Jul 18–19 write-day partitions of Kalshi depth and prints, mostly MLB/WNBA. Separate coverage note; first depth timestamp is Jul 17 UTC.
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.
Start by inspecting the free sample and schema. If this format fits your project, review the larger Kalshi tape's coverage. The tryout and archive are separate one-time purchases.
Frozen artifact delivery: 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.
MLB 2026 · Phase coverage not specified
WNBA 2026 · Phase coverage not specified
NFL 2026 · Phase coverage not specified
The sample uses July 18–19, 2026 UTC write-day partitions; a partition can include an observation timestamp from the preceding UTC day. Exact book and print time bounds are not recorded in this catalog metadata. Partition dates are not substituted for those clocks.
UTC timestamps retain their recorded precision; dates alone identify UTC days. Capture time does not establish exchange quote freshness or an executable fill.
Scheduled event times are not inferred from capture windows or combo trade dates.
The schema and coverage notes identify this artifact's record types: sampled quotes or depth, trade prints, derived outcomes or analysis, depending on the product. Observation time, exchange event time and artifact vintage are different clocks. Read the documented fields, gaps and joins before deciding whether the file fits your research; a quote observation does not establish a fill.
Dated snapshot: 21,520,801 depth rows · 746,902 trade prints · 22,267,703 total rows · 2026-07-18 through 2026-07-19 · artifact vintage 2026-07-19; separate from observation times
Load the same Parquet schema as the full tape and test joins, storage and feature code at lower cost.
Confirm the sampled L2 and deduplicated trade fields fit your research question before buying the growing archive.
We publish real sample rows — not a marketing mockup. Load them in DuckDB, inspect the schema and coverage contract, then decide.