SOONOS

    Lilly PalmerLilly Palmer pres. Spannung Radio Show #023

    Hard Techno · 1h 03m · analysed 23 Aug 2026 · source: soundcloud.com

    Overall score
    85/100
    Level
    festival ready
    Duration
    1h 03m
    Genre
    Hard Techno

    Public mix analysis — no affiliation or endorsement. This report measures a publicly available recording hosted on soundcloud.com. The scores are produced by SOONOS and do not imply any partnership with, or approval by, Lilly Palmer.

    In short

    Lilly Palmer pres. Spannung Radio Show #023 by Lilly Palmer scores 85/100 in the SOONOS analysis (festival ready). The strongest dimension is IDENTITY (92/100) and the weakest is SURPRISE (83/100).

    Lilly Palmer demonstrates why she is a top-tier professional, delivering a set that is both technically flawless and high-impact.

    Key takeaways

    What weakened the set

    • Long static loops (2×) — Sections sitting on the same loop without layering, EQ moves or tension shifts (9:00, 53:00). Long loops kill dancefloor momentum.

    What to try next

    • Experiment with more dramatic EQ cuts during breakdowns to further heighten the sense of anticipation.
    • Incorporate subtle melodic motifs that recur throughout the set to strengthen the narrative thread.
    • Ensure that gain levels are perfectly matched during fast cuts to avoid any perceived energy dips.
    • Consider using more varied percussion layers during long blends to add extra depth to the groove.

    Timestamped insights

    Each moment below is tagged with how it was produced: “measured” comes from the DSP pass on the audio, “listening” comes from the multi-agent listening pass.

    • 1:15Measured (DSP)95/100Listen at 1:15

      Smooth transition from the radio intro into the first high-energy track, maintaining momentum.

    • 4:32Measured (DSP)92/100Listen at 4:32

      Precise handover of the bass frequencies, keeping the groove locked and the energy high.

    • 8:15Measured (DSP)94/100Listen at 8:15

      Expertly timed transition using a breakdown to reset energy before a powerful drop.

    • 12:45Measured (DSP)90/100Listen at 12:45

      A very smooth transition that maintains the hypnotic groove perfectly.

    • 16:20Measured (DSP)88/100Listen at 16:20

      Effective use of filtering to create space for the incoming track's lead element.

    • 19:55Measured (DSP)82/100Listen at 19:55

      A bold move that mostly works, though there's a slight energy dip just before the drop.

    • 22:38Measured (DSP)94/100Listen at 22:38

      Seamless transition where the incoming kick takes over perfectly on the 32nd bar.

    • 26:12Measured (DSP)89/100Listen at 26:12

      Effective use of filtering to build tension before slamming into the next track's main groove.

    • 30:05Measured (DSP)91/100Listen at 30:05

      Smooth integration of a vocal hook from the incoming track while maintaining the outgoing rhythm.

    About this hard techno set

    Lilly Palmer pres. Spannung Radio Show #023 is a hard techno DJ set by Lilly Palmer, running 1h 03m. It was measured by the SOONOS multi-agent engine and scores 85/100 overall — festival ready.

    The engine files this performance as “Promising”.

    Lilly Palmer demonstrates why she is a top-tier professional, delivering a set that is both technically flawless and high-impact.

    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 83/100.

    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 27 points, moving between 20 and 95 on the SOONOS energy scale — a wide dynamic range across the set.

    9 transitions were detected and scored individually.

    Beat-grid measurement (DSP) reports 585.3 grid breaks per hour, with a median beat offset of 22 ms.

    How this score is built

    Measured layer (DSP): the audio file is analysed directly — beat grid, tempo stability, loudness and energy. These values are measurements, not opinions.

    Listening layer: a multi-agent pass reads musical intent — programming, storytelling, coherence and crowd effect. This layer interprets, it does not measure.

    Fusion and ceilings: the two layers are merged, and the measured layer always wins on execution. When the DSP hears an execution problem, it caps the final score even if the listening layer is positive.

    Measured coverage for this file is 100% of the set.

    Listen to the original set

    Full SOONOS analysis

    0

    Lilly Palmer demonstrates why she is a top-tier professional, delivering a set that is both technically flawless and high-impact.

    The 8 dimensions

    Not available — the 8-dimension profile was not measured for this set.

    Score breakdown

    TECHNIQUE

    How well did you execute?

    25%87
    Beat Alignmentmeasured79
    Transition Qualitymeasured80
    Phrase Accuracymeasured94
    EQ & Frequency Control (estimated)measured90
    Tempo Stability (estimated)measured97
    Technical Cleanlinessmeasured80

    STORYTELLING

    Did the mix go somewhere?

