Enrico Sangiuliano — Enrico Sangiuliano @ TECH, Parma - March 14th, 2015
Peak Techno · 1h 28m · analysed 20 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, Enrico Sangiuliano.
In short
Enrico Sangiuliano @ TECH, Parma - March 14th, 2015 by Enrico Sangiuliano scores 83/100 in the SOONOS analysis (club ready). The strongest dimension is IDENTITY (89/100) and the weakest is SURPRISE (80/100).
Mastery in techno is often found in the subtle evolution of a single groove rather than the introduction of new themes.
Key takeaways
What weakened the set
- Long static loops (6×) — Sections sitting on the same loop without layering, EQ moves or tension shifts (19:00, 22:00, 26:00, 33:00, 37:00, 52:00). Long loops kill dancefloor momentum.
What to try next
- Experiment with more dramatic EQ carving during the longest blends to create even more space.
- Use brief moments of silence or extreme filtering to create 'reset' points.
- Incorporate a track with a strong melodic hook to provide a contrast to the percussive drive.
- Use more dramatic EQ sweeps during long blends to add movement.
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.
Textbook techno transition. The incoming kick replaces the outgoing one so smoothly it feels like a single evolving track.
Smooth integration of new rhythmic elements. The DJ uses the high-end to bridge the tracks before committing to the bass.
A textbook techno transition, perfectly phased and transparent.
Smoothly introduces new elements while maintaining the core groove.
Perfectly executed handover of the kick drum; the groove remains completely undisturbed.
About this peak techno set
Enrico Sangiuliano @ TECH, Parma - March 14th, 2015 is a peak techno DJ set by Enrico Sangiuliano, running 1h 28m. It was measured by the SOONOS multi-agent engine and scores 83/100 overall — club ready.
The engine files this performance as “Promising”.
Mastery in techno is often found in the subtle evolution of a single groove rather than the introduction of new themes.
How the score breaks down
SOONOS scores this set across 5 weighted categories. The strongest is IDENTITY at 89/100; the weakest is SURPRISE at 80/100.
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 55 points, moving between 10 and 92 on the SOONOS energy scale — a wide dynamic range across the set.
5 transitions were detected and scored individually.
Beat-grid measurement (DSP) reports 345.1 grid breaks per hour, with a median beat offset of 20 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
Mastery in techno is often found in the subtle evolution of a single groove rather than the introduction of new themes.
The 8 dimensions
Not available — the 8-dimension profile was not measured for this set.
Score breakdown
TECHNIQUE
How well did you execute?
25%84
TECHNIQUE
How well did you execute?
STORYTELLING
Did the mix go somewhere?
25%87
STORYTELLING
Did the mix go somewhere?
ENERGY
Did you control the room?
20%84
ENERGY
Did you control the room?
SURPRISE
Did you remain unpredictable?
15%80
SURPRISE
Did you remain unpredictable?
IDENTITY
Did the mix sound like you?
15%89
IDENTITY
Did the mix sound like you?
Energy arc
Transitions analysed (5)
Long EQ blend with low-end swap on phrase
Textbook techno transition. The incoming kick replaces the outgoing one so smoothly it feels like a single evolving track.
High-pass filter transition with percussive layering
Smooth integration of new rhythmic elements. The DJ uses the high-end to bridge the tracks before committing to the bass.
Long EQ blend with low-end swap
A textbook techno transition, perfectly phased and transparent.
Progressive layering and mid-frequency swap
Smoothly introduces new elements while maintaining the core groove.
Long EQ blend with low-end swap
Perfectly executed handover of the kick drum; the groove remains completely undisturbed.
Technical subscores
88
EQ balance
93
Beat alignment
88
Energy control
94
Tempo stability
87
Loudness control
90
Musical coherence
86
Harmonic compatibility
90
Transition cleanliness
Measured (DSP)
20 ms
Beat-grid drift (median)
Typical gap between the two tracks' beats while they play together. Lower is tighter.
123 ms
Drift p95
Worst-case drift: 95% of the set stays tighter than this value.
5,280
Boundaries detected
Points where the audio changes track or section.
114
Hard cuts / h
Abrupt track changes per hour, with no blend between the two records.
119
Clipping events
Moments where the recording hits the ceiling and distorts.
271
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 (19:00, 22:00, 26:00, 33:00, 37:00, 52:00). Long loops kill dancefloor momentum.
Timeline
- 00:00Atmospheric Hook
- 05:15Groove Lock
- 09:45Energy Plateau
- 14:50Groove Lock Achievement
- 19:20Tension Peak
- 26:30Groove Lock Peak
Coaching notes
- Experiment with more dramatic EQ carving during the longest blends to create even more space.
- Use brief moments of silence or extreme filtering to create 'reset' points.
- Incorporate a track with a strong melodic hook to provide a contrast to the percussive drive.
- Use more dramatic EQ sweeps during long blends to add movement.
- Incorporate tracks with more atmospheric depth to enhance the 'story'.
- Experiment with shorter, more aggressive cuts to vary the transition style.
- Experiment with more dramatic EQ cuts to create tension.
- Incorporate a few more melodic elements to broaden the emotional range.
- Use subtle reverb washes on the percussion to add depth to the industrial textures.
- Experiment with longer, more atmospheric breakdowns to enhance the impact of the drops.
- Use subtle delay and reverb automation on percussion to add spatial depth.
- Incorporate a few 'surprise' elements (e.g., a sudden vocal or synth stab) to break the hypnotic loop occasionally.
- Continue exploring cinematic and ambient textures for set closings.
- Maintain the high level of EQ precision shown in the final transition.
- Consider recording a dedicated 'ambient/closing' mix to further showcase this side of your artistry.
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 Enrico Sangiuliano's Enrico Sangiuliano @ TECH, Parma - March 14th, 2015 get?
- Enrico Sangiuliano @ TECH, Parma - March 14th, 2015 scores 83/100 in the SOONOS Mix Database (club ready), based on audio measurement plus multi-agent listening.
- How long is Enrico Sangiuliano @ TECH, Parma - March 14th, 2015?
- The analysed recording runs 1h 28m.
- Which part of the mix scores best?
- IDENTITY is the strongest category at 89/100, while SURPRISE is the lowest at 80/100.
- 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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- Enrico Sangiuliano at Awakenings Festival Easter 202288
- Enrico Sangiuliano live at Tomorrowland 2022, Atmosphere Stage87
- Enrico Sangiuliano closing Kappa FuturFestival 202387
- Enrico Sangiuliano - ES System 2.0 Livestream - July 16th 202087
- Enrico Sangiuliano at Egg London - February 17th, 201786
- Enrico Sangiuliano - Closing Set @ BACK>>To Clubbing - Milan 2011-10-0776
- Enrico Sangiuliano at Awakenings ADE 201973
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Test how a set like this one would land in a club, a beach club or a festival.
Get the same breakdown on your own set: transitions, energy arc and measured execution.
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