Event Metadata Feed
In prediction markets, probabilities alone do not explain what an event represents. An event metadata feed includes descriptive details such as event titles, categories, timelines, resolution rules, and outcome definitions.
This metadata helps users and systems understand what each market is actually predicting. It clarifies scope, reduces ambiguity, and ensures forecasts are interpreted correctly.
Event metadata feeds are especially important when working with large numbers of markets. They allow analysts to group events, filter by type, and align forecasts with comparable events.
Metadata also supports automation. Models rely on consistent event identifiers, timestamps, and resolution attributes to process prediction markets data accurately. For analysts, event metadata feeds provide the structural layer that makes prediction markets data usable at scale. They turn raw probabilities into interpretable, organized information.
Why It Matters
Without metadata, prediction markets data can be confusing or misinterpreted. Event metadata feeds ensure probabilities are analyzed in the correct context.
What is an event metadata feed in prediction markets?
In prediction markets, an event metadata feed is a structured dataset describing each market event. It includes information like event type, timing, and resolution criteria. This helps users understand what probabilities refer to. It is essential for correct interpretation.
How does an event metadata feed improve prediction markets data analysis?
Event metadata feeds allow analysts to organize and filter prediction markets data effectively. They enable comparison across similar events and prevent mixing unrelated markets. Metadata improves accuracy in modeling and reporting. It adds meaning to probability signals.
Why is an event metadata feed important for prediction markets APIs?
Prediction markets APIs often deliver both probabilities and metadata together. Event metadata feeds give analysts the context needed to process data programmatically. They support indexing, validation, and lifecycle tracking. APIs make metadata consistently available across markets.
Real-World Example
On Kalshi, event metadata may specify the exact economic indicator, release schedule, and resolution source. This metadata ensures traders and analysts interpret probability movements correctly.
Event Metadata Feed and FinFeedAPI
FinFeedAPI’s Prediction Markets API provides event metadata feeds alongside prediction markets data. Analysts can access structured event details, identifiers, and timing information. This supports data organization, automated analysis, and accurate modeling. The API enables consistent metadata integration across prediction markets.