Ticketmaster Events Scraper: Search & Extract Event Data Instantly

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What Is Ticketmaster?

Ticketmaster is the world's leading entertainment ticketing platform, hosting millions of events across concerts, sports, theater, and family entertainment. With events updated constantly and search results spanning thousands of listings, manually collecting event data is impractical. The Ticketmaster Events Scraper automates this workflow, extracting structured event information directly from search result pages.

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Overview

The Ticketmaster Events Search Scraper extracts comprehensive event data from Ticketmaster search result pages, converting unstructured web content into clean, queryable records. It is designed for:

• Event aggregators building multi-source event databases
• Data analysts tracking ticket availability and pricing trends
• Researchers studying entertainment market dynamics
• BI teams feeding real-time event data into dashboards

Key strengths include configurable item limits per search URL, flexible date range filtering, automatic handling of failed requests, and capture of 22+ event attributes including availability status and venue information.

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Input Format

The Actor supports two scraping modes — use only one at a time:

1. Scrape by URLs — scrape data directly from a list of Ticketmaster search result URLs.

{
  "urls": [
    "https://www.ticketmaster.com/search?sort=date&startDate=2026-06-09&endDate=2026-06-12"
  ],
  "ignore_url_failures": true,
  "max_items_per_url": 200,
  "proxy": {
      "useApifyProxy": true,
      "apifyProxyGroups": ["RESIDENTIAL"],
      "apifyProxyCountry": "US"
  }
}

2. Scrape by search filters — scrape data using a keyword and additional filters (region, location, date range) instead of providing URLs.

{
  "region": "nz",
  "keyword": "su",
  "location": "751",
  "start_date": "2026-10-24",
  "end_date": "2026-11-19",
  "max_items_per_url": 200,
  "proxy": {
      "useApifyProxy": true,
      "apifyProxyGroups": ["RESIDENTIAL"],
      "apifyProxyCountry": "US"
  }
}

There is also a General settings group that applies to both modes.

1. Scrape by URLs

Use this mode when you already have specific search result URLs. When this mode is used, all options in the "Scrape by search filters" section will be disabled.

Field	Type	Default	Description
urls	array	(required)	Ticketmaster search result page URLs to scrape, with optional filters (date range, genre, location, sort order). You can paste URLs one by one, or use the Bulk edit section to add a prepared list.
ignore_url_failures	boolean	true	If true, the scraper continues running when a URL fails instead of stopping the entire run (stops at the first error if false). Recommended for bulk jobs.

URL examples:

• Basic search: https://www.ticketmaster.com/search?sort=date
• Date range: https://www.ticketmaster.com/search?sort=date&startDate=2026-06-09&endDate=2026-06-12
• Keyword: https://www.ticketmaster.com/search?q=taylor+swift&sort=date

Tip: Use precise date ranges and keywords to reduce result volume and scrape time.

2. Scrape by search filters

Use this mode when you want to search using a keyword and additional filter attributes instead of scraping by URLs. If you use this mode, leave the urls field above empty.

Field	Type	Default	Description
keyword	string	—	The keyword to search for.
region	string (country code, e.g. us, uk, de, au...)	—	The country/marketplace to search in.
location	string	—	The location to search for. Check the valid value via the region parameter in a Ticketmaster URL, e.g. https://www.ticketmaster.co.nz/search?q=su&region=751 → location=751.
start_date	string (YYYY-MM-DD)	—	Absolute start date of the search range.
end_date	string (YYYY-MM-DD)	—	Absolute end date of the search range.

3. General settings

Applies to both scraping modes above.

Field	Type	Default	Description
max_items_per_url	integer	20	The maximum number of events to extract per URL/search (e.g. 200). Increase for broader datasets.
proxy	object	{ "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"], "apifyProxyCountry": "US" }	Proxy configuration used by the scraper. Residential proxies are recommended for reliable access.

