Damian Lazarus — GET LOST, Mixed by Damian Lazarus & Matthew Styles : The Crosstown Mix Show 127
Indie House · 2h 29m · analysed 21 Aug 2026 · source: soundcloud.com
Public mix analysis — no affiliation or endorsement. This report measures a publicly available recording hosted on soundcloud.com. The scores are produced by SOONOS and do not imply any partnership with, or approval by, Damian Lazarus.
In short
GET LOST, Mixed by Damian Lazarus & Matthew Styles : The Crosstown Mix Show 127 by Damian Lazarus scores 85/100 in the SOONOS analysis (festival ready). The strongest dimension is IDENTITY (94/100) and the weakest is SURPRISE (84/100).
This segment demonstrates that true energy comes from the tension between what is heard and what is withheld.
Key takeaways
What worked
- Invisible technical execution
- Exceptional track selection
- Masterful narrative pacing
What weakened the set
- Long static loops (6×) — Sections sitting on the same loop without layering, EQ moves or tension shifts (7:30, 13:00, 19:00, 29:00, 34:00, 42:00). Long loops kill dancefloor momentum.
What to try next
- Continue to leverage long, evolving blends to maintain the hypnotic state.
- Experiment with subtle vocal textures to add a human element to the deep atmosphere.
- Maintain the current level of restraint; it is your greatest strength.
- Continue to lean into long, patient blends as they define your signature sound.
Timestamped insights
Each moment below is tagged with how it was produced: “measured” comes from the DSP pass on the audio, “listening” comes from the multi-agent listening pass.
A seamless transition where the incoming track's percussion perfectly complements the outgoing track's atmosphere.
A textbook example of a long-form blend where the tracks become one.
Smooth transition focusing on rhythmic continuity.
Perfectly executed transition where the new kick takes over without any phase issues.
Smooth transition focusing on mid-range percussion elements.
About this indie house set
GET LOST, Mixed by Damian Lazarus & Matthew Styles : The Crosstown Mix Show 127 is a indie house DJ set by Damian Lazarus, running 2h 29m. It was measured by the SOONOS multi-agent engine and scores 85/100 overall — festival ready.
The engine files this performance as “Promising”.
This segment demonstrates that true energy comes from the tension between what is heard and what is withheld.
How the score breaks down
SOONOS scores this set across 5 weighted categories. The strongest is IDENTITY at 94/100; the weakest is SURPRISE at 84/100.
Analysis coverage for this file is 100% — the share of the set the engine could measure with full confidence.
Energy and structure
The energy curve was sampled at 56 points, moving between 20 and 86 on the SOONOS energy scale — a wide dynamic range across the set.
5 transitions were detected and scored individually.
Beat-grid measurement (DSP) reports 764.9 grid breaks per hour, with a median beat offset of 14 ms.
How this score is built
Measured layer (DSP): the audio file is analysed directly — beat grid, tempo stability, loudness and energy. These values are measurements, not opinions.
Listening layer: a multi-agent pass reads musical intent — programming, storytelling, coherence and crowd effect. This layer interprets, it does not measure.
Fusion and ceilings: the two layers are merged, and the measured layer always wins on execution. When the DSP hears an execution problem, it caps the final score even if the listening layer is positive.
Measured coverage for this file is 100% of the set.
Full SOONOS analysis
This segment demonstrates that true energy comes from the tension between what is heard and what is withheld.
The 8 dimensions
Not available — the 8-dimension profile was not measured for this set.
Score breakdown
TECHNIQUE
How well did you execute?
25%88
TECHNIQUE
How well did you execute?
STORYTELLING
Did the mix go somewhere?
25%89
STORYTELLING
Did the mix go somewhere?
ENERGY
Did you control the room?
20%86
ENERGY
Did you control the room?
SURPRISE
Did you remain unpredictable?
15%84
SURPRISE
Did you remain unpredictable?
IDENTITY
Did the mix sound like you?
15%94
IDENTITY
Did the mix sound like you?
