SOONOS

    Marino CanalZAMNA Brasil Mix - Adam Sellouk - Brina Knauss - Innellea - Massano - Marino Canal - Toto Chiavetta

    Melodic Techno · 1h 41m · analysed 24 Aug 2026 · source: soundcloud.com

    Overall score
    78/100
    Level
    club ready
    Duration
    1h 41m
    Genre
    Melodic 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, Marino Canal.

    In short

    ZAMNA Brasil Mix - Adam Sellouk - Brina Knauss - Innellea - Massano - Marino Canal - Toto Chiavetta by Marino Canal scores 78/100 in the SOONOS analysis (club ready). The strongest dimension is STORYTELLING (83/100) and the weakest is SURPRISE (77/100).

    The engine files this performance as “Promising”.

    Key takeaways

    What weakened the set

    • Long static loops (6×) — Sections sitting on the same loop without layering, EQ moves or tension shifts (24:00, 30:00, 34:00, 46:42, 52:15, 56:00). Long loops kill dancefloor momentum.

    What to try next

    • Maintain the current level of technical precision in EQ handovers.
    • Experiment with more diverse textures in the mid-range to create a more unique sonic identity.
    • Use the patient build-up to justify a more aggressive energy shift in the next segment.
    • Experiment with brief, dramatic silences to reset the energy floor.

    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.

    • 5:12Measured (DSP)92/100Listen at 5:12

      A textbook melodic techno transition. The incoming bassline is introduced subtly over 32 bars.

    • 9:58Measured (DSP)85/100Listen at 9:58

      Smooth exit of the first track's main synth lead while the new groove takes over.

    • 11:45Measured (DSP)92/100Listen at 11:45

      Expertly executed transition. The incoming kick replaces the outgoing one perfectly on the phrase.

    • 16:30Measured (DSP)82/100Listen at 16:30

      Smooth integration of melodic elements. The transition feels like a natural progression of the same track.

    • 20:15Measured (DSP)78/100Listen at 20:15

      Effective use of high-pass filtering to create a brief moment of tension before the new track drops.

    • 23:45Measured (DSP)92/100Listen at 23:45

      Flawless handover; the incoming bassline takes over without any volume dip or phase issues.

    • 28:10Measured (DSP)88/100Listen at 28:10

      Uses the breakdown of Track A to introduce the melodic elements of Track B, creating a seamless emotional bridge.

    About this melodic techno set

    ZAMNA Brasil Mix - Adam Sellouk - Brina Knauss - Innellea - Massano - Marino Canal - Toto Chiavetta is a melodic techno DJ set by Marino Canal, running 1h 41m. It was measured by the SOONOS multi-agent engine and scores 78/100 overall — club ready.

    The engine files this performance as “Promising”.

    How the score breaks down

    SOONOS scores this set across 5 weighted categories. The strongest is STORYTELLING at 83/100; the weakest is SURPRISE at 77/100.

    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 61 points, moving between 20 and 90 on the SOONOS energy scale — a wide dynamic range across the set.

    7 transitions were detected and scored individually.

    Beat-grid measurement (DSP) reports 635.1 grid breaks per hour, with a median beat offset of 26 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 8 dimensions

    Not available — the 8-dimension profile was not measured for this set.

    Score breakdown

    TECHNIQUE

    How well did you execute?

    25%81
    Beat Alignmentmeasured71
    Transition Qualitymeasured69
    Phrase Accuracymeasured89
    EQ & Frequency Control (estimated)measured86
    Tempo Stability (estimated)measured95
    Technical Cleanlinessmeasured85

    STORYTELLING

    Did the mix go somewhere?

    25%83
    Narrative ArcAI87
    ProgressionAI82
    Tension & ReleaseAI80
    Section AwarenessAI82
    Flow ContinuityAI88
    PayoffAI79

    ENERGY

    Did you control the room?

    20%82
    Energy Curvemeasured81
    PacingAI81
    MomentumAI87
    Peak ManagementAI80
    Energy HandoffAI82
    Fatigue ControlAI75

    SURPRISE

    Did you remain unpredictable?

