Daniel AveryDaniel Avery - NTS Radio (2nd January 2018)

    Indie House · 1h 01m · analysed 22 Aug 2026

    Overall score
    73/100
    Level
    solid
    Duration
    1h 01m
    Genre
    Indie House

    About this indie house set

    Daniel Avery - NTS Radio (2nd January 2018) is a indie house DJ set by Daniel Avery, running 1h 01m. It was measured by the SOONOS multi-agent engine and scores 73/100 overall — solid.

    The engine files this performance as “Promising”.

    Daniel Avery proves that true energy comes from the relentless pressure of a perfectly maintained groove, not just from drops.

    How the score breaks down

    SOONOS scores this set across 5 weighted categories. The strongest is IDENTITY at 95/100; the weakest is TECHNIQUE at 55/100.

    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 20 points, moving between 30 and 82 on the SOONOS energy scale — a wide dynamic range across the set.

    6 transitions were detected and scored individually.

    Beat-grid measurement (DSP) reports 2304.6 grid breaks per hour, with a median beat offset of 138 ms.

    Listen to the original set

    Full SOONOS analysis

    TECSELNRGCRWHRMGRVCRESIG
    0

    Daniel Avery proves that true energy comes from the relentless pressure of a perfectly maintained groove, not just from drops.

    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%55
    Beat Alignmentmeasured15
    Transition Qualitymeasured82
    Phrase Accuracymeasured91
    EQ & Frequency Control (estimated)measured89
    Tempo Stability (estimated)measured94
    Technical Cleanlinessmeasured78

    STORYTELLING

    Did the mix go somewhere?

    25%89
    Narrative ArcAI93
    ProgressionAI89
    Tension & ReleaseAI87
    Section AwarenessAI89
    Flow ContinuityAI93
    PayoffAI83

    ENERGY

    Did you control the room?

    20%87
    Energy Curvemeasured87
    PacingAI92
    MomentumAI90
    Peak ManagementAI86
    Energy HandoffAI87
    Fatigue ControlAI71

    SURPRISE

    Did you remain unpredictable?

    15%85
    Unexpected MomentsAI82
    ContrastAI85
    Transition Varietymeasured94
    Selection RiskAI87
    FreshnessAI69
    Surprise ControlAI82

    IDENTITY

    Did the mix sound like you?

    15%95
    Selection QualityAI94
    Identity ConsistencyAI97
    IntentionalityAI95
    ConfidenceAI93
    RestraintAI93
    SignatureAI95

    Final score capped by measured execution (-) — weighted average was 80.

    Energy arc

    0:0049:00

    Transitions analysed (6)

    3:45

    Long EQ blend with subtle high-pass filtering

    A masterfully executed transition where the incoming track's atmosphere seamlessly replaces the outgoing one.

    95
    8:12

    Layered percussion blend over 32 bars

    The transition is so gradual it feels like a natural evolution of the track rather than a change.

    92
    13:32

    Long EQ blend

    Seamless integration of new percussive layers.

    92
    17:25

    Filter-assisted blend

    Smooth transition using high-pass filtering to clear space.

    88
    22:00

    EQ-based handover

    Flawless low-end swap on the phrase boundary.

    90
    25:42

    Long EQ blend with high-pass filtering.

    Perfectly executed transition that maintains the hypnotic flow.

    92

    Technical subscores

    89

    EQ balance

    95

    Beat alignment

    88

    Energy control

    94

    Tempo stability

    87

    Loudness control

    93

    Musical coherence

    90

    Harmonic compatibility

    92

    Transition cleanliness

    Measured (DSP)

    137.5 ms

    Beat-grid drift (median)

    214.7 ms

    Drift p95

    3,625

    Boundaries detected

    21

    Hard cuts / h

    32

    Clipping events

    336

    Level jumps

    Measurement confidence 99% · analysed on the full audio.

    Recurring patterns

    • Long static loops (5×)

      Sections sitting on the same loop without layering, EQ moves or tension shifts (6:00, 10:00, 14:00, 36:00, 41:00). Long loops kill dancefloor momentum.

    Timeline

    • 0:00Atmospheric Opening
    • 5:30Groove Lock
    • 10:45Energy Shift
    • 15:30Groove Lock
    • 19:45Textural Peak
    • 29:30Atmospheric Peak

    Coaching notes

    • Continue to prioritize long, seamless blends to maintain the hypnotic state.
    • Experiment with brief moments of silence or sudden resets to dramatically shift the pressure.
    • Introduce subtle, warmer melodic elements to provide contrast to the industrial darkness.
    • Ensure the energy continues to evolve progressively to avoid any potential plateaus in longer sets.
    • Maintain the long, patient blends; they are a signature of your style.
    • Experiment with layering more melodic elements to add emotional depth.
    • Use high-pass filters even more aggressively to create moments of tension.
    • Consider a slightly more varied rhythmic palette in the next segment.
    Listen on SoundCloud

    Curious how your own set scores?

    Questions about this analysis

    What score does Daniel Avery's Daniel Avery - NTS Radio (2nd January 2018) get?
    Daniel Avery - NTS Radio (2nd January 2018) scores 73/100 in the SOONOS Mix Database (solid), based on audio measurement plus multi-agent listening.
    How long is Daniel Avery - NTS Radio (2nd January 2018)?
    The analysed recording runs 1h 01m.
    Which part of the mix scores best?
    IDENTITY is the strongest category at 95/100, while TECHNIQUE is the lowest at 55/100.
    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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