Sven VäthOpening For Sven Väth, Front Rite Montreal 11.23.2024

    Classics · 2h 07m · analysed 18 Aug 2026

    Overall score
    85/100
    Level
    festival ready
    Duration
    2h 07m
    Genre
    Classics

    About this classics set

    Opening For Sven Väth, Front Rite Montreal 11.23.2024 is a classics DJ set by Sven Väth, running 2h 07m. It was measured by the SOONOS multi-agent engine and scores 85/100 overall — festival ready.

    The engine files this performance as “Promising”.

    This DJ understands that an opening set is about building a foundation, not showing off.

    How the score breaks down

    SOONOS scores this set across 5 weighted categories. The strongest is IDENTITY at 91/100; the weakest is SURPRISE at 82/100.

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

    6 transitions were detected and scored individually.

    Beat-grid measurement (DSP) reports 1045.5 grid breaks per hour, with a median beat offset of 24 ms.

    Listen to the original set

    Full SOONOS analysis

    TECSELNRGCRWHRMGRVCRESIG
    0

    This DJ understands that an opening set is about building a foundation, not showing off.

    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%85
    Beat Alignmentmeasured76
    Transition Qualitymeasured78
    Phrase Accuracymeasured92
    EQ & Frequency Control (estimated)measured88
    Tempo Stability (estimated)measured94
    Technical Cleanlinessmeasured80

    STORYTELLING

    Did the mix go somewhere?

    25%87
    Narrative ArcAI92
    ProgressionAI88
    Tension & ReleaseAI83
    Section AwarenessAI88
    Flow ContinuityAI93
    PayoffAI77

    ENERGY

    Did you control the room?

    20%84
    Energy Curvemeasured78
    PacingAI93
    MomentumAI89
    Peak ManagementAI85
    Energy HandoffAI85
    Fatigue ControlAI66

    SURPRISE

    Did you remain unpredictable?

    15%82
    Unexpected MomentsAI79
    ContrastAI84
    Transition Varietymeasured92
    Selection RiskAI84
    FreshnessAI63
    Surprise ControlAI79

    IDENTITY

    Did the mix sound like you?

    15%91
    Selection QualityAI89
    Identity ConsistencyAI97
    IntentionalityAI91
    ConfidenceAI89
    RestraintAI94
    SignatureAI85

    Final score capped by measured execution (-) — weighted average was 86.

    Energy arc

    0:00126:00

    Transitions analysed (6)

    5:12

    Long EQ blend with low-end swap

    Perfectly executed transition that maintains the hypnotic flow.

    95
    11:05

    Percussive layering and mid-range swap

    Seamless integration of new rhythmic elements.

    92
    13:15

    Long EQ blend with low-end swap

    Invisible transition that respects the phrasing of both tracks.

    94
    18:40

    Atmospheric layering and filter fade

    Beautifully executed blend of textures, creating a rich sonic landscape.

    92
    24:15

    Long EQ blend with low-end swap

    A textbook deep techno transition. The incoming kick replaces the outgoing one so smoothly it's almost imperceptible.

    88
    29:40

    Layered percussion blend

    Excellent use of layering to build rhythmic complexity before removing the first track.

    85

    Technical subscores

    88

    EQ balance

    94

    Beat alignment

    88

    Energy control

    94

    Tempo stability

    86

    Loudness control

    90

    Musical coherence

    89

    Harmonic compatibility

    91

    Transition cleanliness

    Measured (DSP)

    24.3 ms

    Beat-grid drift (median)

    259.2 ms

    Drift p95

    7,576

    Boundaries detected

    42

    Hard cuts / h

    61

    Clipping events

    517

    Level jumps

    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 (14:00, 20:00, 25:00, 31:00, 38:42, 46:00). Long loops kill dancefloor momentum.

    What SOONOS heard

    • Restraint
    • Technical precision
    • Contextual awareness

    Timeline

    • 0:00Atmospheric Hook
    • 7:45Groove Lock
    • 15:45Groove Lock
    • 20:30Atmospheric Peak
    • 27:10Groove Lock

    Coaching notes

    • Continue to trust your patience; the long-form storytelling is world-class.
    • Experiment with very subtle field recordings or non-musical textures to further enhance the 'journey' aspect.
    • Ensure the transition into the next DJ (or the next phase of your set) maintains this level of technical transparency.
    • Experiment with manual loop manipulation to create unique rhythmic variations during long blends.
    • Use subtle reverb sends on percussive elements to increase the sense of space.
    • Consider a 'reset' moment—a brief period of near-silence—to heighten the impact of the next energy push.
    Listen on SoundCloud

    Curious how your own set scores?

    Questions about this analysis

    What score does Sven Väth's Opening For Sven Väth, Front Rite Montreal 11.23.2024 get?
    Opening For Sven Väth, Front Rite Montreal 11.23.2024 scores 85/100 in the SOONOS Mix Database (festival ready), based on audio measurement plus multi-agent listening.
    How long is Opening For Sven Väth, Front Rite Montreal 11.23.2024?
    The analysed recording runs 2h 07m.
    Which part of the mix scores best?
    IDENTITY is the strongest category at 91/100, while SURPRISE is the lowest at 82/100.
    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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