Bart SkilsBart Skils @ Drumcode x Loveland, Sonar Barcelona [17-06-2016]

    Peak Techno · 1h 27m · Sonar · analysed 21 Aug 2026

    Overall score
    86/100
    Level
    festival ready
    Duration
    1h 27m
    Genre
    Peak Techno

    About this peak techno set

    Bart Skils @ Drumcode x Loveland, Sonar Barcelona [17-06-2016] is a peak techno DJ set by Bart Skils, running 1h 27m. It was measured by the SOONOS multi-agent engine and scores 86/100 overall — festival ready.

    The engine files this performance as “Promising”.

    Bart Skils demonstrates why he is a Drumcode staple, delivering a set that is as technically proficient as it is dancefloor-effective.

    How the score breaks down

    SOONOS scores this set across 5 weighted categories. The strongest is IDENTITY at 93/100; 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 30 points, moving between 20 and 95 on the SOONOS energy scale — a wide dynamic range across the set.

    7 transitions were detected and scored individually.

    Beat-grid measurement (DSP) reports 162.6 grid breaks per hour, with a median beat offset of 7 ms.

    Listen to the original set

    Full SOONOS analysis

    TECSELNRGCRWHRMGRVCRESIG
    0

    Bart Skils demonstrates why he is a Drumcode staple, delivering a set that is as technically proficient as it is dancefloor-effective.

    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%92
    Beat Alignmentmeasured98
    Transition Qualitymeasured87
    Phrase Accuracymeasured94
    EQ & Frequency Control (estimated)measured91
    Tempo Stability (estimated)measured97
    Technical Cleanlinessmeasured80

    STORYTELLING

    Did the mix go somewhere?

    25%91
    Narrative ArcAI93
    ProgressionAI90
    Tension & ReleaseAI86
    Section AwarenessAI91
    Flow ContinuityAI95
    PayoffAI89

    ENERGY

    Did you control the room?

    20%86
    Energy Curvemeasured82
    PacingAI92
    MomentumAI94
    Peak ManagementAI89
    Energy HandoffAI90
    Fatigue ControlAI57

    SURPRISE

    Did you remain unpredictable?

    15%82
    Unexpected MomentsAI82
    ContrastAI82
    Transition Varietymeasured93
    Selection RiskAI85
    FreshnessAI54
    Surprise ControlAI82

    IDENTITY

    Did the mix sound like you?

    15%93
    Selection QualityAI91
    Identity ConsistencyAI97
    IntentionalityAI94
    ConfidenceAI94
    RestraintAI89
    SignatureAI91

    Final score capped by measured execution (-) — weighted average was 89.

    Energy arc

    0:0086:00

    Transitions analysed (7)

    4:12

    Long EQ blend with low-end swap

    A textbook techno transition, perfectly phased and balanced.

    92
    9:20

    Percussive layering and high-pass filtering

    Smoothly introduces new rhythmic layers while maintaining the core groove.

    90
    12:15

    Perfect Blend

    100
    16:20

    Minor EQ Overlap

    intentional_reset

    82
    20:45

    Seamless Handoff

    100
    24:15

    Perfect Blend

    100
    28:40

    Surgical EQ Swap

    100

    Technical subscores

    91

    EQ balance

    95

    Beat alignment

    91

    Energy control

    97

    Tempo stability

    91

    Loudness control

    93

    Musical coherence

    88

    Harmonic compatibility

    92

    Transition cleanliness

    Measured (DSP)

    7.2 ms

    Beat-grid drift (median)

    51.4 ms

    Drift p95

    5,203

    Boundaries detected

    51

    Hard cuts / h

    8

    Clipping events

    149

    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 (33:00, 39:50, 44:00, 50:00, 54:00, 58:22). Long loops kill dancefloor momentum.

    Timeline

    • 0:45Atmospheric Hook
    • 6:30Groove Lock

    Coaching notes

    • Maintain the exceptional level of technical precision.
    • Experiment with more varied atmospheric textures to enhance the emotional depth.
    • Continue to master the art of the long, evolving blend.
    • Experiment with longer filter sweeps to build more tension before drops.
    • Incorporate a track with a more prominent vocal or melodic hook to create a memorable peak.
    • Monitor the high-frequency levels during intense layering to avoid ear fatigue.
    • Continue to trust the long blend; it is your strongest technical asset.
    • Consider a 'reset' moment (short breakdown) to make the subsequent re-entry hit even harder.
    • Explore slightly more melodic B-sides to add emotional depth to the industrial drive.
    • Continue focusing on long, locked-in percussive blends.
    • Use high-pass filters more aggressively during transitions to create tension.
    • Introduce a melodic element in the final track to signal the set's conclusion.
    Listen on SoundCloud

    Curious how your own set scores?

    Questions about this analysis

    What score does Bart Skils's Bart Skils @ Drumcode x Loveland, Sonar Barcelona [17-06-2016] get?
    Bart Skils @ Drumcode x Loveland, Sonar Barcelona [17-06-2016] scores 86/100 in the SOONOS Mix Database (festival ready), based on audio measurement plus multi-agent listening.
    How long is Bart Skils @ Drumcode x Loveland, Sonar Barcelona [17-06-2016]?
    The analysed recording runs 1h 27m.
    Which part of the mix scores best?
    IDENTITY is the strongest category at 93/100, 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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