1. What a liquidation heatmap actually shows
A liquidation heatmap is a 2D chart with price on the y-axis and time on the x-axis. At each price level, the colour encodes the USD-equivalent notional that would be liquidated if price touched there. Darker colour means a bigger cluster of forced exits waiting.
Underneath, the heatmap is built from estimated open interest, leverage distributions and the maintenance margin formula. The provider does not have your account, but they can model what fraction of OI is at what implied liq price given typical leverage stats. The output is good enough to be useful, but it is an estimate, not exchange-confirmed truth.
The shorthand: dark band = lots of forced exits waiting at that price. Light band = sparse, easy passage. A market moving toward a dark band is moving toward a place where price action accelerates.
2. Where the data comes from — CoinGlass's method
The standard free reference is CoinGlass's liquidation heatmap. They aggregate position data from Binance, OKX and Bybit, then model the per-leverage-tier liq prices using each exchange's MMR table. They produce two views: a price-time heatmap and a stacked OI / leverage breakdown.
Glassnode has a more academic version on the futures liquidation volume metric — see their derivatives liquidation volume dashboard. Free tier limits the granularity, but it is a good cross-check.
For the academic definition of a liquidation event, Wikipedia's liquidation entry drops it into the broader finance context.
3. The physical meaning of a magnet price
"Magnet price" is jargon for a price level that attracts the spot rate. The mechanism is feedback: when price gets close to a big liquidation cluster, even small price moves trigger some of those liquidations. Those liquidations print as forced market orders. Market orders consume the order book on the trigger side, pushing price further into the cluster, triggering more liquidations.
That is why a dark cluster is rarely a "support" level. From the long side, the cluster is everyone else's stop-out. Once price gets close, the forced selling accelerates the descent through the cluster, not the bounce off it.
The phrase "they're going to hunt the liquidations" is a folk version of this. There is no centralised "they". The mechanic is automatic: the higher the OI sitting at a level, the bigger the gravitational pull of that level on the market.
On 2026-04-09 we took a heatmap-driven counter-trade ourselves. CoinGlass BTC 1d heatmap showed a clear high-density long-liquidation cluster at $66,800 - $67,200 (bright yellow, accumulated >$180M notional long liq prices over 3 days). BTC was trading at $68,500. Our read: "if any pullback comes, this cluster gets tagged."
Same day 21:42 UTC+8 we opened a 0.05 BTC perp short at $68,420, 5x leverage, notional $3,421, principal 684 USDT, stop attached at $69,800 (-2%), target near $67,000 at the lower edge of the cluster. Next morning 04:18 UTC+8 BTC printed $66,910 — the cluster fired, price bounced to $67,400 within 12 minutes, and our trailing closed us at $67,200. Book PnL +$61, after fees ($3.42 maker + taker) and one favourable funding settlement of $0.41 we netted +$58 USDT (+8.5% on principal).
Do not read this as "heatmap = signal". We ran the same setup on a $63K cluster twice in the same window; one time the magnet was skipped entirely, price walked away, our stop got tagged, -$28. The heatmap gives a probability tilt, not a certainty — across roughly 14 similar setups in the last six months, our hit rate sits around 55-60%.
4. Hands-on: walking through this week's BTC map
Practical workflow: open CoinGlass, set BTC, set the 24h or 7d window. Look for the two or three darkest horizontal bands on the chart. Note the price levels.
From here, ask three questions. (a) Where is BTC trading right now relative to those bands? If price is sandwiched between two heavy clusters, expect a range. If price is above all the clusters with a heavy cluster below, the market has a downside attractor. (b) How fresh are the clusters? A cluster that has been building over weeks is more reliable than a cluster that built up in the last 24 hours. (c) How does the cluster shape your stop placement?
Repeat for ETH. The two assets often share clusters at similar percentage offsets from spot, but not always — when they diverge, the divergence itself tells you something about positioning.
5. Replaying the 2024-08-05 BTC flash crash
In the week before 2024-08-05, BTC was trading around $61,000. CoinGlass's heatmap showed a heavy long-liquidation cluster between $49,000 and $52,000 — roughly $500M of estimated long-side OI sitting at implied liq prices in that band.
Once the carry-trade unwind kicked off on 2024-08-04 evening Asia time, BTC started shedding levels. Each leg lower triggered chunks of that $49-52k cluster. The forced selling kept the descent rolling. The low print on 2024-08-05 was $48,830 — basically the bottom edge of the cluster — before the market bounced.
The heatmap did not predict the news. It did predict that, given a triggering event, BTC would walk down to $49,000 and bounce. That is the conditional value of the chart: it tells you where the floor is, given that the move starts.
Cross-check your map on OKX.
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6. Long-term vs short-term clusters — the time axis
Clusters have lifespans. A long-term cluster built up over 30 days is durable — even if the market chops past it briefly, the OI re-anchors there. A short-term cluster built up in 24 hours is fragile — it can dissipate as quickly as it appeared, especially if traders react to seeing it.
Practical use: trade off the long-term clusters for swing positioning. Use the short-term clusters for intraday flow context, but do not anchor your view on them.
The 2024-08-05 $49k cluster was a 7-day build, which is in the middle. The cluster predated the crash trigger, but it was not so old that the market had already adjusted around it.
7. Using clusters to place better stops
The single most actionable rule out of all of this: do not park your stop inside a heavy cluster. Two reasons.
First, the cluster triggers in lockstep. Your stop fires at the same time as everyone else's, and the order book is empty on the trigger side because everyone is selling at once. Slippage is unpredictably bad — easily 0.5-1% beyond your stop level.
Second, the cluster magnet effect means the market is more likely to touch the price than the heatmap-free intuition suggests. You will get stopped out and watch the market reverse.
Better rule: place your stop a few percent past the cluster, on the assumption that if price walks through the cluster, you have legitimate trend confirmation. The cluster becomes your reference, not your trigger.
8. Three common misreadings — don't do this
One: treating clusters as walls. They are not walls, they are speed bumps. A cluster can be smashed through if the macro flow is strong enough. The 2024-08-05 case happens to be where the cluster did hold, but on a strong trend day they get vaporised.
Two: confusing implied with realised. The heatmap shows implied liq prices. The actual liquidations happen at market and can print anywhere within a wide band around the implied price, especially in fast markets.
Three: trading the heatmap as a primary signal. The heatmap is a context layer, not a trigger. Trade your setup, use the heatmap to size and to place stops. If you let the heatmap drive entries, you will be trading other people's stress.
Pair this with the leverage and liq math article so you can map your own positions onto the heatmap. And the 2024-08-05 replay ties the heatmap into the full event timeline.