Platform · Steam

Steam Store Data Scraping

Steam publishes concurrent players. Almost nothing else in games does, which is why it anchors the dataset.

Steam exposes two different surfaces and they are not equivalent. The documented Web API carries a published key limit of 100,000 calls a day and returns current concurrent players and review counts with the positive percentage. The storefront endpoints used for pricing are undocumented and unsupported, with no published rate limit, so they are polled conservatively. Prices resolve by country code, and the country and currency sit on every row. Every record carries its data basis — public page, official API, or licensed and therefore excluded — and nothing unpublished is modelled, so a figure a source does not publish comes back null with a reason.

An undocumented endpoint is not a promise. It is polled gently and the record says it came from there.

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steam_sample.jsonl LIVE FEED

{"app_id":"as published","country_code":"DE","currency":"EUR","current_price":49.99} {"data_basis":"official_api","concurrent_players":18422,"observed_at":"2026-09-23T10:00Z"} {"data_basis":"public_page","review_count":91204,"review_pct":87}

illustrative sample rows · Globaltwo surfaces, one game · schema v1.0

Independence and trademarks. Actowiz Solutions is not affiliated with, endorsed by or connected to Steam or its owners. Steam and related marks belong to their respective owners, used here only to name the publicly accessible source this service collects from.

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Steam at a glance

How we handle Steam specifically

Platform-specific handling, not a generic retail template pointed at a different domain.

Documented API: 100,000 calls a day per key
Public metrics: Concurrent players, review counts
Store endpoints: Undocumented, unsupported
Pricing: Per country code
Regions: Many currencies plus regional groups
Price rises: Trigger a discount cooldown
Sales: Published event calendar
Refresh: Hourly in sales, daily otherwise

Platform specifics

Two surfaces, one storefront

These are the reasons a Steam dataset needs its own handling rather than a shared retail schema.

Source fields

A documented API with a stated limit and an undocumented endpoint with none are different risks, and the record distinguishes them so a client can see which is which.

data_basis — official_api or public_page, on every row.
country_code and currency on every price.
tax_inclusive flag, since display rules differ by region.
concurrent_players with its capture timestamp, never modelled.

Litigation, and what we do not do

Litigation

Antitrust proceedings over platform price-parity terms are live in more than one jurisdiction, including a developer class certified in November 2024 and a UK collective claim certified in January 2026; they are recorded as dated case facts, with no outcome predicted. See our regional pricing page.

Data basis

Prices stay attached to their storefront, region and currency, and a historical low is only ever computed from our own observation archive, as the gaming and sports hub describes.

What we do not do

Exceed a published key limit, hammer an undocumented endpoint, model player counts, use an account or library, or predict a case outcome.

Scope

What we collect on Steam, and what we do not

The right column matters more than the left. Anyone can list fields; the limits are what tell you whether the dataset will hold up.

✅ What we collect

Data basis on every row
Documented limits respected
Undocumented endpoints polled conservatively
Country and currency on every price
Tax inclusivity flagged
Concurrent players as published
Review counts and percentage as published
Historical low from our own archive
Hourly refresh during sales

❌ What we do not, and why

Modelled player counts
Key limits exceeded
Accounts or libraries
Predicted litigation outcomes
Prices without a country code

Core Steam fields

The full dictionary is agreed during scoping. These are the fields specific to this platform.

Field	What it is on this platform
app_id / title	Stable identifier
publisher / developer	As listed
country_code / currency	Price context
base_price / current_price	Local currency
discount_pct / sale_name	Where in a sale
tax_inclusive	Region rule
edition	Standard, deluxe, bundle
concurrent_players	As published, timestamped
review_count / review_pct	As published
historical_low	From our archive
data_basis / observed_at	Per record

Use cases

What teams do with Steam data

Price benchmarking

One title across regions.

Sale analysis

Discount depth by event.

Engagement tracking

Published concurrents over time.

Catalogue monitoring

Releases, editions and delistings.

The 24-hour sample — run on your sources, not ours

Send us a Steam item or category list. We run real collection against it and return the output within 24 hours, with the platform-specific fields populated so you can check them yourself rather than take our word for it.

Real extraction from your actual sources
Returned within 24 hours
Coverage and QA note included
You keep the data either way
No card, no trial clock
Named engineer on the call

Get my free sample Book a 20-min scoping call Reply within one business day. Reference calls available under NDA.

How we engage

Three ways to engage us

Same collection pipeline and QA underneath. The difference is who holds the schedule and how the data reaches you.

Managed service (most common)

We own the collection, the QA and the delivery. You receive clean data on a schedule and never touch a scraper.

Dedicated engineer assigned to your account
Site changes fixed by us, not reported to you
Scheduled delivery to your warehouse or S3
Named contact on Slack or email

Best fit: Teams who need the data, not the infrastructure.

API access

The same collection pipeline exposed as an authenticated REST endpoint your systems query directly.

On-demand and scheduled endpoints
Rate limits agreed to your load profile
Sandbox keys for integration testing
Versioned schema with deprecation notice

Best fit: Product and engineering teams building on live data.

One-time or project extraction

A defined pull for a specific question — market sizing, diligence, a pitch, a one-off audit.

Fixed scope agreed in writing upfront
Single delivery with full QA report
Methodology documented for your records
Converts to managed if you want continuity

Best fit: Research, strategy and diligence work with a deadline.

Pricing

Every engagement is quoted individually, because the honest answer depends on your scope: how many sources, how many records, how often, and how the data reaches you. We scope it with you, run a free pilot on your own sources, and then quote a fixed monthly figure — no per-request metering and no overage billing when volumes move. Request a quote and you will have a number after one call.

Steam is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. Steam data becomes useful when it sits next to the competitor set on one schema, refreshed on one schedule, so a price index or availability comparison is genuinely like-for-like.

That is what gaming & sports data covers, and a Steam-only engagement can be expanded into it without rebuilding. If you already know you need several platforms, start there instead — it is the same pipeline and usually the better scoping conversation.

FAQ

Steam data scraping: frequently asked questions

Platform-specific questions, including what cannot be collected here.

Yes for some data, with a published daily key limit that we stay inside.

They come from undocumented storefront endpoints, polled conservatively and labelled.

Never. Only the published concurrent figure, with its timestamp.

To the start of our own archive, and the record says so.

No. Nothing behind a login.

It depends on titles, regions and refresh.

Talk to us.

See real Steam data before you commit to anything

Send us an item or category list. We return the output within 24 hours with the platform-specific fields populated.

Get a free sample Talk to an engineer

Free pilot, no card, no obligation. If we cannot collect a field you need on this platform, the sample shows you that too.

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