Why the Rockets Rejected Jalen Green: A Data-Driven Breakdown of a Trade That Never Happened

I don’t chase headlines. I chase patterns.

When the Suns reportedly turned down Jalen Green’s offer last June, it wasn’t about ego or drama—it was about alignment. The Rockets had offered a package that included Green,狄龙-布鲁克斯, and small贾巴里-史密斯—but if you strip away the noise, the math told a different story.

Green’s advanced metrics reveal an athlete who thrives in transition offense but underperforms in rim protection. His defensive rating? Below league average. His three-point volume? High—but inefficient when spacing collapses.

The Suns’ analytics team runs simulation models that prioritize floor-spacing over isolated scorers. They don’t need another ball-dominant wing—they need symmetry. Green’s usage rate (32%) and age (28) fit a rebuild timeline for 2026—not this offseason.

This trade didn’t happen because the data said no.

I’ve seen this before: teams mistake charisma for capability. But in basketball, truth is visible through efficiency ratios—not hype cycles.

Ask yourself: What does the box score really say when you remove the marketing?

The answer isn’t in tweets. It’s in the model.