Enrico Sangiuliano — Enrico Sangiuliano closing Kappa FuturFestival 2023

    Peak Techno · 1h 28m · analysed 20 Aug 2026 · source: soundcloud.com

    Overall score
    87/100
    Level
    festival ready
    Duration
    1h 28m
    Genre
    Peak Techno

    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 closing Kappa FuturFestival 2023 by Enrico Sangiuliano scores 87/100 in the SOONOS analysis (festival ready). The strongest dimension is IDENTITY (94/100) and the weakest is TECHNIQUE (84/100).

    The DJ uses silence and atmospheric space as effectively as the kick drum to command the audience.

    Key takeaways

    What weakened the set

    • Long static loops (6×) — Sections sitting on the same loop without layering, EQ moves or tension shifts (33:00, 37:00, 41:00, 55:00, 64:00, 81:00). Long loops kill dancefloor momentum.

    What to try next

    • Continue to leverage long-form tension to command large audiences.
    • Experiment with more complex melodic layering in the mid-sections.
    • Monitor high-frequency levels to ensure clarity at high volumes.
    • Continue to explore subtle melodic variations to add depth.

    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.

    • 6:20Measured (DSP)92/100Listen at 6:20

      Seamless transition from atmospheric intro to driving techno groove.

    • 9:45Measured (DSP)88/100Listen at 9:45

      Clean handover of the bass energy, maintaining the driving momentum.

    • 14:20Measured (DSP)82/100Listen at 14:20

      Intentional reset

    • 28:00Measured (DSP)82/100Listen at 28:00

      Intentional reset

    About this peak techno set

    Enrico Sangiuliano closing Kappa FuturFestival 2023 is a peak techno DJ set by Enrico Sangiuliano, running 1h 28m. It was measured by the SOONOS multi-agent engine and scores 87/100 overall — festival ready.

    The engine files this performance as “Promising”.

    The DJ uses silence and atmospheric space as effectively as the kick drum to command the audience.

    How the score breaks down

    SOONOS scores this set across 5 weighted categories. The strongest is IDENTITY at 94/100; the weakest is TECHNIQUE 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 23 points, moving between 40 and 98 on the SOONOS energy scale — a wide dynamic range across the set.

    7 transitions were detected and scored individually.

    Beat-grid measurement (DSP) reports 457.0 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.

    Listen to the original set

    Full SOONOS analysis

    0

    The DJ uses silence and atmospheric space as effectively as the kick drum to command the audience.

    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
    Beat Alignmentmeasured89
    Transition Qualitymeasured61
    Phrase Accuracymeasured94
    EQ & Frequency Control (estimated)measured89
    Tempo Stability (estimated)measured96
    Technical Cleanlinessmeasured73

    STORYTELLING

    Did the mix go somewhere?

    25%93
    Narrative ArcAI94
    ProgressionAI92
    Tension & ReleaseAI91
    Section AwarenessAI93
    Flow ContinuityAI93
    PayoffAI94

    ENERGY

    Did you control the room?

    20%89
    Energy Curvemeasured87
    PacingAI92
    MomentumAI95
    Peak ManagementAI92
    Energy HandoffAI92
    Fatigue ControlAI69

    SURPRISE

    Did you remain unpredictable?

    15%86
    Unexpected MomentsAI85
    ContrastAI85
    Transition Varietymeasured94
    Selection RiskAI89
    FreshnessAI67
    Surprise ControlAI85

    IDENTITY

    Did the mix sound like you?

    15%94
    Selection QualityAI93
    Identity ConsistencyAI98
    IntentionalityAI95
    ConfidenceAI96
    RestraintAI87
    SignatureAI93

    Energy arc

    0:0087:00

    Transitions analysed (7)

    6:20

    Long EQ blend with percussive layering

    Seamless transition from atmospheric intro to driving techno groove.

    92
    9:45

    Low-end swap on phrase boundary

    Clean handover of the bass energy, maintaining the driving momentum.

    88
    11:45

    Perfect Blend

    100
    14:20

    Minor EQ Overlap

    intentional_reset

    82
    18:45

    Peak Impact Swap

    100
    24:15

    Perfect Blend

    100
    28:00

    Minor EQ Overlap

    intentional_reset

    82

    Technical subscores

    89

    EQ balance

    94

    Beat alignment

    92

    Energy control

    96

    Tempo stability

    90

    Loudness control

    91

    Musical coherence

    88

    Harmonic compatibility

    88

    Transition cleanliness

    Measured (DSP)

    14 ms

    Beat-grid drift (median)

    Typical gap between the two tracks' beats while they play together. Lower is tighter.

    173 ms

    Drift p95

    Worst-case drift: 95% of the set stays tighter than this value.

    5,263

    Boundaries detected

    Points where the audio changes track or section.

    145

    Hard cuts / h

    Abrupt track changes per hour, with no blend between the two records.

    44

    Clipping events

    Moments where the recording hits the ceiling and distorts.

    246

    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 (33:00, 37:00, 41:00, 55:00, 64:00, 81:00). Long loops kill dancefloor momentum.

    Timeline

    • 0:00Cinematic Intro
    • 5:12First Kick Drop
    • 10:30Groove Lock

    Coaching notes

    • Continue to leverage long-form tension to command large audiences.
    • Experiment with more complex melodic layering in the mid-sections.
    • Monitor high-frequency levels to ensure clarity at high volumes.
    • Continue to explore subtle melodic variations to add depth.
    • Maintain the high level of technical precision shown here.
    • Experiment with even longer build-ups to further heighten tension.
    Listen on SoundCloud

    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 closing Kappa FuturFestival 2023 get?
    Enrico Sangiuliano closing Kappa FuturFestival 2023 scores 87/100 in the SOONOS Mix Database (festival ready), based on audio measurement plus multi-agent listening.
    How long is Enrico Sangiuliano closing Kappa FuturFestival 2023?
    The analysed recording runs 1h 28m.
    Which part of the mix scores best?
    IDENTITY is the strongest category at 94/100, while TECHNIQUE 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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