    15%77
    Unexpected MomentsAI72
    ContrastAI80
    Transition Varietymeasured90
    Selection RiskAI69
    FreshnessAI72
    Surprise ControlAI72

    IDENTITY

    Did the mix sound like you?

    15%83
    Selection QualityAI81
    Identity ConsistencyAI94
    IntentionalityAI83
    ConfidenceAI83
    RestraintAI75
    SignatureAI75

    Energy arc

    0:00100:50

    Transitions analysed (7)

    5:12

    Long EQ blend with low-end swap on phrase

    A textbook melodic techno transition. The incoming bassline is introduced subtly over 32 bars.

    92
    9:58

    High-pass filter fade out with percussive layering

    Smooth exit of the first track's main synth lead while the new groove takes over.

    85
    11:45

    Long EQ blend with low-end swap

    Expertly executed transition. The incoming kick replaces the outgoing one perfectly on the phrase.

    92
    16:30

    Mid-range layering

    Smooth integration of melodic elements. The transition feels like a natural progression of the same track.

    82
    20:15

    Filter sweep and drop

    Effective use of high-pass filtering to create a brief moment of tension before the new track drops.

    78
    23:45

    Long EQ blend with low-end swap on phrase

    Flawless handover; the incoming bassline takes over without any volume dip or phase issues.

    92
    28:10

    Filter-assisted transition during breakdown

    Uses the breakdown of Track A to introduce the melodic elements of Track B, creating a seamless emotional bridge.

    88

    Technical subscores

    86

    EQ balance

    92

    Beat alignment

    83

    Energy control

    95

    Tempo stability

    84

    Loudness control

    86

    Musical coherence

    90

    Harmonic compatibility

    88

    Transition cleanliness

    Measured (DSP)

    26 ms

    Beat-grid drift (median)

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

    208 ms

    Drift p95

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

    6,032

    Boundaries detected

    Points where the audio changes track or section.

    97

    Hard cuts / h

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

    221

    Clipping events

    Moments where the recording hits the ceiling and distorts.

    273

    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 (24:00, 30:00, 34:00, 46:42, 52:15, 56:00). Long loops kill dancefloor momentum.

    Timeline

    • 0:00Atmospheric Hook
    • 5:12The Groove Lock
    • 13:45Atmospheric Peak
    • 18:20Energy Plateau
    • 25:30Groove Lock
    • 29:45Peak Tension

    Coaching notes

    • Maintain the current level of technical precision in EQ handovers.
    • Experiment with more diverse textures in the mid-range to create a more unique sonic identity.
    • Use the patient build-up to justify a more aggressive energy shift in the next segment.
    • Experiment with brief, dramatic silences to reset the energy floor.
    • Layer in organic percussion (e.g., shakers, woodblocks) to add warmth.
    • Utilize vocal fragments to create more distinct 'moments' within the hypnotic flow.
    • Incorporate more varied percussion elements to distinguish narrative chapters.
    • Utilize dramatic filter sweeps to heighten tension during buildups.
    • Layer additional ambient textures to deepen the emotional resonance of melodic peaks.
    • Experiment with subtle rhythmic variations during long melodic passages.
    • Use vocal stems more strategically to anchor emotional peaks.
    • Explore slightly more aggressive EQ cuts for added dynamic impact.
    Listen on SoundCloud

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    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 Marino Canal's ZAMNA Brasil Mix - Adam Sellouk - Brina Knauss - Innellea - Massano - Marino Canal - Toto Chiavetta get?
    ZAMNA Brasil Mix - Adam Sellouk - Brina Knauss - Innellea - Massano - Marino Canal - Toto Chiavetta scores 78/100 in the SOONOS Mix Database (club ready), based on audio measurement plus multi-agent listening.
    How long is ZAMNA Brasil Mix - Adam Sellouk - Brina Knauss - Innellea - Massano - Marino Canal - Toto Chiavetta?
    The analysed recording runs 1h 41m.
    Which part of the mix scores best?
    STORYTELLING is the strongest category at 83/100, while SURPRISE is the lowest at 77/100.
    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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