Fills (Trades)

Shape

A fill is one normalized trade execution. It links to a market and one of that market’s outcomes.

Field	Type	Values and meaning
`id`	`UUID`	Stable Probalytics fill ID. Generated deterministically from the venue trade or chain event.
`market_id`	`UUID`	Probalytics market ID. Join this to `markets.id`.
`market_platform_id`	`string`	Venue-native market identifier copied from the linked market.
`platform`	`enum`	`POLYMARKET` or `KALSHI`.
`platform_id`	`string`	Venue-native trade, order, or execution ID. The exact source differs by product.
`outcome`	`Outcome`	Traded outcome containing `id` (UUID), `platform_id` (string), `name` (string), and zero-based `index` (integer).
`size`	`decimal`	Executed quantity. Prediction markets use contracts/shares; perpetual and margin products use venue instrument units.
`price`	`decimal`	Execution price for the stored `outcome`. Prediction-market prices are normally between `0` and `1`; perpetual prices are instrument prices.
`normalized_price`	`decimal`	Prediction markets: execution price expressed as the price of outcome index `0`. Perpetual and margin products: same value as `price`.
`taker_side`	`enum`	`BUY` or `SELL`. The exact mapping is product-specific and documented below.
`taker_cash_flow`	`decimal`	Positive gross/notional value assigned to the taker. It is not signed by trade direction.
`maker_cash_flow`	`decimal`	Positive gross/notional value assigned to the maker. It is not signed by trade direction.
`taker_id`	`string \| null`	Taker wallet or participant ID when exposed by the source. Currently populated for Polymarket prediction-market fills.
`maker_id`	`string \| null`	Maker wallet or participant ID when exposed by the source. Currently populated for Polymarket prediction-market fills.
`fee`	`decimal`	Source fee amount when available. `0` is also used when the source does not expose fees.
`source_block_number`	`integer \| null`	Chain block containing the execution. Present for Polymarket prediction-market fills.
`source_tx_hash`	`string \| null`	Chain transaction hash when available.
`source_log_index`	`integer \| null`	Event position within the chain transaction.
`timestamp`	`datetime`	Source execution time in UTC.
`indexed_at`	`datetime`	Time Probalytics wrote the fill.
`metadata`	`object`	Product-specific annotations. Values are strings, numbers, or booleans. Usually empty for prediction-market fills.

Coverage by venue and product

Venue	Product	Fills	Coverage starts
Polymarket	Prediction-market trades	1,171,916,395	2022-11-21
Polymarket	Perpetual trades	9,580,526	2026-05-06
Kalshi	Prediction-market trades	1,360,159,691	2022-01-01
Kalshi	Margin trades	25,225,233	2026-06-03

_{Counts as of 2026-08-24 17:59 UTC. Coverage starts use the earliest source timestamp. Prediction and perpetual/margin rows are separated using the linked market’s market_type.} Fills are indexed continuously, so these counts change throughout the day. Query the data warehouse for current values:

WITH market_id IN (
    SELECT id
    FROM markets FINAL
    WHERE market_type = 'PERPETUAL'
) AS is_perpetual
SELECT
    platform,
    if(is_perpetual, 'PERPETUAL', 'PREDICTION') AS product,
    count() AS fills,
    min(timestamp) AS earliest_fill
FROM fills
GROUP BY platform, product
ORDER BY platform, product;

Polymarket prediction-market trades

Source

These fills come from OrderFilled events emitted on Polygon by the supported CTF Exchange and Neg Risk Exchange contracts, including their V2 versions. Legacy executions can emit two related OrderFilled logs. Probalytics retains the maker-focused representation instead of publishing both as separate trades.

Field mapping

Polymarket source	Probalytics field
Transaction hash + log index + taker address	`id`
Outcome token’s linked market	`market_id`, `market_platform_id`
Order hash	`platform_id`
Outcome token ID	`outcome`
Outcome-token amount ÷ `1,000,000`	`size`
USDC amount ÷ outcome-token amount	`price`
`price` for outcome index `0`; otherwise `1 - price`	`normalized_price`
Taker pays USDC	`taker_side = 'BUY'`
Taker supplies outcome tokens	`taker_side = 'SELL'`
USDC amount ÷ `1,000,000`	`taker_cash_flow`, `maker_cash_flow`
Taker and maker wallet addresses	`taker_id`, `maker_id`
Event fee ÷ `1,000,000`	`fee`
Block number, transaction hash, log index	Source provenance fields
Block timestamp	`timestamp`

Outcome index 0 is the reverse-alphabetically first normalized market outcome. For a typical Yes/No market, Yes is index 0 and No is index 1.

