Volume Monitor
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How the Liquidation Heatmap Is Estimated

Exchanges don't publish where their users' liquidation prices sit, so every liquidation heatmap outside Hyperliquid is a model. This page shows exactly how ours is built, and scores it every day against liquidations that actually happened, next to a simple baseline it has to beat.

There isn't enough scored data yet to say whether the model beats a simple baseline. The scoreboard fills in daily.

Model est-1.0+hl-2026-09-27Scored on BybitWindow 2026-08-28 to 2026-09-27

Does the model beat the baseline?

Last 30 complete days · 2026-08-28 to 2026-09-27 UTC
  • insufficient data4-hour horizon: not enough data for a verdict yet (0 of the 48 scored snapshots needed).
  • insufficient data24-hour horizon: not enough data for a verdict yet (0 of the 48 scored snapshots needed).

Validation scoreboard

Model est-1.0+hl-2026-09-27 · realised Bybit liquidations · computed 2026-09-27T18:34:12+00:00
Horizon Rank corr. (model) Rank corr. (baseline) Skill Model ahead Calibration Log-lik. gain Top-3 hit (model / baseline / random) Scored snapshots Coins Verdict
4h — — — — — — — / — / — 0 0 insufficient data
24h — — — — — — — / — / — 0 0 insufficient data

A verdict needs at least 48 scored snapshots per horizon. Skill above 0 means the model ranks the levels where liquidations happened better than the baseline; below 0 means it does worse. We publish the numbers either way.

How the estimate is built

Model est-1.0+hl-2026-09-27
  1. Inputs. Open interest, price bars and volume that this site records from exchanges' public APIs, in 5-minute to 1-hour buckets.
  2. Opens. Every rise in open interest is booked as a new long and a new short (each contract has both sides) at the bucket's volume-weighted price.
  3. Liquidation levels. Each new position's liquidation price is spread over the distance-from-entry distribution below: longs below the entry, shorts above.
  4. Closes and decay. Falls in open interest close positions proportionally at every level, and all positions decay with a half-life, because most positions are closed without ever being liquidated.
  5. Clearing. When price trades through a level, the positions there count as liquidated and the level is removed.
SettingValueWhy
Model versionest-1.0+hl-2026-09-27stamped on every estimated chart; a new version is scored from scratch
Position half-life5 daysshare of modelled positions still open after this long: half
Price bin width0.25%log-spaced price levels
Maximum leverage100xno liquidation level closer to entry than 1/leverage - margin
Maintenance margin0.5%liquidation price = bankruptcy price adjusted by this rate
Open cap per bucket25% of OIlarger jumps (new listings, unit changes) are capped
Close cap per bucket50% of OI—

Where liquidation prices sit

Measured on real Hyperliquid positions
Liquidation distance from entryShare of new positions
0% – 2%12.0%
2% – 5%7.0%
5% – 10%20.0%
10% – 20%18.0%
20% – 50%17.0%

The other 26.0% of new positions sit more than 50% from entry or can't be liquidated, and aren't placed on the map. Hyperliquid positions are on-chain, so their real liquidation prices can be measured; the same distribution is used for every coin and exchange. See the Hyperliquid liquidation map for real positions.

How it is scored

Daily, on Bybit data only
  • Ground truth. Bybit publishes every liquidation on its public stream (see data coverage), so the model is replayed on Bybit data alone and scored against Bybit's real liquidations.
  • Snapshots. The model's state at the end of every UTC hour, from a 7-day replay, is compared with what happened over the next 4 and 24 hours. A snapshot is skipped if under 80% of that period has price data.
  • Only levels price reached count. Levels are 0.50% wide; a level price never crossed can't show whether it was right, so it is left out. At least 5 crossed levels are needed for a rank correlation.
  • Baseline. The same open interest spread over the same distance distribution around the current price, with no history. If the model can't beat this, its complexity isn't earning anything.
Snapshot
The model state at the end of each whole UTC hour, replayed on Bybit data only.
Traversed bins
0.5% log price bins that price crossed within the horizon: long levels from the horizon's low to the price at the snapshot, short levels from that price to the high.
Realised
Bybit allLiquidation notional in the horizon, binned at the liquidation price (bankruptcy price adjusted by the maintenance margin rate).
Baseline
Open interest at the snapshot spread over the same distance prior around the current price, with no open-interest history.
Rank correlation (rho)
Spearman rank correlation between predicted and realised USD across traversed bins, per snapshot; the scoreboard shows medians.
Skill
Median of model rho minus baseline rho over the same snapshots; > 0 means the model beats the baseline.
Calibration
Sum of realised / sum of predicted USD over traversed bins (below 1: the map overstates, as vendors say theirs do).
Log-likelihood gain
Median log-likelihood gain of the model over the baseline, nats per realised USD.
Top-k hit rate
Share of the top-3 predicted bins per snapshot with at least $10,000 realised; the random rate is the share of all traversed bins.

Known limits

  • Price bars are last-trade prices, not mark prices, which exchanges use to trigger liquidations.
  • Opens and closes inside one open-interest snapshot cancel out, so fast in-and-out positions are invisible.
  • One distance distribution is used for every coin and both sides.
  • The scoreboard uses Bybit only; other exchanges publish a sample of their liquidations and can't be scored fairly.
  • USD values on the heatmaps are modelled amounts; read them as relative intensity. Estimates may be materially wrong. Not financial advice.

See the estimates: liquidation heatmaps for every major coin.

Liquidation heatmap methodology FAQ

Is the liquidation heatmap real data?

No. Exchanges don't publish where their users' liquidation prices sit, so the heatmap is an estimate built from open interest, price and volume. Only on Hyperliquid, where positions are on-chain, can real liquidation prices be read; the Hyperliquid liquidation map uses those instead.

How accurate is the estimated heatmap?

Every day it is scored against the Bybit liquidations that actually happened in the next 4 and 24 hours, and compared with a simple baseline. The scoreboard on this page shows the latest numbers, including when the model loses.

What is the baseline?

Current open interest spread over the same distance-from-entry distribution, centred on the current price, with no history of when positions were opened. If the model can't beat that, its extra complexity isn't earning anything.

Why score it against Bybit only?

Bybit publishes every liquidation on its public stream, so it is the one exchange where the realised liquidations are complete. Other exchanges only publish a sample (see the data coverage page), which would make any score look better or worse than it is.

Can I cite these numbers?

Yes. The scoreboard is recomputed daily from stored data and stamped with the model version. Please link to this page so readers see the method and the current verdict.