common.predictions.kalshi_events table provides event-level metadata for Kalshi prediction markets. Events serve as containers that group related markets together. This table combines both settled and non-settled events.
Use this table for event categorization, series analysis, understanding multi-market events, and tracking event-level patterns.
Table Columns
Data Notes:- Events group multiple related markets together
- Combines settled and non-settled events
- MVE (Multi-Variable Event) indicators help identify complex event structures
event_ticker
| Column Name | Data Type | Description |
|---|---|---|
| project | VARCHAR | Project identifier, always ‘kalshi’. |
| protocol | VARCHAR | Protocol identifier, always ‘kalshi’. |
| event_ticker | VARCHAR | Unique event identifier. |
| series_ticker | VARCHAR | Series ticker identifier grouping similar events. |
| category | VARCHAR | Category classification (auto-corrected for sports based on series_ticker). |
| title | VARCHAR | Event title. |
| sub_title | VARCHAR | Event subtitle (MVE indicator). |
| mutually_exclusive | BOOLEAN | Boolean flag indicating if event outcomes are mutually exclusive. |
| strike_period | VARCHAR | Strike period for the event. |
| strike_date | TIMESTAMP_NTZ(9) | Strike date for the event. |
| available_on_brokers | BOOLEAN | Boolean flag indicating if available on brokers. |
| collateral_return_type | VARCHAR | Type of collateral return. |
| is_settled | BOOLEAN | Boolean flag indicating if the event is settled. |
Understanding Event Structure
Event vs Market
- Event: A container grouping related prediction markets (e.g., “2024 Presidential Election”)
- Market: Individual prediction markets within an event (e.g., “Will Trump win?”, “Will Biden win?”)
- One event can have multiple markets, all sharing the same
event_ticker
Series Ticker
Theseries_ticker groups similar events across time. For example:
NFL-WEEK1,NFL-WEEK2,NFL-WEEK3all belong to the NFL seriesECON-JOBSmight represent monthly employment report events