# Ticketmaster Ticket Listings Scraper (`stealth_mode/ticketmaster-ticket-listings-scraper`) Actor

Scrape Ticketmaster ticket listings across all domains to extract seat details, pricing, sections, and availability. Perfect for event analytics, price monitoring, and secondary market research. Get 16 fields per ticket including ID, section, row, price, and quality attributes.

- **URL**: https://apify.com/stealth_mode/ticketmaster-ticket-listings-scraper.md
- **Developed by:** [Stealth mode](https://apify.com/stealth_mode) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.50 / 1,000 results

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Ticketmaster Ticket Listings Scraper: Extract Event Ticket Data Instantly

***

### Understanding Ticketmaster

Ticketmaster is the world's largest ticket marketplace, hosting millions of listings for concerts, sports events, theater, and live entertainment across dozens of international domains (ticketmaster.co.nz, ticketmaster.com, ticketmaster.co.uk, etc.). Each event page displays hundreds or thousands of individual ticket offerings with varying prices, sections, and availability. Manually tracking ticket data is impractical—the **Ticketmaster Ticket Listings Scraper** automates collection of seat-level ticket information, enabling you to analyze pricing patterns, inventory, and market trends at scale.

***

### Overview

The **Ticketmaster Ticket Listings Scraper** extracts granular ticket data from Ticketmaster event pages, converting seat maps and pricing tables into clean, structured records. It is designed for:

- **Ticket resellers** monitoring price trends and inventory across events
- **Event promoters** analyzing ticket distribution and demand
- **Market researchers** studying ticketing patterns and secondary market dynamics
- **Data analysts** building datasets for pricing models
- **Travel & entertainment aggregators** enriching event databases

Key advantages include multi-domain support (all Ticketmaster regional sites), configurable item limits, proxy integration to avoid detection, and error tolerance via `ignore_url_failures`.

***

### Input Format

The scraper accepts a JSON configuration object:

```json
{
    "urls": [
        "https://www.ticketmaster.co.nz/auckland-fc-v-melbourne-victory-fc-auckland-21-11-2026/event/24006514B68B3A7A"
    ],
    "ignore_url_failures": true,
    "max_items_per_url": 50,
    "proxy": {
        "useApifyProxy": true,
        "apifyProxyGroups": ["RESIDENTIAL"],
        "apifyProxyCountry": "US"
    }
}
```

| Field | Description | Example |
|---|---|---|
| `urls` | Array of Ticketmaster event ticket listing page URLs | `https://www.ticketmaster.co.nz/event/...` |
| `max_items_per_url` | Maximum tickets to extract per event (1–1000+) | `50` |
| `ignore_url_failures` | If `true`, continue scraping even if some URLs fail | `true` |
| `proxy.useApifyProxy` | Enable proxy rotation to avoid IP blocking | `true` |
| `proxy.apifyProxyGroups` | Proxy type; `RESIDENTIAL` recommended for Ticketmaster | `["RESIDENTIAL"]` |
| `proxy.apifyProxyCountry` | Country code matching the Ticketmaster domain (e.g., `NZ` for .co.nz) | `"US"` or `"NZ"` |

> **Best Practice:** Match `apifyProxyCountry` to the Ticketmaster domain you're scraping (e.g., use `NZ` for ticketmaster.co.nz, `GB` for ticketmaster.co.uk) to minimize detection and improve success rates.

***

### Output Format

**Example output record:**

```json
{
  "id": "-327313334",
  "type": "seat",
  "section": "1",
  "row": "A",
  "seat_from": "7",
  "seat_to": "8",
  "name": "Child - Away Supporters",
  "original_price": 21.41,
  "description": "West Stand",
  "area_name": "WEST",
  "place_description_id": "IE5DCMBMG4",
  "has_special_description": false,
  "offer_ids": [
    "GJ6DIQJQGAYDAMBSPQ2TQ",
    "GJ6DIQJQGAYDAMBTPQ2TQ",
    "GJ6DIQJQGAYDAMBUPQ2TQ"
  ],
  "snapshot_image_url": "image?systemId=HOST&sectionNames=1&placeId=GE5ECORY",
  "quality": 0.55625,
  "attributes": [],
  "from_url": "https://www.ticketmaster.co.nz/auckland-fc-v-melbourne-victory-fc-auckland-21-11-2026/event/24006514B68B3A7A"
}
```

Each scraped ticket returns a detailed record with 16 fields covering seat location, pricing, and attributes:

#### Ticket Identification

| Field | Meaning |
|---|---|
| `ID` | Unique identifier for this ticket listing within the event |
| `Type` | Ticket category (e.g., standard, premium, accessible, VIP) |

#### Seat Location & Section

| Field | Meaning |
|---|---|
| `Section` | Section or area name (e.g., "Upper Level North", "Field Floor") |
| `Row` | Row identifier within the section (e.g., "A", "42", "AA") |
| `Seat From` | Starting seat number or identifier (e.g., "101", "1") |
| `Seat To` | Ending seat number if the listing is a range (e.g., "105" for seats 101–105) |
| `Name` | Human-readable seat name or label (e.g., "Seat 101, Row A") |

#### Pricing & Financial Data

| Field | Meaning |
|---|---|
| `Original Price` | Face value or base ticket price before fees (displayed to end user) |