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Output Format

Sample output

{
  "title": "NZTrio: Full Season Pass",
  "id": "2400636ACBFC4845",
  "discovery_id": "1Ae8ZbUGkl5T7-A",
  "dates": {
    "date_display": "showDate",
    "start_date": "2026-05-10T00:00:00+12:00",
    "end_date": "2026-11-08T00:00:00+13:00",
    "onsale_date": "2025-11-16T20:00:00Z",
    "span_multiple_days": false
  },
  "url": "https://www.ticketmaster.co.nz/nztrio-full-season-pass-auckland-10-05-2026/event/2400636ACBFC4845",
  "partner_event": false,
  "is_partner": false,
  "show_tm_button": true,
  "venue": {
    "city": "Auckland",
    "name": "Concert Chamber, Auckland Town Hall",
    "country": "NZ",
    "country_code": "NZ",
    "country_name": "New Zealand",
    "state": "NZ",
    "url": "https://www.ticketmaster.co.nz/concert-chamber-auckland-town-hall-tickets-auckland/venue/295211",
    "image_url": "https://s1.ticketm.net/dbimages/20148v.jpg",
    "latitude": -36.8507309,
    "longitude": 174.7645874,
    "address_line_one": "Queen Street",
    "code": "1010"
  },
  "time_zone": "Pacific/Auckland",
  "cancelled": false,
  "postponed": false,
  "rescheduled": false,
  "tba": false,
  "local": true,
  "same_region": true,
  "sold_out": false,
  "limited_availability": false,
  "event_change_status": "none",
  "virtual": false,
  "artists": [
    {
      "name": "NZTrio",
      "url": "https://www.ticketmaster.co.nz/nztrio-tickets/artist/1089622",
      "image_urls": {
        "a_r_t_i_s_t__p_a_g_e_3_2": "https://s1.ticketm.net/dam/a/c60/8a2474e0-835b-4b56-85db-91a60d9b8c60_ARTIST_PAGE_3_2.jpg",
        "r_e_t_i_n_a__p_o_r_t_r_a_i_t_16_9": "https://s1.ticketm.net/dam/a/c60/8a2474e0-835b-4b56-85db-91a60d9b8c60_RETINA_PORTRAIT_16_9.jpg"
      }
    }
  ],
  "major_category": {
    "id": "KZFzniwnSyZfZ7v7na",
    "canonical_urls": {},
    "major": true
  },
  "from_url": "https://www.ticketmaster.co.nz/search?q=su&region=751&startDate=2026-10-24&endDate=2026-11-19"
}

Each scraped event returns a structured record with 22 fields:

Event Identification

Field	Meaning
ID	Unique Ticketmaster event identifier
Discovery ID	Alternative discovery API identifier
Title	Event name as displayed in search results
URL	Direct link to the event detail page
Major Category	Primary event category (e.g., Music, Sports, Theater)

Date & Time Information

Field	Meaning
Dates	Event date(s) and time(s) in ISO format
Time Zone	Local time zone of the event venue

Venue & Location

Field	Meaning
Venue	Venue name and location details
Local	Boolean indicating if event is in user's local region
Same Region	Boolean indicating if event is in the same region as search origin

Event Status Flags

Field	Meaning
Cancelled	Whether the event has been cancelled
Postponed	Whether the event has been postponed
Rescheduled	Whether the event has been rescheduled to a new date
TBA	Whether date/time is "To Be Announced"
Event Change Status	Summary of any status changes (cancelled, postponed, rescheduled)

Availability & Ticketing

Field	Meaning
Sold Out	Whether all tickets have been sold
Limited Availability	Whether only a few tickets remain
Virtual	Whether the event is virtual/online or in-person
Show TM Button	Whether Ticketmaster "Get Tickets" button displays

Event Details

Field	Meaning
Artists	Array of performer/artist names
Partner Event	Human-readable partner event indicator
Is Partner	Boolean indicating if event is listed by a partner

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How to Use

1. Build a search URL — Visit Ticketmaster.com/search and refine by date, keyword, or category. Copy the full URL from the address bar.

2. Prepare the input — Paste your Ticketmaster search URL(s) into the urls array. Set max_items_per_url to control output volume (recommended: 50–200 for balanced speed/completeness).

3. Configure error handling — Set ignore_url_failures: true if running multiple URLs to prevent one failed request from stopping the entire run.

4. Run the scraper — Start the actor and monitor execution. Large max_items_per_url values may take longer due to pagination.

5. Download results — Export data as JSON, CSV, or Excel for further analysis or integration.

Best practices:

• Use date range filters to narrow results (reduces scrape time significantly)
• Set a reasonable max_items_per_url to avoid unnecessary overhead
• Test with a single URL before running bulk operations
• Monitor the Sold Out and Limited Availability flags for real-time ticket dynamics

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Use Cases & Business Value

• Event aggregators: Build comprehensive multi-source event listings combining Ticketmaster with other platforms
• Market intelligence: Track event supply, cancellations, and rescheduling patterns by region or category
• Availability monitoring: Alert users when tickets become available for tracked artists or venues
• Pricing analysis: Combine event data with external pricing sources to study demand trends
• Travel planning: Aggregate events with hotel and flight data for event-tourism packages

The Ticketmaster Events Scraper transforms raw search results into analytics-ready datasets, enabling data-driven decision-making across ticketing, marketing, and business intelligence teams.

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Conclusion

The Ticketmaster Events Search Scraper is the fastest way to extract structured event data from Ticketmaster at scale. Whether you're building an aggregator, monitoring availability, or conducting market research, this tool eliminates manual data collection and delivers clean, actionable records. Start scraping today and unlock insights from millions of live events.