Guide

Analyzing Polymarket order book depth

Order book depth tells you how much capital is resting at each price level. This guide covers reading L2 data, building cumulative depth charts, identifying liquidity zones, and using depth patterns.

What this guide covers

L2 depth shows every price level, not just the top of book
Cumulative depth charts reveal where liquidity concentrates
Depth imbalances signal directional pressure
Depth patterns indicate market quality and execution risk

Reading L2 order book data

L2 order book data contains every price level with its associated size. Unlike L1 data (which only shows the best bid and ask), L2 shows the full depth of the book on both sides.

On Polymarket, prices range from 0 to 1, representing implied probability. A bid at 0.65 with size 500 means someone is willing to buy 500 shares of the outcome at 65 cents each.

Bids are sorted descending (best bid first), asks ascending (best ask first). The gap between the best bid and best ask is the spread.

When reading L2 data, pay attention to how quickly size drops off as you move away from the best price. A steep drop-off means thin liquidity beyond the top of book.

Building cumulative depth charts

A cumulative depth chart aggregates size from the best price outward. For bids, cumulate from best bid downward. For asks, cumulate from best ask upward.

The shape of the cumulative depth curve reveals market quality. A steep curve means most liquidity is concentrated near the top of book.

Depth charts are especially useful for estimating execution cost. If you want to buy 1,000 shares, the cumulative depth chart tells you how far into the book you need to walk.

Compare depth charts across markets to identify which markets have the deepest liquidity. BTC 5-minute markets typically have deeper books than ETH or SOL markets.

Depth imbalances and liquidity zones

A depth imbalance occurs when one side of the book has significantly more size than the other. If bid_depth is 2x ask_depth, it suggests buying pressure.

Liquidity zones are price levels where size concentrates. These act as support and resistance levels: prices tend to bounce off zones with heavy resting orders.

Track how depth imbalances evolve over time. A shift from balanced to imbalanced often precedes directional price moves.

When depth on one side suddenly vanishes, it often signals that a large market maker has withdrawn quotes. This can precede volatile moves.

Using depth to assess market quality

Market quality on Polymarket can be measured by the ratio of depth to spread. High depth with tight spread means a liquid market.

Low depth with wide spread means an illiquid market where even small orders may move the price. These markets carry higher execution risk.

Depth at specific price levels also matters. If there is heavy depth at 0.50 and thin depth elsewhere, the market is likely to consolidate around that price.

Use depth data alongside spread and VWAP metrics for a complete quality picture. The /metrics endpoint provides pre-computed depth values.

Code examples

import requests

BASE = "https://api.polyorderbooks.com/v1"
HEADERS = {"X-API-Key": "your-key"}

books = requests.get(
    f"{BASE}/markets/btc-updown-5m-1787486400/books",
    headers=HEADERS,
    params={"resolution": "1s"},
).json()

snap = books[0]
bid_cumulative = []
total = 0
for level in snap["bids"]:
    total += level["size"]
    bid_cumulative.append((level["price"], total))

for p, s in bid_cumulative:
    print(f"  {p:.4f} -> {s:.0f}")

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FAQ

What is the difference between L1 and L2 data?

L1 shows only the best bid and best ask (top of book). L2 shows every price level with its size. L2 is essential for depth analysis, fill simulation, and slippage estimation.

How do I identify liquidity zones?

Look for price levels with disproportionately large size compared to neighboring levels. These concentrations act as support/resistance.

Does depth predict price direction?

Depth imbalances are a directional signal but not definitive. Use depth as one input alongside spread, volume, and other indicators.

How does depth differ between BTC and ETH markets?

BTC markets typically have deeper books and tighter spreads than ETH markets. This reflects higher trading volume and more market maker participation.