#### Location & Venue Mapping

| Field | Meaning |
|---|---|
| `Area Name` | Descriptive area name for the seat location (e.g., "Lower Bowl", "Balcony") |
| `Place Description ID` | Internal Ticketmaster identifier linking to the seating map definition |

#### Quality & Attributes

| Field | Meaning |
|---|---|
| `Quality` | Seat quality rating or category (e.g., "standard", "premium", "restricted view") |
| `Has Special Description` | Boolean flag; `true` if the ticket has special notes (e.g., obstructed view, accessible, wheelchair space) |
| `Description` | Text field containing special notes or restrictions (e.g., "Wheelchair Accessible", "Limited Sightlines") |

#### Images & Media

| Field | Meaning |
|---|---|
| `Snapshot Image URL` | URL to a preview image of the seating view from this section/seat |

#### Metadata & Offers

| Field | Meaning |
|---|---|
| `Offer IDs` | Array of promotional offer IDs applicable to this ticket (e.g., group discounts, presale codes) |
| `Attributes` | Additional attributes as key-value pairs (e.g., `"accessible": true`, `"resale_eligible": false`) |

***

### How to Use

1. **Find event URLs** — Navigate to Ticketmaster (any regional domain) and open an event ticket listing page. Copy the full event URL.
2. **Prepare input** — Add URLs to the `urls` array. Adjust `max_items_per_url` based on desired sample size (e.g., `50` for quick analysis, `500+` for comprehensive mapping).
3. **Set proxy country** — Match the proxy country to the Ticketmaster domain (e.g., `NZ` for .co.nz).
4. **Run the scraper** — Execute the actor and monitor the progress log.
5. **Export & analyze** — Download results as JSON or CSV for spreadsheet analysis, price tracking, or database integration.

**Common scenarios:**

- **Single event analysis:** Scrape one event to map seating and price distribution.
- **Batch tracking:** Provide 5–10 event URLs to monitor availability across multiple shows.
- **Resale research:** Extract pricing data to understand secondary market premiums.

***

### Use Cases & Business Value

- **Price monitoring:** Track ticket availability and pricing over time as inventory depletes
- **Seating analysis:** Build heatmaps showing which sections sell fastest and at what premiums
- **Event planning:** Predict demand and optimize pricing strategies based on comparable events
- **Data enrichment:** Merge Ticketmaster data with your CRM or analytics platform
- **Competitive intelligence:** Monitor competitor events and pricing positioning

By automating ticket data collection, the Ticketmaster Scraper transforms static web pages into actionable intelligence, saving hours of manual work and enabling data-driven decisions in the live events industry.

***

### Conclusion

The **Ticketmaster Ticket Listings Scraper** provides unmatched access to seat-level ticket data across all Ticketmaster domains. With detailed output spanning location, pricing, quality, and availability attributes, it is the fastest way to extract and analyze large-scale ticket inventory. Whether you're a reseller, researcher, or event professional, this scraper unlocks the insights you need to succeed in the competitive ticketing market.

# Actor input Schema

## `urls` (type: `array`):

Add the URLs of the ticket listings urls you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list.

## `ignore_url_failures` (type: `boolean`):

If true, the scraper will continue running even if some URLs fail to be scraped.

## `max_items_per_url` (type: `integer`):

The maximum number of items to scrape per URL.

## `proxy` (type: `object`):

Select proxies to be used by your scraper.

## Actor input object example

```json
{
  "urls": [
    "https://www.ticketmaster.co.nz/auckland-fc-v-melbourne-victory-fc-auckland-21-11-2026/event/24006514B68B3A7A"
  ],
  "ignore_url_failures": true,
  "max_items_per_url": 20,
  "proxy": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ],
    "apifyProxyCountry": "NL"
  }
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "urls": [
        "https://www.ticketmaster.co.nz/auckland-fc-v-melbourne-victory-fc-auckland-21-11-2026/event/24006514B68B3A7A"
    ],
    "ignore_url_failures": true,
    "max_items_per_url": 20,
    "proxy": {
        "useApifyProxy": true,
        "apifyProxyGroups": [
            "RESIDENTIAL"
        ],
        "apifyProxyCountry": "NL"
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("stealth_mode/ticketmaster-ticket-listings-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "urls": ["https://www.ticketmaster.co.nz/auckland-fc-v-melbourne-victory-fc-auckland-21-11-2026/event/24006514B68B3A7A"],
    "ignore_url_failures": True,
    "max_items_per_url": 20,
    "proxy": {
        "useApifyProxy": True,
        "apifyProxyGroups": ["RESIDENTIAL"],
        "apifyProxyCountry": "NL",
    },
}

# Run the Actor and wait for it to finish
run = client.actor("stealth_mode/ticketmaster-ticket-listings-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "urls": [
    "https://www.ticketmaster.co.nz/auckland-fc-v-melbourne-victory-fc-auckland-21-11-2026/event/24006514B68B3A7A"
  ],
  "ignore_url_failures": true,
  "max_items_per_url": 20,
  "proxy": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ],
    "apifyProxyCountry": "NL"
  }
}' |
apify call stealth_mode/ticketmaster-ticket-listings-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,stealth_mode/ticketmaster-ticket-listings-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/NBYibo7MfejHIfIbN/builds/qPlQTxid8yqn2oFNs/openapi.json