I Hate ModelsReality Check: I Hate Models x FEMUR @ Grand Palais, Paris

    Hard Techno · 2h 07m · analysed 20 Aug 2026

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

    About this hard techno set

    Reality Check: I Hate Models x FEMUR @ Grand Palais, Paris is a hard techno DJ set by I Hate Models, 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”.

    The DJ treats the mix as a continuous wall of sound, using EQ and filters to sculpt energy rather than just blend tracks.

    How the score breaks down

    SOONOS scores this set across 5 weighted categories. The strongest is IDENTITY at 93/100; the weakest is TECHNIQUE 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 52 points, moving between 20 and 98 on the SOONOS energy scale — a wide dynamic range across the set.

    6 transitions were detected and scored individually.

    Beat-grid measurement (DSP) reports 253.0 grid breaks per hour, with a median beat offset of 20 ms.

    Listen to the original set

    Full SOONOS analysis

    TECSELNRGCRWHRMGRVCRESIG
    0

    The DJ treats the mix as a continuous wall of sound, using EQ and filters to sculpt energy rather than just blend tracks.

    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%82
    Beat Alignmentmeasured82
    Transition Qualitymeasured65
    Phrase Accuracymeasured92
    EQ & Frequency Control (estimated)measured83
    Tempo Stability (estimated)measured94
    Technical Cleanlinessmeasured78

    STORYTELLING

    Did the mix go somewhere?

    25%91
    Narrative ArcAI92
    ProgressionAI90
    Tension & ReleaseAI87
    Section AwarenessAI91
    Flow ContinuityAI92
    PayoffAI94

    ENERGY

    Did you control the room?

    20%86
    Energy Curvemeasured87
    PacingAI89
    MomentumAI95
    Peak ManagementAI92
    Energy HandoffAI93
    Fatigue ControlAI48

    SURPRISE

    Did you remain unpredictable?

    15%82
    Unexpected MomentsAI84
    ContrastAI80
    Transition Varietymeasured94
    Selection RiskAI88
    FreshnessAI48
    Surprise ControlAI84

    IDENTITY

    Did the mix sound like you?

    15%93
    Selection QualityAI94
    Identity ConsistencyAI98
    IntentionalityAI96
    ConfidenceAI96
    RestraintAI79
    SignatureAI95

    Final score capped by measured execution (-) — weighted average was 87.

    Energy arc

    0:00126:58

    Transitions analysed (6)

    4:22

    Atmospheric layering into rhythmic pulse

    Perfectly timed introduction of the low-end pulse beneath the existing drone.

    90
    9:15

    Percussive layering with high-pass filtering

    Smooth introduction of industrial hats and claps over the driving kick.

    85
    14:20

    High-pass filter sweep with percussive layering

    Perfectly timed energy handoff that increases the perceived speed of the set.

    92
    18:40

    Long blend during breakdown

    Smooth transition that utilizes the atmospheric elements of both tracks to build tension.

    85
    23:45

    High-pass filter swap with percussive layering

    Perfectly timed entry of the new kick drum, maintaining the industrial drive without phase issues.

    92
    27:45

    Long EQ blend focusing on mid-range textures

    Smooth transition between two dense tracks; the DJ manages the frequency spectrum well to avoid mud.

    88

    Technical subscores

    83

    EQ balance

    91

    Beat alignment

    91

    Energy control

    94

    Tempo stability

    87

    Loudness control

    88

    Musical coherence

    80

    Harmonic compatibility

    84

    Transition cleanliness

    Measured (DSP)

    19.7 ms

    Beat-grid drift (median)

    113.3 ms

    Drift p95

    7,599

    Boundaries detected

    193

    Hard cuts / h

    54

    Clipping events

    529

    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 (29:00, 46:00, 53:45, 58:00, 77:00, 81:00). Long loops kill dancefloor momentum.

    Timeline

    • 0:05Atmospheric Hook
    • 6:58The Drop
    • 25:15Industrial Peak Energy
    • 29:50Melodic Contrast

    Coaching notes

    • Experiment with a 'false ending' or a total breakdown to create a more dramatic final resolution.
    • Incorporate a brief melodic motif in the final 2 minutes to provide a memorable emotional hook.
    • Slightly reduce the mid-range gain during the 120:45 transition to ensure total clarity.
    Listen on SoundCloud

    Curious how your own set scores?

    Questions about this analysis

    What score does I Hate Models's Reality Check: I Hate Models x FEMUR @ Grand Palais, Paris get?
    Reality Check: I Hate Models x FEMUR @ Grand Palais, Paris scores 85/100 in the SOONOS Mix Database (festival ready), based on audio measurement plus multi-agent listening.
    How long is Reality Check: I Hate Models x FEMUR @ Grand Palais, Paris?
    The analysed recording runs 2h 07m.
    Which part of the mix scores best?
    IDENTITY is the strongest category at 93/100, while TECHNIQUE 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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