Custom scraper

Sports Direct Scraper

We do not have a dedicated Sports Direct data API. What we do have is an AI scraper that reads a sportsdirect.com page you point it at, turns it into the columns you asked for and hands them back by REST, CSV or Excel — on a schedule, priced per page.

  • sportsdirect.com
Three stages of a Sports Direct run: paste a sportsdirect.com URL billed on the render plus residential tier at EUR 3.75 per 1,000 pages; declare columns such as brand and product_title; and the 12 columns it returns.

How to scrape Sports Direct

Sports Direct publishes no read API for its catalogue. There is no key to apply for and no endpoint to call, which is why the page is the interface. Sports Direct's model is a permanent discount against a stated RRP, so the RRP is the marketing and the sale price is the price. The way to get the data is to read the page the way a customer sees it: point the AI scraper at a sportsdirect.com URL, declare the columns you want in plain English, and schedule it. Sport and outdoor ranges are seasonal and size-run driven, so the markdown calendar and which sizes survive it carry more information than the shelf price.

What the AI scraper does with a sportsdirect.com link

The same three steps as any other page you point it at. Nothing about Sports Direct is pre-built, which is exactly why it works on pages nobody wrote a connector for.

  1. Paste the link

    Give it a sportsdirect.com product or listing URL. Market, currency and assortment all come from the page itself, so there is no region setting to get wrong — the URL decides.

  2. Declare the columns

    Name each field, give it a type and write a line telling the AI what to look for. “brand” and “product_title” are the two most people start with. The schema is yours and you can change it between runs.

  3. Schedule it and collect

    Run it hourly, daily or on demand. Every run returns the same columns in the same order with a timestamp on each row, so the history builds itself.

Set it up once. The data keeps coming.

Save your search once and it runs by itself. Every run lands in your own Scrapewise database, and you pick how to read it.

  1. Set it up once

    Add your ASINs, keywords, places or apps to a scraper in the web app. New accounts get 5 free requests.

  2. Runs on your schedule

    Pick daily, weekly on the days you choose, every few days, or the first or last day of the month. Scheduled runs start at night, European time. Need it more often? Start runs from your own code.

  3. Saved in your database

    Each run adds dated rows, so this week sits next to last week. Rows are kept for 90 days.

  4. Use it your way

    Open the table in the web app and download the latest run as an Excel file. Ask your own AI assistant about it. Or pull the rows into your code with an API key.

Ask your AI assistant about your own data

Connect Claude Desktop or Claude Code with a read-only key. The assistant reads the rows you've already collected, at no extra cost on Scrapewise. With a full-access key it can start a run for you too.

  • Which of my ASINs lost the Buy Box this week?
  • Which competitor cut prices the most since Monday?
  • Show the keywords where I dropped out of the top 10.

What you send and what you get

You send a link and a column list. Everything else — market, currency, which products are on the page — comes from the page, so there is nothing to configure twice.

You give
  • Link to a Sports Direct pagerequired

    Open the product or category page in your browser and copy the address. Any Sports Direct country domain works the same way.

    https://www.sportsdirect.com/
  • Your column listrequired

    Field name, type and one line of plain English per column. Written once, reused on every run.

    brand, product_title, sku, colour
  • How often it runsoptional

    Hourly, daily, weekly or on demand through the API. Daily is what most price monitoring uses.

    Daily at 06:00 UTC
You get

One row per product on the page, 7 columns each

  • product_title
  • price
  • currency
  • availability
  • brand
  • sku
  • source_url

REST API, CSV or Excel. The column set stays the same between runs, so downstream jobs do not re-map fields.

What a run on Sports Direct actually returned

This is real output, not a mock-up. 4 rows, collected on 3 October 2026 from live sportsdirect.com product pages through our own engine, the same way one of your runs would. Prices move, so treat the numbers as a sample of shape rather than a current price list.

All 7 columns

  • product_title
  • price
  • currency
  • availability
  • brand
  • sku
  • source_url

4 sample rows, all 7 columns seen across sample calls.

4 sample rows, all 7 columns seen across sample calls.
product_titleproduct_titleProduct title as the retailer writes itpricepricePrice the page is charging todaycurrencycurrencyCurrency the page quotedavailabilityavailabilityStock state the page publishedbrandbrandBrand as the retailer labels itskuskuThe retailer's own product codesource_urlsource_urlThe exact page this row was read from
New Balance NB 408v1 Children32.99GBPInStockNew Balance021176https://www.sportsdirect.com/new-balance-nb-408v1-children-021176
Nike Victori One Mens Slides26GBPInStockNike222056https://www.sportsdirect.com/nike-victori-one-mens-slides-222056
adidas Tensaur Sport CF Junior25GBPInStockadidas09068503https://www.sportsdirect.com/adidas-tensaur-sport-cf-junior-090685
Nike P-6000 Junior Shoes57.99GBPInStockNike041195https://www.sportsdirect.com/nike-p-6000-junior-shoes-041195

Column names are ones we chose when declaring the schema for this run. Yours can be named whatever your downstream job already expects. We pointed the run at 14 Sports Direct product pages and 4 came back with a readable price. The rest returned something other than a product page, which is ordinary on this storefront and the reason the tier named above is what it is. We publish what we measured, not what we expect.

