shot trajectories from 2013 to 2023—each dot a heartbeat, each line a breath. The Bulls’ collapse wasn’t emotional—it was statistical. Their win probability dropped below 0.38 after Game 7 in ‘23. No drama. Just decay.

Dynasty Fades in Plain Text

We romanticize ‘the Jordan王朝’ like it’s sacred scripture. But data doesn’t pray. It measures efficiency, turnover rate, and clutch performance under pressure—the real metrics no fan sees on Reddit threads at 2 AM after midnight.

I ran regression models across every playoff series since ‘98: when Pip went down, when Rose left, when the second unit failed to close out Game 6 in ‘17—those were not emotional collapses—they were variance outliers.

The Quiet Collapse of Hope

Fans still cling to ‘what if?’ narratives: what if Pip had stayed? What if Rose took one more shot? But algorithms don’t care. They just calculate. And in ‘24? The next season starts where we left off—in Philly? In Detroit? In Sacramento? The numbers are clear: expectation is dead. You can feel it when you watch the clock tick past 15 seconds in Game 4—and realize this isn’t about legends. It’s about .57% effective field goal rate under pressure—and that’s all that matters now.