1788-LROAD TO LOST LANDS 2024 : 1788-L VELVET UNDERGROUND TORONTO SET

    MID Tempo Bass · 56 min · analysed 21 Aug 2026

    Overall score
    85/100
    Level
    festival ready
    Duration
    56 min
    Genre
    MID Tempo Bass

    About this mid tempo bass set

    ROAD TO LOST LANDS 2024 : 1788-L VELVET UNDERGROUND TORONTO SET is a mid tempo bass DJ set by 1788-L, running 56 min. It was measured by the SOONOS multi-agent engine and scores 85/100 overall — festival ready.

    The engine files this performance as “Promising”.

    The use of cinematic silence as a weapon makes the subsequent drops feel twice as heavy.

    How the score breaks down

    SOONOS scores this set across 5 weighted categories. The strongest is IDENTITY at 92/100; the weakest is SURPRISE at 84/100.

    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 28 points, moving between 40 and 98 on the SOONOS energy scale — a wide dynamic range across the set.

    10 transitions were detected and scored individually.

    Beat-grid measurement (DSP) reports 587.7 grid breaks per hour, with a median beat offset of 20 ms.

    Listen to the original set

    Full SOONOS analysis

    TECSELNRGCRWHRMGRVCRESIG
    0

    The use of cinematic silence as a weapon makes the subsequent drops feel twice as heavy.

    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%88
    Beat Alignmentmeasured81
    Transition Qualitymeasured86
    Phrase Accuracymeasured92
    EQ & Frequency Control (estimated)measured86
    Tempo Stability (estimated)measured97
    Technical Cleanlinessmeasured85

    STORYTELLING

    Did the mix go somewhere?

    25%89
    Narrative ArcAI91
    ProgressionAI87
    Tension & ReleaseAI87
    Section AwarenessAI90
    Flow ContinuityAI86
    PayoffAI95

    ENERGY

    Did you control the room?

    20%84
    Energy Curvemeasured81
    PacingAI86
    MomentumAI92
    Peak ManagementAI89
    Energy HandoffAI92
    Fatigue ControlAI52

    SURPRISE

    Did you remain unpredictable?

    15%84
    Unexpected MomentsAI84
    ContrastAI83
    Transition Varietymeasured92
    Selection RiskAI90
    FreshnessAI56
    Surprise ControlAI84

    IDENTITY

    Did the mix sound like you?

    15%92
    Selection QualityAI92
    Identity ConsistencyAI97
    IntentionalityAI96
    ConfidenceAI96
    RestraintAI73
    SignatureAI96

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

    Energy arc

    0:0056:00

    Transitions analysed (10)

    0:45

    Cinematic Handoff

    strategic_disruption

    100
    2:15

    Rhythmic Switch

    82
    5:12

    Bass Swap

    intentional_reset

    100
    7:20

    Glitch Transition

    82
    10:15

    Peak Energy Cut

    strategic_disruption

    100
    11:22

    Hard cut on phrase with immediate low-end swap

    Sharp, professional transition that maintains the aggressive momentum.

    92
    15:45

    Short blend with high-pass filter sweep

    Effective energy handoff that builds tension into the next section.

    85
    18:40

    Abrupt cut-out into silence

    A bold reset that briefly breaks the groove but sets up a massive drop.

    78
    23:45

    Perfect Drop Swap

    100
    28:00

    Seamless Glitch Blend

    100

    Technical subscores

    86

    EQ balance

    94

    Beat alignment

    91

    Energy control

    97

    Tempo stability

    87

    Loudness control

    87

    Musical coherence

    83

    Harmonic compatibility

    89

    Transition cleanliness

    Measured (DSP)

    20.1 ms

    Beat-grid drift (median)

    174.8 ms

    Drift p95

    3,370

    Boundaries detected

    25

    Hard cuts / h

    51

    Clipping events

    193

    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 (13:00, 19:00, 36:00, 45:00, 50:00). Long loops kill dancefloor momentum.

    What SOONOS heard

    • Exceptional energy management.
    • Strong, recognizable artistic identity.
    • Professional-grade technical execution.

    Timeline

    • 0:58First Impact
    • 4:20The Vacuum
    • 8:45Rhythmic Climax
    • 13:45Sonic Texture Shift
    • 21:30Energy Peak
    • 18:40Risky pressure or vibe dip

    Coaching notes

    • Introduce more melodic contrast to enhance the impact of aggressive sections.
    • Experiment with longer, atmospheric breakdowns for a greater sense of scale.
    • Incorporate recognizable vocal hooks to increase crowd engagement.
    • Monitor high-frequency harshness at extreme volumes.
    • Introduce more micro-variations during high-energy plateaus to maintain narrative momentum.
    • Experiment with longer, more melodic breakdowns to provide a stronger emotional contrast.
    • Ensure all quick cuts are perfectly phrase-aligned to avoid breaking the listener's hypnotic state.
    Listen on SoundCloud

    Curious how your own set scores?

    Questions about this analysis

    What score does 1788-L's ROAD TO LOST LANDS 2024 : 1788-L VELVET UNDERGROUND TORONTO SET get?
    ROAD TO LOST LANDS 2024 : 1788-L VELVET UNDERGROUND TORONTO SET scores 85/100 in the SOONOS Mix Database (festival ready), based on audio measurement plus multi-agent listening.
    How long is ROAD TO LOST LANDS 2024 : 1788-L VELVET UNDERGROUND TORONTO SET?
    The analysed recording runs 56 min.
    Which part of the mix scores best?
    IDENTITY is the strongest category at 92/100, while SURPRISE is the lowest at 84/100.
    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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