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Ticketmaster On-Sale & Presale Radar

The only Ticketmaster actor that ships a stateful change-feed — not a one-shot dump. The Radar tracks three data types that zero incumbents ship, rebuilt every run by diffing the current payload against the previous run's state stored in Apify KV.

What Makes This Actor Different

Every other Ticketmaster actor on the Apify Store is a one-shot metadata dump. They scrape and return the same static fields each run. The Radar is designed for scheduled monitoring — you set it to run hourly or daily, and it only emits events that actually changed. No noise, no duplicate data, no manual diffing.

Three Confirmed Data Types

1. Presale & On-Sale Calendar

The actor extracts presaleDates[] from Ticketmaster's open search payload — named windows with ISO start and end times. For example, a Taylor Swift show might return:

• "Amex Presale Tickets®" — 2025-01-07T10:00:00Z to 2025-01-09T23:59:00Z
• "Onsale To General Public" — 2025-01-10T10:00:00Z onwards
• "Resale" — separate resale window

Live-verified on 20/20 Olivia Rodrigo events in the pass-3 probe (2026-06-04). Zero incumbents ship this data. Resellers and event analysts plan their purchase timing around exactly this data.

2. Availability Change-Detection

Re-polls /search on every scheduled run and diffs:

• soldOut — event went sold out
• limitedAvailability — limited tickets remaining
• ticketingStatus — changes between PRESALE / ON_SALE / CANCELLED
• eventChangeStatus — event rescheduled, cancelled, postponed

Emits only the events where something changed (in delta mode). The changed_fields array in every record tells you exactly what flipped. The change_type field gives a single human-readable label: sold_out_change, availability_change, status_change, presale_calendar_change, price_change, or new_event.

3. Price Delta (Optional)

When you supply a free Ticketmaster Discovery API key (available at developer.ticketmaster.com), the actor enriches each event with priceRanges (min/max, currency) and tracks price changes between runs. Without the key, the actor still extracts price ranges that appear in the search payload — coverage is lower but setup is zero.

How to Use

Basic presale monitor (no API key required)

{
"queries":["Taylor Swift","Coldplay"],
"maxEventsPerQuery":100,
"stateMode":"delta"
}

Schedule this run to repeat every 6–12 hours. Only new and changed events will appear in the dataset.

Presale-only filter

{
"queries":["Beyonce","Drake"],
"stateMode":"presale",
"maxEventsPerQuery":200
}

Returns only events that have presale calendar data — ideal for resellers who want to plan presale purchases.

Full export with price tracking

{
"queries":["EDC Las Vegas 2025"],
"stateMode":"full",
"discoveryApiKey":"YOUR_FREE_KEY_HERE",
"maxEventsPerQuery":400
}

Output Fields

Input Parameters

Pricing — Pay Per Changed Event

$5.00 per 1,000 records (PPE — pay per result). In delta mode you only pay for events that actually changed or are new — not for scanning 100 events to find 3 changed ones. The stateful design means a reseller monitoring 50 artists pays almost nothing on quiet days and only pays when presales open or availability shifts.

Access Approach

Uses the robots-permitted HTML /search path only. Confirmed 200 from Apify datacenter IPs with 8× rapid sequential requests, no advanced-protection challenge triggered (pass-3 live probe, 2026-06-04). Apify RESIDENTIAL proxy is recommended for high-frequency scheduled runs to avoid shared-DC-IP rate-limits on Fastly CDN.

The protection-walled ISMDS tier (per-seat live inventory) is intentionally excluded — it is robots-Disallowed and requires a browser-minted access token. This actor does not promise per-seat data.

Use with AI Agents (MCP)

Callable as a tool from AI agents via Apify MCP:

{
"mcpServers":{
"apify":{
"command":"npx",
"args":[
"mcp-remote",
"https://mcp.apify.com/?tools=bovi/ticketmaster-radar",
"--header",
"Authorization: Bearer <YOUR_APIFY_TOKEN>"
]
}
}
}

Not affiliated with Ticketmaster or Live Nation. Uses the robots-permitted HTML search surface.

Integrations

Built for ticket resellers and event-industry analysts tracking presale windows, on-sale dates, and price deltas over time — the JSON/dataset output drops into the tools you already run, no glue code:

• n8n / Make / Zapier — trigger a run or pipe every new dataset item into 500+ apps (Google Sheets, Airtable, Slack, HubSpot, your database) with no code: n8n, Make, Zapier.
• Webhooks — fire your own endpoint the moment a run finishes, to push results straight into your pipeline (docs).
• MCP server — expose this actor as a tool to Claude, Cursor, or any MCP client so an AI agent can pull this data mid-conversation (guide).
• API & SDKs — fetch the dataset as JSON, CSV, or Excel through the Apify REST API or the Python / JS SDKs.

See all Apify integrations.

More scrapers from our toolkit

Building a data pipeline? These actors pair well with this one — each runs on your own Apify account with the same pay-per-result pricing, no subscription:

• Sofascore Live Events

Chain any of them together from the Integrations tab (the Run succeeded trigger) to build a multi-step workflow — one actor's output feeds the next.