Polymarket perpetual trades

Polymarket perpetual trades come from the perpetual product feed and link to markets with market_type = 'PERPETUAL'.

Polymarket perpetual source	Probalytics field
Instrument ID	`market_id`, `market_platform_id` through the linked market
Trade ID	`id`, `platform_id`
Synthetic Long outcome	`outcome`
Quantity	`size`
Instrument price	`price`, `normalized_price`
`long`	`taker_side = 'BUY'`
`short`	`taker_side = 'SELL'`
`size × price`	`taker_cash_flow`, `maker_cash_flow`
Source timestamp in milliseconds	`timestamp`
Source transaction hash, when present	`metadata.tx_hash`

Participant IDs are null, and fee is 0 because the current source does not expose those values.

Kalshi prediction-market trades

Source

These fills come from Kalshi trade records. Each record contains the market ticker, Yes and No prices, traded count, taker side, trade ID, and execution time.

Field mapping

Kalshi source	Probalytics field
Market ticker	`market_id`, `market_platform_id` through the linked market
Trade ID	`id`, `platform_id`
`taker_side = 'yes'`	Yes `outcome`; `price = yes_price_dollars`
`taker_side = 'no'`	No `outcome`; `price = no_price_dollars`
`count_fp`	`size`
`yes_price_dollars`	`normalized_price`
Every current Kalshi prediction fill	`taker_side = 'BUY'`
`size × price`	`taker_cash_flow`, `maker_cash_flow`
`created_time`	`timestamp`

The source’s Yes/No taker side selects which outcome was bought. It does not map to the stored BUY/SELL enum, so all current Kalshi prediction fills are stored as BUY. Participant IDs are null, and fee is 0 because the current trade source does not expose those values. Kalshi KXMVE trades are not included in fills because their markets are not available to this normalization path.

Kalshi margin trades

Kalshi margin trades come from the margin product feed and link to markets with market_type = 'PERPETUAL'.

Kalshi margin source	Probalytics field
Margin ticker	`market_id`, `market_platform_id` through the linked market
Trade ID	`id`, `platform_id`
Synthetic Long outcome	`outcome`
Count	`size`
Instrument price	`price`, `normalized_price`
`taker_side = 'bid'`	`taker_side = 'BUY'`
`taker_side = 'ask'`	`taker_side = 'SELL'`
`size × price`	`taker_cash_flow`, `maker_cash_flow`
`created_time`	`timestamp`
Product marker	`metadata.instrument_type = 'perpetual_future'`

Participant IDs are null, and fee is 0 because the current source does not expose those values.

Reading fills across products

Join market_id to markets.id before interpreting price or size units.
Use price for the stored outcome’s execution price.
Use normalized_price to create one outcome-0 price series for prediction markets.
Do not treat perpetual normalized_price as a probability.
Do not sum the cash-flow fields as signed P&L; both currently store positive gross/notional values.

See Tables & Schemas for access-specific database types and query behavior.

Getting Started

Datasets

Access Methods

REST API

Reference

Support

Shape

Coverage by venue and product

Polymarket prediction-market trades

Source

Field mapping

Polymarket perpetual trades

Kalshi prediction-market trades

Source

Field mapping

Kalshi margin trades

Reading fills across products

​Shape

​Coverage by venue and product

​Polymarket prediction-market trades

​Source

​Field mapping

​Polymarket perpetual trades

​Kalshi prediction-market trades

​Source

​Field mapping

​Kalshi margin trades

​Reading fills across products

Shape

Coverage by venue and product

Polymarket prediction-market trades

Source

Field mapping

Polymarket perpetual trades

Kalshi prediction-market trades

Source

Field mapping

Kalshi margin trades

Reading fills across products