Markets

The common.predictions.kalshi_markets table provides comprehensive metadata for Kalshi prediction markets including market details, pricing, settlement rules, and resolution outcomes. This table combines both settled and non-settled markets. Use this table to discover markets, analyze settlement patterns, understand market structure, and track outcomes across different categories.

Table Columns

Unique Key: market_unique_id

Column Name	Data Type	Description
project	VARCHAR	Project identifier, always ‘kalshi’.
protocol	VARCHAR	Protocol identifier, always ‘kalshi’.
market_unique_id	VARCHAR	Unique identifier for the Kalshi market ticker.
market_event_id	VARCHAR	Event identifier that groups related markets together.
market_series_id	VARCHAR	Series ticker identifier for the event.
market_mve_id	VARCHAR	Multi-variable event (MVE) collection ticker.
market_name	VARCHAR	Market title describing the prediction question.
question_id	VARCHAR	Question identifier.
question	VARCHAR	Question text from the event.
description	VARCHAR	Market description.
last_token_price	FLOAT	Last traded price as a float (0-1 scale).
market_status	VARCHAR	Current status (active, open, closed, finalized, settled).
active	BOOLEAN	Boolean flag indicating if the market is active or open.
closed	BOOLEAN	Boolean flag indicating if closed, finalized, or settled.
accepting_orders	BOOLEAN	Boolean flag indicating if currently accepting orders.
category	VARCHAR	Category classification of the market.
start_date	TIMESTAMP_NTZ(9)	Timestamp when the market opened for trading.
end_date	TIMESTAMP_NTZ(9)	Timestamp when the market closes for trading.
expected_expiration_time	TIMESTAMP_NTZ(9)	Expected timestamp for market expiration.
expiration_time	TIMESTAMP_NTZ(9)	Actual expiration timestamp of the market.
latest_expiration_time	TIMESTAMP_NTZ(9)	Latest possible expiration timestamp.
seconds_delay	NUMBER	Settlement timer in seconds.
can_close_early	BOOLEAN	Boolean flag indicating if the market can close before expiration.
expiration_value	VARCHAR	Value used to determine market settlement.
strike_type	VARCHAR	Type of strike price (if applicable).
floor_strike	FLOAT	Floor strike price for ranged markets.
cap_strike	FLOAT	Cap strike price for ranged markets.
rules_primary	VARCHAR	Primary rules governing the market settlement.
rules_secondary	VARCHAR	Secondary rules for market settlement.
early_close_condition	VARCHAR	Conditions under which the market can close early.
mve_collection_ticker	VARCHAR	Multi-variable event collection ticker.
mve_selected_legs	VARCHAR	Selected legs for multi-variable events.
market_outcome_resolution	VARCHAR	Market outcome resolution (or ‘unresolved’ if still open).
resolved_at	TIMESTAMP_NTZ(9)	Timestamp when the market was resolved (expiration_time).

Understanding Market Structure

Market Status Flow

Markets progress through different statuses:

active/open: Market is accepting trades
closed: Market has stopped accepting new orders
finalized: Market is awaiting settlement
settled: Market outcome has been determined and market is settled

Multi-Variable Events (MVE)

MVE markets group multiple related prediction markets and conditions together into one. For example:

“Which NBA Player will score 20+ pts today?” might have markets for:
- Yes. Stephen Curry
- Yes. Lebron James
- Yes. Kevin Durant

All these related markets share the same market_mve_id.

Overview

Data Verticals

Solana

Hyperliquid

Lighter

Bitcoin Ecosystem

EVM

Cosmos Ecosystem

Move Ecosystem

Other Ecosystems

Table Columns

Understanding Market Structure

Market Status Flow

Multi-Variable Events (MVE)

​Table Columns

​Understanding Market Structure

​Market Status Flow

​Multi-Variable Events (MVE)

Table Columns

Understanding Market Structure

Market Status Flow

Multi-Variable Events (MVE)