Joel Mull — Smoke Machine Podcast 130 Joel Mull
Peak Techno · 2h 07m · 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, Joel Mull.
In short
Smoke Machine Podcast 130 Joel Mull by Joel Mull scores 85/100 in the SOONOS analysis (festival ready). The strongest dimension is IDENTITY (93/100) and the weakest is SURPRISE (83/100).
Joel Mull proves that the most powerful transitions are the ones you never hear happening.
Key takeaways
What worked
- Technical transparency in transitions.
- Exceptional groove continuity.
- Mature pacing and restraint.
- Technical transparency in mixing.
What weakened the set
- Long static loops (6×) — Sections sitting on the same loop without layering, EQ moves or tension shifts (9:00, 14:30, 20:00, 25:00, 31:00, 46:00). Long loops kill dancefloor momentum.
What to try next
- Experiment with 'vacuum' filter drops to create artificial tension.
- Layer in more organic field recordings to contrast the industrial tones.
- Maintain the current blend lengths; they are a significant technical strength.
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 masterfully executed transition that brings the first rhythmic element into the mix without breaking the atmospheric spell.
Perfectly executed transition; the two tracks become one for over 64 bars.
Smooth transition focusing on the mid-range energy shift.
Perfectly executed handover of the sub-frequencies, maintaining the hypnotic drive.
Seamless integration of new rhythmic elements without disrupting the established groove.
About this peak techno set
Smoke Machine Podcast 130 Joel Mull is a peak techno DJ set by Joel Mull, running 2h 07m. It was measured by the SOONOS multi-agent engine and scores 85/100 overall — festival ready.
The engine files this performance as “Promising”.
Joel Mull proves that the most powerful transitions are the ones you never hear happening.
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 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 38 points, moving between 20 and 88 on the SOONOS energy scale — a wide dynamic range across the set.
5 transitions were detected and scored individually.
Beat-grid measurement (DSP) reports 1041.1 grid breaks per hour, with a median beat offset of 26 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
Joel Mull proves that the most powerful transitions are the ones you never hear happening.
The 8 dimensions
Not available — the 8-dimension profile was not measured for this set.
Score breakdown
TECHNIQUE
How well did you execute?
25%85
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%86
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%93
IDENTITY
Did the mix sound like you?
Energy arc
Transitions analysed (5)
Long EQ blend with low-end handover
A masterfully executed transition that brings the first rhythmic element into the mix without breaking the atmospheric spell.
Long EQ blend with sub-bass handover
Perfectly executed transition; the two tracks become one for over 64 bars.
Textural layering and high-pass fade
Smooth transition focusing on the mid-range energy shift.
Long EQ blend with low-end swap
Perfectly executed handover of the sub-frequencies, maintaining the hypnotic drive.
32-bar percussive layering
Seamless integration of new rhythmic elements without disrupting the established groove.
Technical subscores
90
EQ balance
95
Beat alignment
89
Energy control
94
Tempo stability
89
Loudness control
92
Musical coherence
89
Harmonic compatibility
92
Transition cleanliness
Measured (DSP)
26 ms
Beat-grid drift (median)
Typical gap between the two tracks' beats while they play together. Lower is tighter.
203 ms
Drift p95
Worst-case drift: 95% of the set stays tighter than this value.
7,605
Boundaries detected
Points where the audio changes track or section.
25
Hard cuts / h
Abrupt track changes per hour, with no blend between the two records.
61
Clipping events
Moments where the recording hits the ceiling and distorts.
336
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 (9:00, 14:30, 20:00, 25:00, 31:00, 46:00). Long loops kill dancefloor momentum.
What SOONOS heard
- Technical transparency in transitions.
- Exceptional groove continuity.
- Mature pacing and restraint.
- Technical transparency in mixing.
- Exceptional groove continuity.
- Professional restraint and pacing.
Timeline
- 15:45Groove Lock Mastery
- 21:20Atmospheric Peak
- 27:45Groove Lock Peak
Coaching notes
- Experiment with 'vacuum' filter drops to create artificial tension.
- Layer in more organic field recordings to contrast the industrial tones.
- Maintain the current blend lengths; they are a significant technical strength.
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 Joel Mull's Smoke Machine Podcast 130 Joel Mull get?
- Smoke Machine Podcast 130 Joel Mull scores 85/100 in the SOONOS Mix Database (festival ready), based on audio measurement plus multi-agent listening.
- How long is Smoke Machine Podcast 130 Joel Mull?
- The analysed recording runs 2h 07m.
- Which part of the mix scores best?
- IDENTITY is the strongest category at 93/100, 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.
More Joel Mull sets analysed
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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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