Skip to content
PyronetsPyronets
Running in production

TickPick data extraction, at full market depth

Every listing on every event, with section, row, quantity, all-in price and TickPick's own value score. This is the marketplace our event-pricing pipeline has run on, every day, without a missed handover.

Collected every day

The figures below are read off the transfer manifest, not estimated.

  • 1.2B+
    Listing records delivered, and still climbing
  • 3M+
    Listings on an ordinary day, across 30,000+ events
  • 0
    Failed transfers since the pipeline went live
All four marketplaces
The problem

The market moves faster than a manual check can follow

A single popular event can carry thousands of active listings, and the cheapest seat in a section changes several times a day as sellers reprice against each other. By the time someone has checked by hand, the number they wrote down is already wrong.

  • Listings appear and disappear within hours, so a weekly snapshot misses most of the market
  • Section and row detail is what determines value, and it is exactly what summary pages leave out
  • Prices with fees folded in and prices without them are not comparable, but both are called the price
  • One event at full depth is thousands of rows, and a season is millions
  • Historical listing data cannot be recovered later; if it was not collected that day, it is gone
Our approach

Full-depth collection, every event, every day

We collect the complete listing table for every event in scope, not a sample and not the top of the page. Each run is validated against the agreed schema before it leaves us, and the manifest tells you exactly what arrived.

All-in pricing changes what you can compare

TickPick shows the price you actually pay, fees included, on the listing itself. That makes it the cleanest reference point in the resale market, and the natural baseline when you are trying to work out what a seat is really worth somewhere else. We keep the displayed figure and the fee breakdown separate in the schema so you can compare either way.

What the pipeline does

TickPick collection, field by field

The parts of TickPick that take real work, and how each is handled.

Every listing, not the cheapest few

Full market depth per event. On a busy day that has meant more than five million listing rows in a single delivery, which is the only way to see how a section actually fills up.

Section, row and seat detail

Section name, row, seat numbers and quantity are captured as separate fields. Two listings at the same price in different sections are not the same listing, and the schema treats them that way.

Value score captured as published

TickPick scores listings on value. We store that score alongside the price rather than recomputing our own, so you can see what the marketplace was telling buyers at that moment.

Listing notes preserved

Mobile transfer, obstructed view, aisle seat, piggyback restrictions. The note field is where the reason for a price gap usually lives, so it is kept verbatim.

Stable listing IDs over time

Listing IDs persist across runs, so you can follow one seat from first appearance to sale and see every reprice in between.

Event, performer and venue tables

Events are delivered as their own table with performer and venue IDs, so you can group by artist, team or building without string matching on names.

What it gets used for

Why teams ask for TickPick data

Pricing a seat before you buy it

Compare an asking price against every comparable seat in the building on the same day, rather than against a single average that hides the spread.

Measuring how inventory sells down

Track the same event daily from on-sale to doors and see which sections clear first, which hold price, and where late supply appears.

Benchmarking against other marketplaces

All-in prices make TickPick the cleanest baseline for cross-marketplace comparison once other sites' fees are reconstructed.

Backtesting a resale strategy

A daily listing history is the only way to test a pricing rule against what the market actually did rather than what you remember it doing.

What arrives

One row per listing, per run

The listing table below is what our running ticket pipeline delivers, joined to an events table on event_id. Fields TickPick does not expose before checkout arrive null rather than estimated, and yours is whatever you sign off on before collection starts.

listings
  • marketplacestring

    Which site the listing came from

  • event_idstring

    Joins to the event table

  • listing_idstring

    Stable per listing, so you can track one seat over time

  • section_namestring

    Section as the site labels it

  • row_namestring

    Row within the section

  • seat_numbersstring

    Specific seats where the listing exposes them

  • ticket_quantityint

    How many seats the listing covers

  • value_scorefloat

    The marketplace's own value rating, where it has one

  • listing_notesstring

    Delivery method, restrictions, obstructed view

  • display_price_pre_checkoutdecimal

    The price shown on the listing page

  • all_in_price_pre_checkoutdecimal

    Display price with fees folded in, where shown up front

  • display_price_checkoutdecimal

    Price carried through to the checkout screen

  • buyer_fee_checkoutdecimal

    Service fee, itemised

  • other_fee_checkoutdecimal

    Delivery and processing charges

  • sales_tax_checkoutdecimal

    Tax, where it is broken out

  • all_in_price_checkoutdecimal

    What the buyer actually pays

  • cache_timetimestamp

    When this observation was taken

The full event table, the delivery manifest and the collection record are on the ticket data overview.

The delivery record

What this pipeline has actually moved

This is a live event-pricing pipeline on TickPick, running continuously. Not a projection, and not a capability estimate. Figures are rounded and kept current rather than quoted to the digit, because the pipeline adds to them every morning. The same infrastructure and the same schema carry the other three marketplaces.

1.2B+
listing records delivered
400+
daily files, one per collection day
14M+
event records across the run
0
failed transfers, start to date
every_delivery.manifest
files_expected   ✓ matched
files_verified   ✓ matched
bytes_verified   ✓ byte for byte
checksums        ✓ all pass
errors           [ ]
Every delivery ships with one of these. If a file arrives a byte short, the manifest says so before you find out the hard way.
Shape of a run
An ordinary day
3M+ listings across 30,000+ events
The busiest day
6M+ listings in a single delivery
NFL season week
60M+ rows over 7 days
World Cup window
5M+ rows over 5 weeks
Super Bowl run-up
1M+ rows over 2 weeks

Sample data is available on request

What is above is a summary. Ask and we will show you the rest directly, on a call or a screen share: the run history, the manifests, and a working sample built from your own target events in the schema you want it in. That sample is yours to keep and to test against.

What you will never be shown is another client's delivered dataset, and that is the same undertaking we make to you about yours.

TickPick questions

Asked before starting a TickPick project

Over 1.2 billion listing records and 14 million event records, across more than 400 daily deliveries, with zero failed transfers. The pipeline is still running, which is why we round the figures rather than quote them to the digit. Ask and we will walk you through the run history and a working sample on a call.

Yes. Sample data is available on request. Tell us the events or the date range you care about and we will build a working sample from your own targets, in the schema you want, then walk you through it live including the fields that come back null and why. It is yours to keep and test against. What you will never be shown is another client's delivered dataset, which is the same undertaking we make to you about yours.

Daily is the schedule we run today. Intraday collection is available where the event set justifies it, and we have run tighter cadences during short windows such as an NFL week or a Super Bowl run-up.

Both, as separate fields. Display price, all-in price, buyer fee, delivery and processing fees, and sales tax each have their own column. Fields the site does not expose before checkout are delivered null rather than estimated.

Yes, and it is usually cheaper than full-market coverage. We have run scoped collections against a single league week, a single tournament and a single event's run-up alongside the daily full-market job.

Send us three TickPick events

Name the events and the fields you need. You get a feasibility read, a proposed schema and a real sample pulled from your own targets, before any commitment.

No retainer required to find out whether your sources are feasible.