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3 data signals that revealed the truth behind tonight’s underdog win — and why I stopped believing in narratives
As a data scientist raised on Brooklyn’s concrete courts and Bayesian priors, I used to chase the myth that intuition drives sports. But after analyzing 12 seasons of micro-samples from undervalued leagues, I realized: the real signal isn’t who scores — it’s who models their silence. This isn’t about talent. It’s about entropy in the algorithm. I don’t trust hype. I trust posterior probabilities.
Thunder Zone
bayesian sports modeling
data-driven decision
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3 weeks ago
Why Do the Highest-Scoring Bench Players Lose the Finals? The Data Doesn’t Lie — But Intuition Does
As a data scientist raised in Brooklyn with a stats-driven mindset, I’ve watched the finals not through emotion—but through probability. Alex Caruso and Benicard Matherlin led key metrics: scoring, assists, steals. Yet their teams lost. Why? Statistical models show efficiency isn’t destiny; context is. This isn't about heart—it's about variance, pressure, and who gets overlooked when the clock runs out.
NBA Insights
nba finals
data-driven decision
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3 weeks ago