ICT QML — The Quasimodo Reversal Pattern Explained
The Quasimodo (QML) is a reversal chart pattern used in ICT methodology to identify high-probability turning points. It combines liquidity sweeps with structural failure for clean counter-trend entries.
The Quasimodo pattern — abbreviated QML in ICT circles — is a reversal chart pattern that identifies the moment when a trend has overextended, swept the final liquidity pool, and is about to reverse. Named after the fictional hunchback character whose asymmetrical shape mirrors the pattern's structure, the QML is one of the cleaner reversal setups because it combines a visible structural failure with a precise entry zone.
What Does the QML Pattern Look Like?
A bearish QML forms during an uptrend and consists of four swing points. The sequence: a Higher High (HH), followed by a Higher Low (HL), followed by a new Higher High that is higher than the first HH — and then the critical component: a Lower Low that breaks below the HL between the two Higher Highs. This lower low is the structural failure that signals the trend has exhausted. The pattern looks like a person with one shoulder higher than the other — the Quasimodo shape.
A bullish QML is the mirror during a downtrend: Lower Low, Higher Low (partial reversal), new Lower Low below the first LL, then a Higher High that breaks above the lower high between the two Lower Lows. This structural failure confirms the downtrend has exhausted its final push.
The ICT Logic Behind the QML
The QML works because the second extreme — the higher HH or the lower LL — is a liquidity sweep. The algorithm uses this final push beyond the prior extreme to collect all the stop orders and pending entries sitting at that level. Retail breakout traders who bought the new HH are now trapped long when the Lower Low forms and breaks the HL. The sweep cleared the buy-side liquidity; the subsequent HL breakdown confirms the delivery has reversed.
The entry zone in the QML is the last Higher Low (for bearish QML) or the last Lower High (for bullish QML) — the intermediate swing between the two extremes. When price returns to that level after the structural failure, it is entering the zone where early smart money positioned before the final sweep. This zone acts as resistance (bearish QML) or support (bullish QML) on the retest.
Trading the QML — Entry Model
- diamondIdentify the four-swing sequence on your chart: HH → HL → higher HH → LL that breaks the HL (for bearish QML).
- diamondOnce the LL forms and closes below the HL, the QML pattern is confirmed.
- diamondMark the HL level — this is your entry zone on the retest.
- diamondWait for price to retrace back up to the HL zone. On the 5-minute chart, watch for a bearish reaction — a displacement away from the zone or a bearish FVG forming within it.
- diamondEnter short at the HL level (or the CE of any FVG that forms within it). Stop: above the second Higher High (the sweep candle high). Target: the lowest swing low below, or the next SSL level.
- diamondFor bullish QML: enter long at the last Lower High zone on the retest. Stop: below the second Lower Low. Target: the highest swing high above or nearest BSL.
QML vs Head and Shoulders — The Key Difference
Retail traders will recognize the QML as similar to a Head and Shoulders pattern. The difference is the ICT interpretation of what is actually happening. In traditional technical analysis, Head and Shoulders is just a pattern to be followed. In ICT, the QML reveals the liquidity mechanism: the second shoulder (the higher HH) is an engineered sweep of the prior high, specifically designed to trap breakout buyers before the reversal. The HL breakdown is the confirmation that the sweep was manipulation, not genuine continuation.
QML setups are most reliable on the 1-hour and 4-hour charts during Killzone periods. A bearish QML on the 4-hour chart that forms during the New York session open, with the entry zone aligning with a 4-hour Order Block, is an extremely high-probability reversal setup. The structural clarity of the QML makes it one of the easier ICT patterns to identify in hindsight — the challenge is identifying it in real-time as the fourth swing is forming.