Prediction Markets Explained: Probability, Calibration, and Information Efficiency
Blockchain
AI
Prediction markets express event probabilities through traded prices. Since the second half of 2025, trading volumes on platforms such as Kalshi and Polymarket have risen significantly, with sports, macroeconomics, and crypto topics becoming highly active segments. At the same time, the CFTC is advancing event contract rules, while federal-state regulatory jurisdictional disputes continue—"popular" and "credible" should not be treated as synonymous.
For crypto users, prediction markets serve both as event information dashboards and potential trading entry points. In March 2026, Gate integrated Polymarket, allowing users to participate in selected prediction markets using spot USDT. Gate for AI Agent, meanwhile, can integrate market data, news, and other capabilities into clients such as Cursor and Claude to help organize event background information. This course explains how to read probabilities, assess calibration, and judge information efficiency; Gate-related products appear only in the context of reading workflows and boundary illustrations. The entire content is for educational purposes only and does not constitute investment advice or gambling guidance.
About the Course
The course consists of 6 sessions, structured as "price equals probability → events and settlement → calibration and assessment → information efficiency → regulatory boundaries → reading discipline." Lesson 1 establishes the basic definitions of prediction markets and distinguishes them from traditional gambling and futures. Lesson 2 discusses how events are written and settled, and why controversial definitions matter more than prices themselves. Lesson 3 introduces the concept of calibration and explains how to measure whether the market "got it right." Lesson 4 analyzes the impact of liquidity, spreads, manipulation, and smart-money narratives on information efficiency. Lesson 5 reviews the regulatory landscape of the CFTC, U.S. states, and major platforms in 2025–2026. Lesson 6 concludes with a reusable reading framework and explains how it connects to macro observation of crypto markets. The Gate-Polymarket integration appears only lightly in access pathways and reading scenarios, and does not constitute a product recommendation session.
What You Will Learn
Conversion between prediction market prices and implied probabilities, and common misinterpretation pitfalls
How event definitions, settlement sources, and dispute resolution determine "what you are betting on"
Calibration, Brier scores, and methods for assessing "when the market got it right"
The impact of liquidity, spreads, manipulation, and whale narratives on information efficiency
The 2025–2026 regulatory landscape and user compliance awareness
A reading workflow combining Gate's prediction market and Gate for AI Agent
The four-tier capability boundaries of Agents: when to read only, when manual verification is required, and when execution should never be authorized
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