Prediction markets are no longer niche financial experiments—they are becoming real-time probabilistic data layers for global events. Among them, Polymarket has emerged as the largest and most liquid prediction market platform, enabling users to trade on outcomes of real-world events using probability pricing.
In this article, we will explore how to work with Polymarket market data using Python, with a focus on the Polymarket V2 architecture, practical API usage, data modeling, and building analytics pipelines.
We’ll also integrate lessons from building trading bots, including insights from an open-source project:
And building on a previous article:
Official documentation reference:
