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Baseball pitch data displayed as rows and columns in a glowing grid, representing Moddy's MLB event-level dataset

Every aggregated MLB stat had its question baked in years ago. Raw events flip the model — every pitch is a row with 20+ tags. Seven example formulas show what's possible when you write the question yourself instead of consuming someone else's.

abstract data streams flowing from the keyboard into an intricate, luminous network on the screen, representing the creation of an AI prediction model

Everyone's building AI sports prediction tools in 24 hours. But there's a difference between a model that looks like it's finding edge and one that actually is — and a viral experiment involving Dwayne Johnson explains exactly why.

DNA molecule illustrating near-infinite combinations

Building a sports prediction model is actually three problems: building something predictive, figuring out how to bet on it profitably, and proving the edge is real. Most tools solve one. Here's how Moddy solves all three — and what's happening under the hood when you build a model.

A tightrope walker above NBA basketball court illustrating razor thin moneyline margins

A look inside one of Moddy's NBA models — and what it reveals about why winning bets doesn't always mean making money