polyorderbooks/polymarket-btc-5min-historical-l2

Polymarket BTC 5-Minute Historical L2 Order Books

Full level-2 order book snapshots captured at 1-second resolution for one resolved Polymarket BTC 5-minute up/down market — every resting bid and ask, not just top-of-book.

One row per (timestamp, outcome). 600 rows covering 300 seconds across both outcomes.

from datasets import load_dataset

ds = load_dataset("polyorderbooks/polymarket-btc-5min-historical-l2", split="train")
row = ds[0]

print(row["timestamp"], row["outcome"])
print("best bid", row["best_bid"], "best ask", row["best_ask"])
print("depth", len(row["bids"]), "bid levels /", len(row["asks"]), "ask levels")

Why this dataset exists

Most publicly available Polymarket data is midpoints or daily candles. That is enough to plot a price line and not enough to answer the question that matters for execution research: what would this trade actually have cost?

A midpoint says the market was at 0.195. The ladder says only 13.6 was available at the best ask, and filling 100 units would have averaged 0.2086 — 4.3% worse than top of book. That difference is invisible in candle data and is the reason backtests built on midpoints overstate returns.

Coverage

Market	btc-updown-5m-1786596600 — Bitcoin Up or Down, Aug 13 12:50–12:55AM ET
Rows	600
Timestamps	300 (1 per second)
Outcomes	Yes, No
Capture resolution	1 second
Ladder depth	1–74 levels per side
Resolution outcome	Yes
Crossed books	0
Prices outside [0, 1]	0

Schema

Field	Type	Description
timestamp	string	UTC, ISO-8601, one per second
market_id	string	PolyOrderbooks market identifier
market_slug	string	Polymarket slug
question	string	Market question text
outcome	string	Yes or No
token_id	string	Polymarket CLOB token ID for the outcome
bids	list of {price, size}	Full bid ladder, best (highest) first
asks	list of {price, size}	Full ask ladder, best (lowest) first
best_bid / best_ask	float	Top of each ladder
spread	float	best_ask - best_bid
mid_price	float	(best_bid + best_ask) / 2
bid_levels / ask_levels	int	Number of price levels on each side
bid_depth / ask_depth	float	Notional depth, sum(price * size)
resolved_winner	string	Final resolution of the market

Prices are probabilities in [0, 1]. Sizes are fractional, not integer share counts.

Working with the ladders

def simulate_buy(row, target_size):
    """What it would actually have cost to buy target_size."""
    filled = cost = 0.0
    for level in row["asks"]:
        take = min(level["size"], target_size - filled)
        cost += take * level["price"]
        filled += take
        if filled >= target_size:
            break
    if filled < target_size:
        return None                      # ladder exhausted — not fillable
    return {"avg_price": cost / filled, "slippage": cost / filled - row["asks"][0]["price"]}

Two properties of this data are worth knowing before you model with it:

• The two outcomes are complementary. Yes_bid + No_ask == 1 and Yes_ask + No_bid == 1, structurally. Useful as an integrity check on your own pipeline.
• Depth varies per snapshot and per side. Between 1 and 74 levels here. Code that assumes a fixed number of levels will silently truncate.

Use cases

Execution-aware backtesting · slippage and fill modelling · spread and depth regime analysis · market microstructure research on short-horizon prediction markets · validating an order book reconstruction pipeline against a known-good reference.

Source and methodology

Captured from the Polymarket CLOB by PolyOrderbooks, a historical Polymarket data API covering prices, liquidity metrics, and L2 order books.

Snapshots are recorded as observed, at 1-second cadence, with no synthetic interpolation. A repeated ladder across consecutive seconds means the book did not change, or no new capture landed in that second — the data does not distinguish the two, which matters if you are computing update frequency or realised volatility from it.

• Sample page and CSV download: polyorderbooks.com/datasets/polymarket-btc-5min-orderbook-sample
• Working with L2 data: docs.polyorderbooks.com/historical/order-books
• API quickstart: docs.polyorderbooks.com/quickstart

Larger coverage

This is a single market. The full archive covers Polymarket crypto markets continuously at 1-second capture, available through the REST API and Python SDK:

pip install polyorderbooks

License

Creative Commons Attribution 4.0 (CC BY 4.0).