Predictive Liquidation Map API: Where Leverage Lives, Before It Gets Hit

Most traders watch liquidation feeds the wrong way. They wait for a candle to move, scroll Coinglass, see the red bar, and think "ok, now I know." That is reactive intelligence. By the time a liquidation prints, the move that caused it is already 80 percent of the way through. The edge is not in seeing what just liquidated. The edge is in knowing where the next 200 million dollars of leveraged longs are sitting, exactly how far below current price, and what happens to the cascade if BTC drops 5, 10, or 15 percent.

We just shipped that, as a public API.

What the Liquidation Map API gives you

One GET request to /api/v1/liquidation-map with a symbol parameter returns a structured JSON with two things that matter.

First, the cluster array. For every meaningful concentration of liquidation prices on the Hyperliquid order book, you get the side (long or short positions about to be hit), the estimated USD size of liquidations that would trigger if price reaches that zone, the exact price level, and the percentage distance from the current mark price. Sorted by size, ready to filter.

Second, the cascade scenarios array. You ask "what happens if BTC moves 5 percent down, 10 percent down, 15 percent down" and you get back the dollar amount of long liquidations that would be triggered at each step, plus the equivalent for upward moves hitting shorts. Symmetric, oriented, with totals computed server-side.

Default scenarios are 5, 10, and 15 percent. You can pass a CSV of any integers from 1 to 50 in the scenarios query parameter and get back what you need. Want a granular sweep at 2, 4, 6, 8, 10? Pass scenarios=2,4,6,8,10. Want the extreme tails? scenarios=20,30,50. Six entries per scenario set (down and up for each percentage), every entry includes the side triggered, the price target, and the liquidation USD.

Why this is different from Coinglass and Hyblock

Coinglass shows you a heatmap. It is a beautiful image. You cannot easily parse it programmatically, you cannot feed it into a bot decision tree, and the API access tier costs hundreds of dollars per month with rate limits that make automated polling expensive. Hyblock has solid analytics but is institutional-grade pricing and locks key features behind enterprise contracts.

The Buildix API is built for developers and bot builders. Plain JSON, cleanly typed, $79 per month on the Whale tier with 50,000 requests per day included. No images to scrape, no chart screenshots to OCR, no hand-tuning of pixel-to-price conversions. You write four lines of Python and you have liquidation cluster data in your strategy.

`python import requests

r = requests.get( "https://www.buildix.trade/api/v1/liquidation-map", headers={"x-api-key": "YOUR_KEY"}, params={"symbol": "BTC", "scenarios": "5,10,15"}, ) data = r.json() `

That is it. From there you have current_price, the clusters, and the cascade scenarios in a Python dict.

Three concrete uses for an automated trader

First use is signal coherence. When your bot generates a buy signal on BTC, before placing the order, you ask the liquidation map what the asymmetry looks like. If there are 500 million dollars of short liquidations sitting 5 percent above current price and only 50 million of long liquidations 5 percent below, the buy signal has a magnet pulling price upward. If the asymmetry is the other way, the buy signal is fighting gravity. Most retail bots ignore this. They fire trades into the void without checking what the order book gravity field looks like. Adding the liquidation asymmetry as a final filter before order placement is the kind of small change that meaningfully shifts winrate without requiring a full strategy rewrite.

Second use is take-profit calibration. Stop placing TP at fixed multiples of ATR. The market does not care about your ATR. The market cares about clusters of stops that get harvested when price reaches them. Read the largest cluster on the side of your trade and set TP one tick below that level. You catch the move into the magnet, you exit before the bounce.

Third use is regime awareness. The cascade scenarios array tells you whether the leverage in the market is symmetrically distributed (max-to-min liquidation ratio under 2x), asymmetrically tilted (between 2x and 4x), or fragile (above 4x). In fragile regimes, moves are faster and more unidirectional. Tighten stops, widen TPs, expect the unexpected. In symmetric regimes, mean reversion strategies win. The cascade scenarios give you a regime classifier with one API call.

Why Hyperliquid first

Hyperliquid is the venue where this matters most. The HYPE perpetual exchange is now responsible for 70 percent of decentralized perp volume, with a fully on-chain order book that lets us reconstruct the true liquidation surface from public data. No exchange rate-limiting, no IP-bans on aggregators, no opaque private API. We can see every leveraged position because the chain itself shows them.

For BTC and ETH specifically, Hyperliquid open interest is large enough to be representative of broader market leverage. For altcoins where Hyperliquid has dominant share (HYPE itself, mid-cap perps with native HL volume), the map is the most accurate view available anywhere. For pairs where Hyperliquid is one of several venues, the data is directional but should be combined with funding and basis data from your other sources, which Buildix already provides on the deep view.

How to start

Three steps. Sign up at buildix.trade if you have not already, the free screener is enough to test the platform. Upgrade to Whale tier from the dashboard, $79 per month, crypto or card. Generate an API key from your dashboard at buildix.trade/dashboard/api-keys. Then make your first request, see the JSON, and start integrating.

Full API reference at buildix.trade/docs. Endpoints documented with curl examples, response schemas, and rate limits. If you build something interesting with the data, send it to us, we feature creative integrations on the homepage and in the newsletter.

This is the first endpoint of what will become a suite of programmatic primitives for orderflow-aware automation. Liquidation map today, then VPIN feeds, whale flow streams, and the V5 signal score itself, all accessible via the same authenticated REST surface. The goal is simple: make the same institutional-grade orderflow analytics that we run internally available as building blocks for any bot, any dashboard, any strategy. You bring the logic, we bring the signal.