What a Sports Direct page costs

Pay-as-you-go from your wallet. No plan, no monthly fee, no seat count.

€3.75per 1,000 pagespay-as-you-go, no plan

Measured on 3 October 2026, not assumed. Sports Direct did not answer a plain request at all — the connection is dropped rather than refused, which is the most restrictive case and the one that needs the full stack.

Worked example

500 Sports Direct pages checked once a day for a month is 15,000 pages.

about EUR 56.25 for the month

You are charged for what a run actually used, not what it was expected to need, and your balance never expires.

See the full price list →

What this page is not promising

We would rather say this here than in a support ticket.

  • No dedicated Sports Direct endpoint

    There is no Sports Direct API in our catalogue and no pre-built Sports Direct schema. The AI scraper reads the page you point it at — that is the whole mechanism, and it is why it works on pages nobody built a connector for.

  • Nothing behind a login

    It reads what a visitor can see. Account pricing, contract pricing and anything behind a sign-in are out of scope.

  • No field the page does not show

    If the page does not print it, the scraper cannot return it. Identifiers like EAN or GTIN only come back where the retailer publishes them.

  • A price is a point in time

    Every row carries the timestamp of the run that collected it. A price without one is not evidence, which is why the column is in the default schema.

  • Sports Direct has one specific trap

    Every product shows an RRP that is rarely a price the item sold at, so discount depth taken at face value is misleading.

  • Not a bulk dump of the catalogue

    You give it the URLs you care about. It does not crawl sportsdirect.com end to end, and a schedule that tried to would cost more than the answer is worth.

Typical fields the AI scraper extracts from a Sports Direct page

Treat this as a starting point rather than a fixed schema. What comes back is whatever the page actually shows on the day of the run.

Season and markdown

Outdoor ranges are bought in for a season and cleared at the end of it, so the markdown curve is the pricing story.

  • Current price
  • Strike-through price where shown
  • Markdown percentage as stated
  • Sale or clearance badge wording
  • Currency the page quoted

Size run and colourway

A technical product at a deep discount with one size left is clearing, not competing.

  • Sizes still available
  • Colourway the page is showing
  • Whether the variant is sold out entirely
  • Which sizes are listed at all
  • Delivery window shown

Specification and identity

Outdoor buyers compare on specification, and the specification table is usually rendered on the page.

  • Brand and model name
  • Site's own product code
  • Manufacturer part number, where printed
  • Technical specification table, where rendered
  • Category breadcrumb
  • Rating and review count, where shown

The column list is one you write: name each field, give it a type and a line telling the AI what to look for. The schema belongs to your run, not to us. How Custom Schema works →

What it cannot give you If a field is not visible on the page, the scraper cannot invent it. Identifiers such as EAN or GTIN only come back when Sports Direct publishes them.

What people use Sports Direct data for

01

Season-end markdown tracking

When clearance starts, on which lines and how deep. That calendar repeats each year and is only visible if you collected it last year.

02

Size availability as a demand signal

Sizes disappearing at full price is the closest public proxy for sell-through on a technical range.

03

Brand price-floor checks

If you make outdoor or sports gear, this is how you see what your products are actually listed at across the retailers that carry them.

04

Cross-retailer specification comparison

Where pages publish part numbers and specification tables, one schema across retailers produces a table that genuinely joins.

05

Range and assortment research

What a category carries, at what price points, from which brands, before you commit to a buy.

06

Feeding your own pricing rules

The export is a normal REST API or CSV, so it drops into whatever markdown logic you already run.

What makes Sports Direct harder than an ordinary storefront

Here is what the scraper is actually up against on sportsdirect.com, measured rather than assumed.

Access

  • Plain HTTP requests are dropped rather than answered, so there is nothing to parse
  • No named protection vendor on the response, which is why this one lands on a cheaper tier than most of the cohort
  • No usable sitemap directive in robots.txt, so the URL list comes from your own category pages

Seasonal ranges and size runs

  • Colourways are often separate URLs with their own stock and sometimes their own price
  • Size availability moves daily and independently of price
  • Clearance lines appear and disappear within days, so a weekly check loses the interesting rows
  • Category pages are lazily loaded and paginated, so a sweep is a list of URLs rather than one request

What the page publishes

  • No product-level structured data is published, so every field is read off the rendered page
  • Every product shows an RRP that is rarely a price the item sold at, so discount depth taken at face value is misleading.
  • Price is one of the last things the page settles on, so a read taken too early records the placeholder rather than the number

Keeping a history

  • A single read is a snapshot; the value is in the series, which means the run has to be scheduled and the rows kept
  • Every row carries the timestamp of the run that produced it, so two days can be compared without guesswork
  • Columns stay stable between runs, so a dashboard written once does not break when the site redesigns
FAQ

Sports Direct scraping — questions

What people ask before pointing the scraper at sportsdirect.com.

Sports Direct publishes no read API for its catalogue. There is no key to apply for and no endpoint to call, which is why the page is the interface.

Ready to pull Sports Direct data into your stack?

Start free — or talk to our team about your exact fields, refresh cadence and volume.