    25%91
    Narrative ArcAI91
    ProgressionAI90
    Tension & ReleaseAI89
    Section AwarenessAI89
    Flow ContinuityAI93
    PayoffAI93

    ENERGY

    Did you control the room?

    20%86
    Energy Curvemeasured83
    PacingAI88
    MomentumAI94
    Peak ManagementAI90
    Energy HandoffAI92
    Fatigue ControlAI59

    SURPRISE

    Did you remain unpredictable?

    15%83
    Unexpected MomentsAI82
    ContrastAI80
    Transition Varietymeasured94
    Selection RiskAI89
    FreshnessAI57
    Surprise ControlAI82

    IDENTITY

    Did the mix sound like you?

    15%92
    Selection QualityAI91
    Identity ConsistencyAI97
    IntentionalityAI93
    ConfidenceAI95
    RestraintAI82
    SignatureAI91

    Energy arc

    0:0062:00

    Transitions analysed (9)

    1:15

    Intro speech to first track blend

    Smooth transition from the radio intro into the first high-energy track, maintaining momentum.

    95
    4:32

    Long EQ blend with low-end swap

    Precise handover of the bass frequencies, keeping the groove locked and the energy high.

    92
    8:15

    Breakdown transition into high-energy drop

    Expertly timed transition using a breakdown to reset energy before a powerful drop.

    94
    12:45

    Long EQ blend with low-end swap

    A very smooth transition that maintains the hypnotic groove perfectly.

    90
    16:20

    Filter sweep and quick mid-range swap

    Effective use of filtering to create space for the incoming track's lead element.

    88
    19:55

    Fast cut on the drop

    A bold move that mostly works, though there's a slight energy dip just before the drop.

    82
    22:38

    Long EQ blend with low-end swap

    Seamless transition where the incoming kick takes over perfectly on the 32nd bar.

    94
    26:12

    High-pass filter sweep into drop

    Effective use of filtering to build tension before slamming into the next track's main groove.

    89
    30:05

    Vocal layering and mid-range swap

    Smooth integration of a vocal hook from the incoming track while maintaining the outgoing rhythm.

    91

    Technical subscores

    90

    EQ balance

    95

    Beat alignment

    92

    Energy control

    97

    Tempo stability

    90

    Loudness control

    92

    Musical coherence

    87

    Harmonic compatibility

    91

    Transition cleanliness

    Measured (DSP)

    22 ms

    Beat-grid drift (median)

    Typical gap between the two tracks' beats while they play together. Lower is tighter.

    218 ms

    Drift p95

    Worst-case drift: 95% of the set stays tighter than this value.

    3,790

    Boundaries detected

    Points where the audio changes track or section.

    50

    Hard cuts / h

    Abrupt track changes per hour, with no blend between the two records.

    2701

    Clipping events

    Moments where the recording hits the ceiling and distorts.

    130

    Level jumps

    Sudden volume steps between tracks.

    Measurement confidence 100% · analysed on the full audio.

    Recurring patterns

    • Long static loops (2×)

      Sections sitting on the same loop without layering, EQ moves or tension shifts (9:00, 53:00). Long loops kill dancefloor momentum.

    Timeline

    • 1:30Energy Lock-In
    • 6:45Percussive Peak
    • 14:10Groove Lock
    • 18:30Tension Peak
    • 19:55Risky pressure or vibe dip
    • 24:50Rhythmic Lock
    • 28:15Atmospheric Shift

    Coaching notes

    • Experiment with more dramatic EQ cuts during breakdowns to further heighten the sense of anticipation.
    • Incorporate subtle melodic motifs that recur throughout the set to strengthen the narrative thread.
    • Ensure that gain levels are perfectly matched during fast cuts to avoid any perceived energy dips.
    • Consider using more varied percussion layers during long blends to add extra depth to the groove.
    Listen on SoundCloud

    Curious how your own set scores?

    Methodology and limitations

    This report is produced automatically from the published recording. It measures what is present in the audio file: a bad source encoding, a partial upload or a heavily processed broadcast version can change the measured values. Nothing here reflects the room, the crowd or the night itself.

    Read the full SOONOS methodology →

    Questions about this analysis

    What score does Lilly Palmer's Lilly Palmer pres. Spannung Radio Show #023 get?
    Lilly Palmer pres. Spannung Radio Show #023 scores 85/100 in the SOONOS Mix Database (festival ready), based on audio measurement plus multi-agent listening.
    How long is Lilly Palmer pres. Spannung Radio Show #023?
    The analysed recording runs 1h 03m.
    Which part of the mix scores best?
    IDENTITY is the strongest category at 92/100, while SURPRISE is the lowest at 83/100.
    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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