Nina Kraviz — nina kraviz @ amnesia 05.07.2026

    Experimental Techno · 1h 56m · Amnesia Ibiza · analysed 18 Aug 2026 · source: soundcloud.com

    Overall score
    87/100
    Level
    festival ready
    Duration
    1h 56m
    Genre
    Experimental 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, Nina Kraviz.

    In short

    nina kraviz @ amnesia 05.07.2026 by Nina Kraviz scores 87/100 in the SOONOS analysis (festival ready). The strongest dimension is IDENTITY (94/100) and the weakest is SURPRISE (84/100).

    This DJ understands that techno is a marathon, not a sprint, using subtle evolution to maintain interest over long periods.

    Key takeaways

    What worked

    • Groove continuity
    • Technical precision
    • Narrative focus
    • Exceptional groove continuity.

    What weakened the set

    • Long static loops (6×) — Sections sitting on the same loop without layering, EQ moves or tension shifts (0:00, 6:00, 10:00, 12:00, 20:00, 28:00). Long loops kill dancefloor momentum.

    What to try next

    • Maintain the current level of percussive density but experiment with more frequent filter work.
    • Consider a brief, atmospheric breakdown to reset the crowd's ears before the next major peak.
    • Ensure the sub-bass frequencies are carefully managed during the most complex layering sections.
    • Incorporate brief melodic breakdowns to provide contrast to the relentless percussion.

    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.

    • 4:12Measured (DSP)88/100Listen at 4:12

      Seamless transition, the new kick drum integrates perfectly without any phase issues.

    • 8:20Measured (DSP)92/100Listen at 8:20

      Excellent use of filtering to bring in the acid line, creating a significant energy boost.

    • 14:12Measured (DSP)88/100Listen at 14:12

      A very smooth transition that maintains the hypnotic drive. The incoming track's percussion is introduced subtly.

    • 19:45Measured (DSP)85/100Listen at 19:45

      Effective use of high-pass filtering to create a brief moment of tension before dropping into the next groove.

    • 25:30Measured (DSP)88/100Listen at 25:30

      Seamless transition that maintains the hypnotic flow perfectly.

    About this experimental techno set

    nina kraviz @ amnesia 05.07.2026 is a experimental techno DJ set by Nina Kraviz, running 1h 56m. It was measured by the SOONOS multi-agent engine and scores 87/100 overall — festival ready.

    The engine files this performance as “Promising”.

    This DJ understands that techno is a marathon, not a sprint, using subtle evolution to maintain interest over long periods.

    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 64 points, moving between 70 and 95 on the SOONOS energy scale — a moderate dynamic range across the set.

    5 transitions were detected and scored individually.

    Beat-grid measurement (DSP) reports 422.6 grid breaks per hour, with a median beat offset of 18 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

    This DJ understands that techno is a marathon, not a sprint, using subtle evolution to maintain interest over long periods.

    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 Alignmentmeasured84
    Transition Qualitymeasured82
    Phrase Accuracymeasured92
    EQ & Frequency Control (estimated)measured85
    Tempo Stability (estimated)measured94
    Technical Cleanlinessmeasured61

    STORYTELLING

    Did the mix go somewhere?

    25%91
    Narrative ArcAI93
    ProgressionAI91
    Tension & ReleaseAI87
    Section AwarenessAI91
    Flow ContinuityAI94
    PayoffAI89

    ENERGY

    Did you control the room?

    20%87
    Energy Curvemeasured83
    PacingAI93
    MomentumAI95
    Peak ManagementAI88
    Energy HandoffAI88
    Fatigue ControlAI64

    SURPRISE

    Did you remain unpredictable?

    15%84
    Unexpected MomentsAI83
    ContrastAI83
    Transition Varietymeasured93
    Selection RiskAI88
    FreshnessAI61
    Surprise ControlAI83

    IDENTITY

    Did the mix sound like you?

    15%94
    Selection QualityAI93
    Identity ConsistencyAI98
    IntentionalityAI95
    ConfidenceAI95
    RestraintAI90
    SignatureAI94

    Energy arc

    0:00115:00

    Transitions analysed (5)

    4:12

    Long EQ blend with low-end swap

    Seamless transition, the new kick drum integrates perfectly without any phase issues.

    88
    8:20

    Harmonic layering with filter sweep

    Excellent use of filtering to bring in the acid line, creating a significant energy boost.

    92
    14:12

    Long EQ blend with low-end swap

    A very smooth transition that maintains the hypnotic drive. The incoming track's percussion is introduced subtly.

    88
    19:45

    Filter sweep and quick swap

    Effective use of high-pass filtering to create a brief moment of tension before dropping into the next groove.

    85
    25:30

    Long EQ blend, swapping lows on the 32nd bar.

    Seamless transition that maintains the hypnotic flow perfectly.

    88

    Technical subscores

    85

    EQ balance

    92

    Beat alignment

    89

    Energy control

    94

    Tempo stability

    88

    Loudness control

    91

    Musical coherence

    84

    Harmonic compatibility

    85

    Transition cleanliness

    Measured (DSP)

    18 ms

    Beat-grid drift (median)

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

    183 ms

    Drift p95

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

    6,935

    Boundaries detected

    Points where the audio changes track or section.

    54

    Hard cuts / h

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

    141

    Clipping events

    Moments where the recording hits the ceiling and distorts.

    359

    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 (0:00, 6:00, 10:00, 12:00, 20:00, 28:00). Long loops kill dancefloor momentum.

    What SOONOS heard

    • Groove continuity
    • Technical precision
    • Narrative focus
    • Exceptional groove continuity.
    • Uncompromising artistic identity.
    • Professional energy management.

    Timeline

    • 5:30Percussive Saturation
    • 10:15Acid Peak
    • 16:30Groove Lock Peak
    • 21:00Vocal Hook Introduction
    • 27:45Vocal Hook Entry

    Coaching notes

    • Maintain the current level of percussive density but experiment with more frequent filter work.
    • Consider a brief, atmospheric breakdown to reset the crowd's ears before the next major peak.
    • Ensure the sub-bass frequencies are carefully managed during the most complex layering sections.
    • Incorporate brief melodic breakdowns to provide contrast to the relentless percussion.
    • Experiment with longer filter sweeps to build more anticipation before drops.
    • Ensure mid-range textures are not occasionally masked by the powerful low-end.
    • Incorporate more dynamic EQ work (e.g., mid-range carving) to create more space for incoming tracks.
    • Experiment with brief rhythmic 'cuts' or silences to break the hypnosis and re-engage the crowd's attention.
    • Introduce a melodic or atmospheric element towards the end of the segment to prepare for a narrative shift.
    • Refine mid-frequency EQ management during dense percussive transitions to maintain absolute clarity.
    • Experiment with very brief atmospheric 'silences' or filtered breakdowns to enhance the impact of the kick re-entry.
    • Consider adding a subtle, recurring melodic or vocal motif to provide a narrative thread through the industrial textures.
    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 Nina Kraviz's nina kraviz @ amnesia 05.07.2026 get?
    nina kraviz @ amnesia 05.07.2026 scores 87/100 in the SOONOS Mix Database (festival ready), based on audio measurement plus multi-agent listening.
    How long is nina kraviz @ amnesia 05.07.2026?
    The analysed recording runs 1h 56m.
    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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