Kevin de Vries — Kevin De Vries | Loveland Festival 2019 | LL111
Melodic Techno · 2h 06m · analysed 23 Aug 2026 · source: soundcloud.com
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, Kevin de Vries.
In short
Kevin De Vries | Loveland Festival 2019 | LL111 by Kevin de Vries scores 86/100 in the SOONOS analysis (festival ready). The strongest dimension is IDENTITY (91/100) and the weakest is SURPRISE (83/100).
The DJ's ability to maintain a relentless drive while introducing subtle emotional layers is what sets this performance apart.
Key takeaways
What weakened the set
- Long static loops (6×) — Sections sitting on the same loop without layering, EQ moves or tension shifts (13:00, 19:00, 34:00, 44:00, 46:00, 50:00). Long loops kill dancefloor momentum.
What to try next
- Experiment with brief, high-impact melodic breakdowns.
- Incorporate more rhythmic syncopation to vary the groove.
- Use vocal elements sparingly to add a human touch to the cinematic soundscape.
- Continue to refine the balance between raw energy and melodic depth.
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.
A textbook techno transition. The incoming track's sub-bass is introduced so subtly it feels like a natural evolution of the first track.
Effective use of filtering to clear space for the next track's lead elements.
Perfectly executed transition, maintaining the groove while introducing new melodic textures.
Smooth energy handoff using filtering to clear space for the new track's transients.
About this melodic techno set
Kevin De Vries | Loveland Festival 2019 | LL111 is a melodic techno DJ set by Kevin de Vries, running 2h 06m. It was measured by the SOONOS multi-agent engine and scores 86/100 overall — festival ready.
The engine files this performance as “Promising”.
The DJ's ability to maintain a relentless drive while introducing subtle emotional layers is what sets this performance apart.
How the score breaks down
SOONOS scores this set across 5 weighted categories. The strongest is IDENTITY at 91/100; 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 61 points, moving between 20 and 95 on the SOONOS energy scale — a wide dynamic range across the set.
6 transitions were detected and scored individually.
Beat-grid measurement (DSP) reports 386.6 grid breaks per hour, with a median beat offset of 21 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.
Full SOONOS analysis
The DJ's ability to maintain a relentless drive while introducing subtle emotional layers is what sets this performance apart.
The 8 dimensions
Not available — the 8-dimension profile was not measured for this set.
Score breakdown
TECHNIQUE
How well did you execute?
25%84
TECHNIQUE
How well did you execute?
STORYTELLING
Did the mix go somewhere?
25%90
STORYTELLING
Did the mix go somewhere?
ENERGY
Did you control the room?
20%87
ENERGY
Did you control the room?
SURPRISE
Did you remain unpredictable?
15%83
SURPRISE
Did you remain unpredictable?
IDENTITY
Did the mix sound like you?
15%91
IDENTITY
Did the mix sound like you?
Energy arc
Transitions analysed (6)
Long EQ blend with low-end swap
A textbook techno transition. The incoming track's sub-bass is introduced so subtly it feels like a natural evolution of the first track.
High-pass filter transition
Effective use of filtering to clear space for the next track's lead elements.
Long EQ blend with low-end swap
Perfectly executed transition, maintaining the groove while introducing new melodic textures.
High-pass filter transition with percussive layering
Smooth energy handoff using filtering to clear space for the new track's transients.
Perfect Blend
Surgical EQ Swap
Technical subscores
88
EQ balance
94
Beat alignment
89
Energy control
96
Tempo stability
87
Loudness control
90
Musical coherence
91
Harmonic compatibility
90
Transition cleanliness
Measured (DSP)
21 ms
Beat-grid drift (median)
Typical gap between the two tracks' beats while they play together. Lower is tighter.
145 ms
Drift p95
Worst-case drift: 95% of the set stays tighter than this value.
7,544
Boundaries detected
Points where the audio changes track or section.
144
Hard cuts / h
Abrupt track changes per hour, with no blend between the two records.
1511
Clipping events
Moments where the recording hits the ceiling and distorts.
495
Level jumps
Sudden volume steps between tracks.
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 (13:00, 19:00, 34:00, 44:00, 46:00, 50:00). Long loops kill dancefloor momentum.
Timeline
- 5:45Seamless Evolution
- 8:30Groove Lock
- 14:50Atmospheric Peak
- 21:30Groove Lock
Coaching notes
- Experiment with brief, high-impact melodic breakdowns.
- Incorporate more rhythmic syncopation to vary the groove.
- Use vocal elements sparingly to add a human touch to the cinematic soundscape.
- Continue to refine the balance between raw energy and melodic depth.
- Experiment with more complex rhythmic layering during transitions.
- Incorporate more frequent use of silence or extreme filtering to create dramatic tension releases.
- Experiment with live stem manipulation during the final peak.
- Incorporate more varied percussive elements in the outro fade.
- Maintain the high level of harmonic awareness shown here.
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 Kevin de Vries's Kevin De Vries | Loveland Festival 2019 | LL111 get?
- Kevin De Vries | Loveland Festival 2019 | LL111 scores 86/100 in the SOONOS Mix Database (festival ready), based on audio measurement plus multi-agent listening.
- How long is Kevin De Vries | Loveland Festival 2019 | LL111?
- The analysed recording runs 2h 06m.
- Which part of the mix scores best?
- IDENTITY is the strongest category at 91/100, 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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Test how a set like this one would land in a club, a beach club or a festival.
Get the same breakdown on your own set: transitions, energy arc and measured execution.
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