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ScrapingBuddy
Illustrative football stadium with teal seating and a green pitch
All use cases

TICKET INTELLIGENCE / MANAGED DATA

SeatGeek
ticket data.

Know the offer. Understand the seat.

We collect SeatGeek ticket listings, prices, seat details and quantity options. Get structured data for the events you follow, delivered on an agreed schedule.

Discuss your project Explore data points

THE SIGNAL BEHIND THE LISTING

Turn ticket listings into market intelligence.

A useful price comparison needs more than a number. ScrapingBuddy keeps the seat, quantity and listing context together, so your team can research offers and monitor changes across your target events.

01

Compare asking prices

Research offers by event, section, row and ticket quantity. Identify pricing differences between comparable seats instead of comparing event-wide averages.

02

Follow available inventory

Monitor observed listings and purchase quantities over time. See how the mix of singles, pairs and larger groups changes for your event set.

03

Build pricing intelligence

Bring timestamped offers into your own models, reports and dashboards. Retain source scores as an additional research signal.

WHAT WE COLLECT

The data behind
your next decision.

Choose the SeatGeek data points your workflow needs. We keep related details together and agree the final schema around your use case.

01

Event & listing identity

Connect every offer to its marketplace and event. Collection timestamps help your team follow the same listing across deliveries.

View field names
  • marketplace
  • event_id
  • listing_id
  • cache_time
02

Section, row & seat detail

Place the offer within the venue using section labels, rows and seat numbers where disclosed. Retain original section names alongside normalized labels.

View field names
  • section_name
  • section_name_raw
  • row_name
  • seat_numbers
03

Ticket quantities

Separate the number of tickets in a listing from the quantities a buyer can purchase. Compare singles, pairs and larger groups accurately.

View field names
  • ticket_quantity
  • ticket_quantity_lots
04

Listing prices

Keep displayed and all-in pre-checkout prices distinct, with each amount attached to its listing and collection time.

View field names
  • display_price_pre_checkout
  • all_in_price_pre_checkout
05

Listing notes

Carry offer-specific notes into your dataset, so price and seat analysis can account for the conditions shown with the listing.

View field names
  • listing_notes
06

Source value scores

Keep marketplace value signals alongside each offer for filtering and research, without replacing your own pricing model.

View field names
  • value_score

Field availability depends on the source and agreed collection scope. Need a different schema or additional enrichment?

Share your requirements

BUILT FOR USEFUL COMPARISONS

Compare the offer, not just the number.

Two listings for the same event may represent very different seats and purchase options. We preserve those differences in the data you receive.

Seat context
Section and row stay linked to the price, with exact seats included when the source discloses them.
Purchase options
Total quantity and permitted purchase quantities remain separate fields.
Price stage
Pre-checkout amounts are identified as such, rather than presented as completed transaction totals.

A COLLECTION BUILT AROUND YOUR BRIEF

From event scope
to a maintained feed.

Recurring ticket intelligence needs more than a page response. We scope access, records and quality checks around your research.

  1. 01 / DEFINE

    Start with your events

    Share target events, required fields and how you plan to use the data. We agree a collection scope, refresh schedule and delivery format.

  2. 02 / VALIDATE

    Maintain the collection

    Source-specific access engineering, parsing and schema checks. Monitor missing fields, failures and freshness separately from inventory changes.

  3. 03 / DELIVER

    Fit your data stack

    Review a sample, confirm the schema and connect the delivery to your pipeline. Choose Parquet, CSV, JSON or a scoped API integration.

Researching a few public pages instead?

Our self-service Scraping API collects accessible public content with optional AI analysis. It does not bypass CAPTCHA or login, and does not automatically return this ticket schema.

Explore Scraping API

BEFORE YOU BUILD ON THE DATA

The questions
that affect your model.

Can you follow a changing set of events?

Yes. We scope the collection around your target event set and agree how additions, removals and refresh schedules will work. Event discovery, collection frequency and delivery latency are part of the project brief.

Will every listing include exact seat numbers?

Only when the source makes them available. Section and row information can still support comparisons when exact seats are undisclosed. Unavailable values remain empty rather than being inferred from neighboring listings.

Can source scores be compared across marketplaces?

Not directly. Each marketplace can define its scores differently. We preserve the source value and platform identity so you can use the signal within its context or build a separately validated normalization model.

How do you set refresh frequency and project pricing?

We scope the event set, listing volume, required fields, collection frequency and delivery method together. Checkout detail or additional enrichment can change the collection work. We validate a sample and agree the scope and price before starting a recurring feed.

What happens when the source changes or a collection fails?

Our managed workflow includes source-specific parsing and validation. We agree freshness checks and how failed or incomplete collections are reported, so a collection failure is not mistaken for empty inventory. Monitoring and maintenance responsibilities are defined in the delivery agreement.

Can the data feed connect to our existing pipeline?

We can scope Parquet, CSV or JSON delivery, or a project-specific API integration. Before delivery, we agree identifiers, field types, missing-value handling, currency, price units and timestamp conventions. This managed feed is separate from the self-service Scraping API.

EXTEND YOUR MARKET VIEW

Researching more than one marketplace? We can scope event matching and field normalization as part of your project.

YOUR EVENTS. YOUR DATA REQUIREMENTS.

Build your
SeatGeek
data feed.

Share your target events and required fields. We will review access and scope a sample before agreeing scale and delivery.

  • Platforms and event coverage
  • Fields, currency and collection context
  • Refresh schedule and delivery format
Talk through your project

Up to 5,000 characters.

Projects are accepted individually, subject to feasibility and available capacity. An enquiry does not reserve a solution or confirm delivery. Pricing and terms are agreed directly with our team.

A real person reviews your brief and follows up about scope and delivery.

ScrapingBuddy is an independent data service, not affiliated with or endorsed by SeatGeek. We provide data collection, not ticket sales. Venue artwork is illustrative. Access and delivery commitments are agreed per project.