Laurent GarnierIIWII - Season 7 - Show 10 (Juin 2017)

    Classics · 2h 02m · analysed 18 Aug 2026

    Overall score
    74/100
    Level
    solid
    Duration
    2h 02m
    Genre
    Classics

    About this classics set

    IIWII - Season 7 - Show 10 (Juin 2017) is a classics DJ set by Laurent Garnier, running 2h 02m. It was measured by the SOONOS multi-agent engine and scores 74/100 overall — solid.

    The engine files this performance as “Promising”.

    This DJ treats the mix as a cinematic experience, using every element to serve the story.

    How the score breaks down

    SOONOS scores this set across 5 weighted categories. The strongest is IDENTITY at 82/100; the weakest is SURPRISE at 76/100.

    The final score is capped by measured -: the DSP layer overrides the listening layer whenever it measures an execution issue directly in the audio.

    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 85 on the SOONOS energy scale — a wide dynamic range across the set.

    7 transitions were detected and scored individually.

    Beat-grid measurement (DSP) reports 1032.0 grid breaks per hour, with a median beat offset of 28 ms.

    Listen to the original set

    Full SOONOS analysis

    TECSELNRGCRWHRMGRVCRESIG
    0

    This DJ treats the mix as a cinematic experience, using every element to serve the story.

    The 8 dimensions

    Technical precision0
    Track selection0
    Energy arc0
    Crowd control0
    Harmonic depth0
    Groove patience0
    Creativity0
    Signature0

    Score breakdown

    TECHNIQUE

    How well did you execute?

    25%77
    Beat Alignmentmeasured66
    Transition Qualitymeasured70
    Phrase Accuracymeasured86
    EQ & Frequency Control (estimated)measured81
    Tempo Stability (estimated)measured90
    Technical Cleanlinessmeasured73

    STORYTELLING

    Did the mix go somewhere?

    25%81
    Narrative ArcAI84
    ProgressionAI80
    Tension & ReleaseAI76
    Section AwarenessAI81
    Flow ContinuityAI85
    PayoffAI76

    ENERGY

    Did you control the room?

    20%79
    Energy Curvemeasured77
    PacingAI79
    MomentumAI84
    Peak ManagementAI78
    Energy HandoffAI79
    Fatigue ControlAI76

    SURPRISE

    Did you remain unpredictable?

    15%76
    Unexpected MomentsAI72
    ContrastAI78
    Transition Varietymeasured86
    Selection RiskAI75
    FreshnessAI70
    Surprise ControlAI72

    IDENTITY

    Did the mix sound like you?

    15%82
    Selection QualityAI81
    Identity ConsistencyAI90
    IntentionalityAI81
    ConfidenceAI83
    RestraintAI79
    SignatureAI75

    Final score capped by measured execution (-) — weighted average was 79.

    Energy arc

    0:00111:00

    Transitions analysed (7)

    4:12

    Long EQ blend with host fade-out

    Masterful transition from spoken word intro into the first musical chapter.

    92
    7:45

    Percussive layering

    Smooth introduction of new rhythmic elements, maintaining the organic flow.

    84
    10:15

    Vocal stem layering

    Excellent use of vocal chants to bridge into a more driving Afro-house section.

    89
    12:15

    Long EQ blend, low-end swap on phrase

    Transparent transition, perfectly beat-matched and phrase-aligned.

    88
    16:20

    Mid-frequency blend with high-pass filter

    Smooth transition using filters to manage the energy handoff.

    85
    23:52

    Long EQ blend with low-end swap

    Extremely smooth transition. The incoming kick replaces the outgoing one almost imperceptibly.

    92
    28:14

    Mid-range handover

    Clean swap of the melodic/percussive elements in the mid-frequencies. Phrase alignment is spot on.

    85

    Technical subscores

    81

    EQ balance

    88

    Beat alignment

    80

    Energy control

    90

    Tempo stability

    81

    Loudness control

    85

    Musical coherence

    83

    Harmonic compatibility

    84

    Transition cleanliness

    Measured (DSP)

    28.1 ms

    Beat-grid drift (median)

    201.8 ms

    Drift p95

    7,302

    Boundaries detected

    93

    Hard cuts / h

    198

    Clipping events

    1144

    Level jumps

    Measurement confidence 99% · analysed on the full audio.

    Recurring patterns

    • Long static loops (6×)

      Sections sitting on the same loop without layering, EQ moves or tension shifts (30:00, 52:15, 71:00, 78:00, 82:45, 91:00). Long loops kill dancefloor momentum.

    Timeline

    • 2:15Narrative Hook
    • 6:30Groove Lock
    • 9:45Atmospheric Peak
    • 14:30Groove Lock
    • 18:45Energy Plateau
    • 25:45Groove Lock

    Coaching notes

    • Experiment with subtle high-pass filter sweeps during transitions to add more dynamic movement.
    • Introduce a recurring melodic motif to further strengthen the narrative identity.
    • Slightly increase the volume of the percussive layers to drive the groove harder in the build phase.
    • Refine EQ management during long blends to avoid mid-range clutter.
    • Experiment with more dramatic tension-release cycles in breakdowns.
    • Ensure track selection during peak phases maintains melodic or rhythmic urgency.
    • Use subtle FX to bridge transitions between tracks with different sonic textures.
    Listen on SoundCloud

    Curious how your own set scores?

    Questions about this analysis

    What score does Laurent Garnier's IIWII - Season 7 - Show 10 (Juin 2017) get?
    IIWII - Season 7 - Show 10 (Juin 2017) scores 74/100 in the SOONOS Mix Database (solid), based on audio measurement plus multi-agent listening.
    How long is IIWII - Season 7 - Show 10 (Juin 2017)?
    The analysed recording runs 2h 02m.
    Which part of the mix scores best?
    IDENTITY is the strongest category at 82/100, while SURPRISE is the lowest at 76/100.
    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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