Moneyball for Physical AI - by Animesh Garg

A Scaling Law Perspective for Marginal Utility per Dollar

In 2002, the Oakland Athletics won 103 games despite maintaining the third-lowest payroll in Major League Baseball. This advantage emerged because the market for player assets was mispriced: legacy scouts favored subjective aesthetics, stolen bases, and batting averages, whereas forward-looking management mathematically isolated on-base percentage, the statistic that actually correlated with runs. Finding the signal with the correct statistic in a field full of intuitive pundits: Moneyball! Data for Physical AI is misunderstood, and mis-priced. Data doesn’t exist for Physical AI. Data has…

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