Polymarket + Kalshi combo and parlay data, Aug–Oct 2026: fills, prints, decoded legs and outcomes in Parquet, with a derived 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.
A competition season has not been verified for this archive. This is not a complete-season archive.
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.
Polymarket combo fills are public on-chain events: anyone can re-read them from Polygon. Kalshi publishes per-market trade history, so complete prints for any listed combo can be fetched from Kalshi directly. What this archive adds is the decoding and joining: each Polymarket combo's decoded legs, market names and on-chain outcome; Kalshi's combo definitions with leg labels, combo and leg results, and the book snapshot our recorder took when it registered each combo, in one schema with a derived coverage map and a list of every known gap (gaps.csv).
Dated snapshot: 1,323,840 Polymarket combo fills · 298,628 Polymarket combos · 1,272,949 Kalshi combo definitions · 1,676,300 sampled Kalshi combo prints · 16,561,512 total rows · Kalshi trade prints are a small sample: about 2.0% of all Kalshi combo trades Aug 6-Oct 4, 2026, measured against Kalshi's own history · 2026-08-06 through 2026-10-04 · artifact vintage 2026-10-04; separate from observation times
Compare combo structure, prices and settlement between Polymarket and Kalshi over the same weeks.
Use gaps.csv (every Kalshi dark window and suspected Polymarket thin window) and days.csv to exclude them before any analysis.
We publish real sample rows — not a marketing mockup. Load them in DuckDB, inspect the schema and coverage contract, then decide.