SHADOWS · LAB REPORT · SAMPLE
CONFIDENTIAL
Shadows Lab · Launch Simulation · Sample deliverable

The night,
simulated.

Hard-techno festival · major LATAM metro · arena-scale venue · 2-night weekend
Sample report · every figure is from a real blind simulation · client anonymized
01

The ask

Can this hard-techno flagship fill the room at the planned pass price — and who actually walks through the door: the local scene, domestic travellers, or an international crowd?

02

The brief

City / venueMajor LATAM metro · arena-scale venue · ~10–12,000 capacity
DateTwo-night weekend · autumn season
Ticket price2-day pass · ~USD 126–150 (early → final tier) · backstage tier above
ConceptHard techno / schranz / hardstyle flagship · 2 days · international headliners over a strong local contingent
Past nights read1 prior edition used as the trajectory anchor
03

The projection — the night

Projected attendance · unique pass-holders
9,060
Range 8,071 – 10,049
Confidence HIGH
Where the night lands (0 – 12,000 room)
03k6k9k12k
04

Who shows up

Local / regional
The local hard-techno scene — the grounded synthetic crowd
85%
Domestic travel
From across the country — modelled on lineup reach + festival history
12%
International
Destination travellers — modelled on lineup geo-reach
3%
This is the read only Shadows can give. 85% of the room is the local scene — so the night lives or dies on how the local hard-techno crowd feels about this bill, not on the international headliners. The engine reached that composition from real local scene data, then corrected an early over-weighting of the international pool.
05

The door

Projected gross · gate
≈ USD 1.36M
mid × 2-day pass
Ceiling
10,049
realistic top of the range
Room used
~76%
of a 12k / day room
06

Sell-through curve

How fast the room fills — announce to door
Module preview — illustrative
Announce Preventa waves Door
Front-loaded: a scene-defining brand with a dedicated following clears most of the room on announce and the early preventa tramos, then grinds toward the date. The curve shape is illustrative in this sample — sell-through timing is a module that calibrates on real preventa pace.
07

Risks · what to watch

  • R1
    Thin trajectory dataOnly one prior edition to anchor against — treat the range as wide until a second known night is scored.
  • R2
    Price ceiling on the casual poolAt the final tier the committed scene converts; students and casual ravers are priced out. That tier is where the curve flattens.
  • R3
    Marketing reach carries the last 20%The core scene comes regardless; the domestic and casual pools only show if the reach lands. Turnout reflects reach, not just latent demand.
08

After the night

Projected vs. actual — the credibility flywheel

The engine ran blind. Then the night happened.

This simulation was produced without knowing the outcome. Here is how it held up.

MetricProjectedActualError
Attendance (mid)9,060~10,0009.4%
In range?8,071 – 10,049~10,000✓ inside
The blind projection landed inside the range, within 9.4% of the real turnout — and the composition read (a local-scene night, not an international one) matched the reality of a locally-rooted festival. Every night that runs through the Lab sharpens the next projection.
09

The recommendation

Book for the scene, not the headliners. The room is 85% local — protect the local contingent, hold the final tier as long as the preventa pace allows, and put marketing spend against the domestic pool, which is the only elastic part of the night.