
Orderbooks, Trades & History
This page covers activity signals: orderbook depth, trade prints, and time-series history.
Use it to measure liquidity, detect regime changes, and build market-quality metrics.
API conventions
These routes are read-oriented. They are designed for analytics, monitoring, and automation.
Auth:
Authorization: Bearer $ACCESO_API_KEYBase URL:
https://<YOUR_ACCESO_API_HOST>Response envelope: stable
success/data/meta
{
"success": true,
"data": {},
"meta": {
"request_id": "req_1c2d3e",
"timestamp": 1765939200
}
}Normalization: timestamps are epoch seconds. IDs are opaque strings.
Pagination (when available):
limit,cursor(opaque),direction=asc|desc(route-dependent)Freshness: sources can be eventually consistent. “Latest” routes may be briefly cached.
Orderbook snapshots
Orderbooks represent current liquidity. Availability varies by market and venue behavior.
What you typically get
market_idas_of(snapshot timestamp)bids[]andasks[]as price levels:pricesize(orquantity)count(optional, number of orders aggregated)
best quotes:
best_bidbest_askspread(when derived)
Common uses
depth-at-price and depth-at-spread analysis
spread monitoring
imbalance and pressure signals (bid vs ask)
Representative routes
GET /v1/polymarket/markets/<MARKET_ID>/orderbookGET /v1/polymarket/markets/<MARKET_ID>/orderbook?depth=25(when supported)
Orderbooks are a point-in-time view. Do not treat them as a replayable event stream. Use the trade feed for executed activity.
Trades and prints
Trades are the cleanest execution signal. They are optimized for analysis and aggregation.
What you typically get
trade_id(opaque)market_idtimestamppricesizeside(buy/sell, when derivable)
Representative routes
GET /v1/polymarket/markets/<MARKET_ID>/trades?limit=200GET /v1/polymarket/markets/<MARKET_ID>/volume?window=1h(route-dependent)
Historical data products
Historical routes support modeling and backtests.
Common outputs:
price series (sampled snapshots)
OHLCV-style candles
volume series per window
Common knobs:
start,end(epoch seconds)interval(deployment-dependent)
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