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Trade / Fill Data

Trade data,
straight from the source

2.6B+ trades from Polymarket and Kalshi. Every fill with price, size, taker/maker IDs, and fees — Polymarket indexed directly from on-chain Polygon transactions, Kalshi from the exchange.

Get Started

2.6B+

Trades tracked

$170B+

Volume indexed

2

Platforms

~1min

Refresh interval

Blockchain-Derived

Indexed from the source

For Polymarket, every fill is derived directly from Polygon blockchain transactions — not scraped from an API. This means complete coverage with no missed trades, plus on-chain metadata like wallet addresses.

  • Polymarket fills derived directly from Polygon blockchain transactions
  • Taker and maker wallet addresses preserved for on-chain analysis
  • Every fill includes normalized price, raw price, size, side, and fees
  • No data missed — we index every on-chain trade, not just API snapshots
Data Pipeline

Polygon Blockchain

Raw on-chain transactions

Probalytics Indexer

Decode, normalize, enrich

Unified Fills Table

2.6B+ trades, ready to query

Data Schema

Every field you need

Each fill includes execution details, participant IDs, normalized pricing, and fees. Same schema across Polymarket and Kalshi.

  • Python SDK — client.fills() returns a Polars or pandas dataframe
  • REST API with filtering by market, platform, and date range
  • Direct SQL queries on the fills table via ClickHouse
  • Daily and weekly Parquet exports for bulk analysis and backtesting
Fills SchemaSample fields
FieldTypeDescription
idUUIDUnique fill id
market_idUUIDInternal market id
platformEnum8('POLYMARKET', 'KALSHI', …)Source venue
sizeDecimal(38, 18)Contracts filled
priceDecimal(38, 18)Execution price (0–1)
normalized_priceDecimal(38, 18)Price normalized to YES
taker_sideEnum8('BUY', 'SELL')Aggressor side
taker_cash_flowDecimal(38, 18)Taker USDC flow
taker_idNullable(String)Taker wallet
maker_idNullable(String)Maker wallet
feeDecimal(38, 18)Fee paid
timestampDateTime64(6)Fill time
View full schema in docs →
SQL Access

Query trades with SQL

Run analytical queries on 2.6B+ trades via ClickHouse. Aggregate volume, analyze price impact, or export results for further analysis.

SQL Console
ClickHouse 
-- Top markets by volume in the last 7 days
SELECT
  market_id,
  platform,
  count() as trade_count,
  sum(size) as total_volume,
  avg(normalized_price) as avg_price
FROM fills
WHERE timestamp > now() - INTERVAL 7 DAY
GROUP BY market_id, platform
ORDER BY total_volume DESC
LIMIT 10
10 rows · 340ms Run Query

Coverage

Platform breakdown

Polymarket

Live

1.19B+

Trades

$55B+

Volume

Nov 2022

Data since

Polygon blockchain

Data source

Polymarket Perpetuals

Live

Full coverage

Trades

Full coverage

Volume

May 2026

Data since

Perpetual futures

Data source

Kalshi

Live

1.42B+

Trades

$115B+

Volume

Jan 2022

Data since

Exchange API

Data source

Kalshi Perpetuals

Live

Full coverage

Trades

Full coverage

Volume

Jun 2026

Data since

Perpetual futures

Data source

Figures as of August 2026.

Use Cases

What you can do with trade data

Wallet Analytics

Track trading activity by wallet address. Identify top traders, analyze PnL, and study participant behavior on-chain.

Backtesting

Replay exact trade history for strategy backtesting. Every fill with real prices, sizes, and timestamps.

Volume Analysis

Track $170B+ in trading volume across both venues. Analyze volume patterns around events and resolutions.

Predictive Models

Build ML models on trade flow data. Use taker/maker ratios, volume spikes, and price impact as features.

Trade Data

Ready to analyze prediction market trades?

Access 2.6B+ trades from Polymarket and Kalshi.

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