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Outbyte Driver Updater FREEFix the driver behind crashes, sound loss and screen glitchesFind Drivers →Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →A Polymarket bot can detect whether displayed bids or asks outweigh the other side by summing price-size levels in a defined slice of the order book and calculating I = (B - A) / (B + A). A positive value means more displayed bid size in that slice; a negative value means more ask size. It is a snapshot of visible liquidity—not proof of informed trading, lasting pressure, or a coming price move.
What an order-book imbalance tells you
Polymarket’s Central Limit Order Book (CLOB) provides a live view of displayed resting liquidity. Its documented architecture uses off-chain order matching and ordering, with on-chain settlement and execution. That distinction matters: a book state describes orders available to trade at a moment; it is not a settled-trade record. Polymarket’s CLOB API documentation, accessed October 7, 2026, describes this architecture.
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In this article, “visible liquidity pressure” means only that displayed size leans toward bids or asks in the measured part of the book. An imbalance does not establish who placed the orders, why they placed them, whether they will remain, whether they will be filled, or which side will initiate the next trade.
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Polymarket documents a market WebSocket at wss://ws-subscriptions-clob.polymarket.com/ws/market. A market subscription uses outcome asset IDs. Book events provide bid and ask levels as prices and sizes; price-change events provide changed levels and best-bid/best-ask information. These are the documented inputs for tracking the visible book, not an official imbalance signal.
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Keep each outcome asset’s book separate. Store timestamps with updates, build local state from a snapshot and subsequent changes, and define how the collector will resynchronize after a disconnect or suspected missed update. If the local book is stale or incomplete, a ratio calculated from it can be misleading. These are implementation safeguards for a bot, not a strategy Polymarket endorses.
How to calculate a reproducible imbalance
Use a defined depth band and calculate:
I = (B - A) / (B + A)
- B is the sum of bid sizes inside the selected band.
- A is the sum of ask sizes inside the same band.
- I ranges from -1 to +1 when the denominator is positive. Positive values indicate more displayed bid size; negative values indicate more displayed ask size.
- If both sums are zero, the denominator is zero and the measure is undefined. Omit that reading rather than treating it as neutral.
For example, in a hypothetical selected band with 60 units of bid size and 40 units of ask size, the ratio is (60 − 40) / (60 + 40) = 0.20. That says the measured slice has more displayed bid size; it does not mean the price has a 20% chance of rising or is expected to rise by 20%.
Choose and disclose the band
State whether the calculation uses the best price level, a fixed number of levels, or a price-distance band. The choice changes what the ratio describes. A top-of-book measure focuses on liquidity nearest the touch; a wider band includes more distant displayed size. Two bands can point in different directions because liquidity is distributed differently across prices.
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Show the underlying book with the ratio
Log the best bid and ask, spread, size by level, selected depth band, asset ID, last-update time, and how long the measured direction persists. A ratio without these inputs hides its scope and can make a fragile near-touch change look like a broad shift in liquidity.
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Turn a reading into a testable signal
- Collect and timestamp the book. Record snapshots and updates for the specific outcome asset. Track reconnects and resynchronization so you can identify intervals where local state may be unreliable.
- Compute separate variants. Compare a near-touch measure with one or more wider bands. If useful, test raw size against a distance-weighted version, but label the latter as your own analytical choice.
- Measure persistence. Record whether the sign and magnitude survive successive updates or a chosen time window. A single snapshot and a sustained imbalance are different observations.
- Compare with later outcomes. Evaluate against subsequent price changes and trades on later data. Keep the measurement window and outcome window explicit.
- Account for execution costs. Include spread, fees, and slippage when assessing whether any rule based on the measure would have been actionable.
- Keep threshold selection separate from evaluation. Do not choose a threshold using the same period on which you report its results. Test across market types and later periods before treating a pattern as useful.
No reviewed source establishes a universally effective threshold, look-ahead window, or profitability result for this imbalance heuristic. Treat those as choices to evaluate, not as validated defaults.
Why displayed imbalance is not proof of “real” market pressure
Displayed orders can change or disappear before they trade. A falling bid or rising ask quantity establishes that displayed depth changed; by itself, it does not show whether the cause was a fill, cancellation, repricing, or intent to mislead. Avoid labeling a change as spoofing, strategic withdrawal, or the behavior of a named bot without separate evidence.
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A 2026 preprint by Maksym Nechepurenko, version 2 revised July 30, 2026, argues that public executed-fill records do not reveal the quote lifecycle needed to identify market making, spoofing, or strategic withdrawal. Fill records and book observations therefore cannot, on their own, establish the motive behind a quote change.
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There is also a specific caution about inferring trade direction from the public feed. Philipp D. Dubach’s 2026 preprint, version 2 revised May 14, studied a pre-registered stratified panel of 600 markets. It reports a panel mean of 0.615, with a 95% confidence interval of 0.58–0.65—about 59% agreement between feed-inferred trade-direction buckets and on-chain ground truth. The preprint describes an archive of 30 billion feed events over 52 days. Those figures describe that study’s sample and method, not the accuracy of every bot, market, or direct depth-imbalance calculation. The work is a preprint, not established here as peer reviewed.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What to report so another person can interpret the result
- The outcome asset and timestamp, plus whether the local book was synchronized.
- The depth-band definition, summed bid and ask sizes, and the resulting ratio.
- Best bid, best ask, spread, and level-by-level depth used in the calculation.
- The persistence window and whether the imbalance agreed across narrower and wider bands.
- The later outcome definition and evaluation period, including spread, fees, and slippage assumptions.
Reporting the inputs alongside the ratio makes it possible to distinguish a narrow, fleeting skew from a broader and more persistent distribution of displayed size—without claiming that either proves intent or predicts a move.
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