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Why the NBA’s Best Sixth Man Got Left Behind: A Chicago South Side Data Story

Why the NBA’s Best Sixth Man Got Left Behind: A Chicago South Side Data Story

As a Chicago South Side analyst raised on streetball and Python models, I watched Ziemus Carnival’s 144–131 win not as luck—but as algorithmic inevitability. The second half wasn’t won by stars; it was won by systems. This isn’t just a game. It’s a case study in how overlooked players, not MVPs, build winning momentum through density, discipline, and community-driven execution. You think the best sixth man gets nominated by points? Let me show you why the data never lies.
Streetball
streetball analytics
data-driven basketball
•1 month ago
Daney's Streetball Show: 19 Shots, 7 Makes, and 5 Fouls — The Stats Behind the Chaos

Daney's Streetball Show: 19 Shots, 7 Makes, and 5 Fouls — The Stats Behind the Chaos

As a data analyst who’s spent years decoding NBA performance, I couldn’t help but dive into Daney’s wild streetball outing. Despite shooting just 7-of-19 and picking up 5 fouls, his impact on the court was undeniable. In this breakdown, I explore the numbers behind the noise — from offensive efficiency to defensive pressure — revealing why stats like these matter more than they appear at first glance. If you’re into streetball analytics or player impact beyond raw points, this one’s for you.
Streetball
basketball stats
streetball analytics
•2 months ago
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