Energy arc
Transitions analysed (5)
Long EQ-balanced blend
A seamless transition where the incoming track's percussion perfectly complements the outgoing track's atmosphere.
Extended EQ blend
A textbook example of a long-form blend where the tracks become one.
Percussive layering
Smooth transition focusing on rhythmic continuity.
Long EQ blend with low-end swap
Perfectly executed transition where the new kick takes over without any phase issues.
Textural layering
Smooth transition focusing on mid-range percussion elements.
Technical subscores
89
EQ balance
95
Beat alignment
87
Energy control
94
Tempo stability
88
Loudness control
92
Musical coherence
92
Harmonic compatibility
91
Transition cleanliness
Measured (DSP)
14 ms
Beat-grid drift (median)
Typical gap between the two tracks' beats while they play together. Lower is tighter.
216 ms
Drift p95
Worst-case drift: 95% of the set stays tighter than this value.
8,934
Boundaries detected
Points where the audio changes track or section.
48
Hard cuts / h
Abrupt track changes per hour, with no blend between the two records.
93
Clipping events
Moments where the recording hits the ceiling and distorts.
1063
Level jumps
Sudden volume steps between tracks.
Measurement confidence 100% · analysed on the full audio.
Recurring patterns
Long static loops (6×)
Sections sitting on the same loop without layering, EQ moves or tension shifts (7:30, 13:00, 19:00, 29:00, 34:00, 42:00). Long loops kill dancefloor momentum.
What SOONOS heard
- Invisible technical execution
- Exceptional track selection
- Masterful narrative pacing
Timeline
- 02:15Atmospheric Reset
- 08:45Groove Lock
- 15:30Groove Lock
- 20:15Atmospheric Peak
- 25:30Groove Lock
- 29:15Textural Shift
Coaching notes
- Continue to leverage long, evolving blends to maintain the hypnotic state.
- Experiment with subtle vocal textures to add a human element to the deep atmosphere.
- Maintain the current level of restraint; it is your greatest strength.
- Continue to lean into long, patient blends as they define your signature sound.
- Consider introducing a very sparse vocal element to add a human touch to the deep textures.
- Maintain the current level of EQ precision; it is what allows the long overlaps to work so well.
- Continue exploring the use of spoken word as a rhythmic element.
- Maintain the long, patient EQ blends that characterize this style.
- Consider a brief melodic 'breather' after high-intensity percussive sections.
- Introduce a slightly more distinct melodic element to provide a narrative anchor.
- Experiment with a more dramatic energy reset to enhance the impact of the final peak.
- Continue to refine the use of vocal textures as they add a unique signature to the mix.
- Study the use of atmospheric layering in the final 10 minutes.
- Observe how the vocal motif is used to provide narrative closure.
- Practice the 'invisible blend' technique used at 141:22.
Curious how your own set scores?
Methodology and limitations
This report is produced automatically from the published recording. It measures what is present in the audio file: a bad source encoding, a partial upload or a heavily processed broadcast version can change the measured values. Nothing here reflects the room, the crowd or the night itself.
Read the full SOONOS methodology →Questions about this analysis
- What score does Damian Lazarus's GET LOST, Mixed by Damian Lazarus & Matthew Styles : The Crosstown Mix Show 127 get?
- GET LOST, Mixed by Damian Lazarus & Matthew Styles : The Crosstown Mix Show 127 scores 85/100 in the SOONOS Mix Database (festival ready), based on audio measurement plus multi-agent listening.
- How long is GET LOST, Mixed by Damian Lazarus & Matthew Styles : The Crosstown Mix Show 127?
- The analysed recording runs 2h 29m.
- Which part of the mix scores best?
- IDENTITY is the strongest category at 94/100, while SURPRISE is the lowest at 84/100.
- How is this score calculated?
- SOONOS measures the audio with a DSP pass (beat grid, loudness, tempo, energy) and runs a multi-agent listening pass on top. Measured axes always override the listening layer, so an execution issue heard in the file caps the final score.
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Test how a set like this one would land in a club, a beach club or a festival.
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