How to Get CS2 Item Supply History

Updated

API reference: POST /v1/archive/history

POST /v1/archive/history returns approximate CS2 item supply through total_supply on the aggregate source. Coverage begins in 2023 and is available in 1h or 1d archive buckets.

total_supply is an observed level. The change between two observations can describe movement in estimated supply, but it does not identify an in-game cause or a set of individual items.

Supply-history fields#

Requesting the aggregate source can return:

Field Meaning
total_supply Approximate total supply at the observation
time Actual last observation timestamp inside the archive bucket
bucket Aligned UTC start of the 1h or 1d interval
sample_count Number of observations aggregated into the bucket
ask, bid Last-observed prices for context
hourly_volume Approximate sale-volume metric

Archive data begins in 2023 and updates once or twice per day. Supported variants can appear under variants when archive data exists for them.

Query and compare supply observations#

Request up to 100 exact market_hash_name values, set sources to aggregate, and choose 1h or 1d. Read total_supply from the aggregate object in each returned bucket.

Sort by bucket, retain the actual time, and calculate changes between consecutive observed rows. If a bucket is absent, preserve that longer time gap instead of filling it with the previous value.

The endpoint supports partial success. Resolved items remain under items, while invalid names or items without archive rows can appear in errors[]. The archive reference describes these item-level errors and timestamp fields.

Applicable endpoint#

Endpoint Returns Plans
POST /v1/archive/history Approximate total_supply from 2023 Scale, Enterprise

Interpreting supply changes#

  • A positive change can reflect newly observed items or revised coverage. A negative change does not prove items were destroyed.
  • ask_volume counts active listings and is not total supply. Substituting it would measure visible sell-side inventory instead of the item population.
  • Large changes should be checked against adjacent observations and sample_count before an in-game event is assigned as the cause.
  • Use supply and sale volume together when trading activity is needed beside the supply level.