Jamie Jones — Hot Robot Radio 248
Tech House · 58 min · analysed 19 Aug 2026
About this tech house set
Hot Robot Radio 248 is a tech house DJ set by Jamie Jones, running 58 min. It was measured by the SOONOS multi-agent engine and scores 68/100 overall — developing.
The engine files this performance as “Promising”.
This DJ understands that the end of a set is about both physical exhaustion and emotional resolution.
How the score breaks down
SOONOS scores this set across 5 weighted categories. The strongest is IDENTITY at 84/100; 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 25 points, moving between 40 and 90 on the SOONOS energy scale — a wide dynamic range across the set.
5 transitions were detected and scored individually.
Beat-grid measurement (DSP) reports 2431.8 grid breaks per hour, with a median beat offset of 202 ms.
Full SOONOS analysis
This DJ understands that the end of a set is about both physical exhaustion and emotional resolution.
The 8 dimensions
Score breakdown
TECHNIQUE
How well did you execute?
25%55
TECHNIQUE
How well did you execute?
STORYTELLING
Did the mix go somewhere?
25%82
STORYTELLING
Did the mix go somewhere?
ENERGY
Did you control the room?
20%78
ENERGY
Did you control the room?
SURPRISE
Did you remain unpredictable?
15%74
SURPRISE
Did you remain unpredictable?
IDENTITY
Did the mix sound like you?
15%84
IDENTITY
Did the mix sound like you?
Final score capped by measured execution (-) — weighted average was 73.
Energy arc
Transitions analysed (5)
Long EQ blend with high-frequency priority
Excellent transparency; the new track's hats emerge naturally.
Bass swap on phrase boundary
Solid technical execution, maintaining the energy floor.
Long EQ blend with low-end swap
Flawless execution, the tracks merge into a single rhythmic entity.
Long EQ blend with low-end swap
Very smooth transition, the incoming track's percussion layers perfectly over the outgoing groove.
Mid-frequency focused blend
Clean transition focusing on the rhythmic elements, maintaining the energy level perfectly.
Technical subscores
88
EQ balance
92
Beat alignment
84
Energy control
92
Tempo stability
87
Loudness control
87
Musical coherence
85
Harmonic compatibility
89
Transition cleanliness
Measured (DSP)
201.5 ms
Beat-grid drift (median)
203.4 ms
Drift p95
3,471
Boundaries detected
104
Hard cuts / h
11
Clipping events
261
Level jumps
Measurement confidence 100% · analysed on the full audio.
Recurring patterns
Long static loops (5×)
Sections sitting on the same loop without layering, EQ moves or tension shifts (17:00, 30:00, 35:00, 43:00, 48:30). Long loops kill dancefloor momentum.
Timeline
- 18:40Groove Lock
- 25:15Groove Lock
Coaching notes
- Introduce more melodic elements to create emotional peaks.
- Vary the energy arc with more pronounced breakdowns.
- Experiment with more creative transition techniques like stem layering.
- Incorporate more mid-set energy resets to make the final peak feel even more impactful.
- Experiment with more complex layering during transitions to further define your artistic signature.
- Use atmospheric elements more aggressively in the closing phase to enhance the emotional payoff.
Curious how your own set scores?
Questions about this analysis
- What score does Jamie Jones's Hot Robot Radio 248 get?
- Hot Robot Radio 248 scores 68/100 in the SOONOS Mix Database (developing), based on audio measurement plus multi-agent listening.
- How long is Hot Robot Radio 248?
- The analysed recording runs 58 min.
- Which part of the mix scores best?
- IDENTITY is the strongest category at 84/100, 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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