Historical Polymarket sports quotes and L2 depth for every captured sport, Mar–Oct 2026. Dated Parquet with coverage map.
Full schema & known gaps →· Sold as-is — but if a file is broken or won't open, email [email protected] and we'll send a fixed file or refund you. No hassle.
Inspect the free sample rows and schemas before buying.
Artifact vintage: the product page and shipped documentation state the exact coverage, row counts and known limitations. A purchase delivers the advertised frozen artifact; no future refresh is promised unless the checkout terms explicitly say so.
Declared season scope; individual event-to-season mapping is unverified. This is not a complete-season archive.
College football 2026 · Phase coverage not specified
Copa Libertadores 2026 · Phase coverage not specified
MLB 2026 · Phase coverage not specified
MLS 2026 · Phase coverage not specified
NFL 2026 · Phase coverage not specified
Tennis 2026 · Phase coverage not specified
WNBA 2026 · Phase coverage not specified
UTC timestamps retain their recorded precision; dates alone identify UTC days. Vintage, observation and sports event times are separate. Capture time does not establish exchange quote freshness.
Sports event starts: start unknown → end unknown. Event dates are not inferred from these quote capture windows.
Venue APIs expose useful live books, trades and price history, but they do not serve the same historical snapshot and game-context archive packaged here. Data that was not recorded during the live window cannot be recreated from a current-book endpoint later. The exact fields, cadence, venue coverage and limitations vary by product, so this page and the shipped documentation state the contract explicitly instead of calling every file complete or tick-level.
Dated snapshot: 587,197,084 depth rows · 1,628,787,386 total rows · book samples 2026-03-28T17:36:32Z through 2026-10-03T23:59:21Z · artifact vintage 2026-10-03; separate from observation times
Compare spreads, depth and repricing speed across every sport label in one consistent schema.
Use COVERAGE.md and days.csv to exclude dark windows and thin days before any backtest.
We publish real sample rows — not a marketing mockup. Load them in DuckDB, inspect the schema and coverage contract, then decide.