Download MLB Polymarket and Kalshi top-of-book quotes with nearest alignment within 30 seconds. Partial coverage and unresolved labels are documented.
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.
Test the same schema with the $9 MLB tryout — 25,914 sampled quote rows across 28 dated games (26 settled, 2 unresolved). Review its coverage before buying.
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
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: 1,394,808 total rows · book samples 2026-06-21T00:00:27.733581Z through 2026-09-30T20:37:34.024713Z · artifact vintage 2026-10-02; separate from observation times
Compare recorded venue midpoints for a dated matchup and represented team. The paid archive pairs a Polymarket sample with the nearest Kalshi sample within ±30 seconds; that Kalshi observation can be later. This is retrospective nearest alignment, not a backward-only as-of join or an execution backtest.
Download the free ARI/MIN matched MLB CSV as mlb_matched_sample_ARI-MIN_2026-06-21.csv. This standard-library example uses its actual columns:
import csv
from decimal import Decimal
with open("mlb_matched_sample_ARI-MIN_2026-06-21.csv", newline="", encoding="utf-8-sig") as handle:
rows = list(csv.DictReader(handle))
for row in rows[:5]:
gap = Decimal(row["poly_mid"]) - Decimal(row["kalshi_mid"])
print(row["date"], row["game"], row["team"],
"recorded midpoint difference (dollars/share)", gap)Both venues' quote fields use the 0–1 dollar convention. The computed difference corresponds to xvenue_spread; it is not executable profit. The free single-game sample does not verify the corrected paid archive's capture window, mappings or labels. Use the current matched archive schema and methodology for its dated-key, doubleheader, complement-derived outcome and unresolved-label rules.
Neither sample time nor nearest alignment establishes quote freshness or a fill. For a causal study, separately establish what information was available before each decision; these columns do not expose exchange freshness timestamps. Review the related matched-book research and compare the separate MLB matched-book tryout before buying the larger archive.
Compare sampled prices with the nearest-time join offset; this archive alone does not establish which venue moved first.
Inspect sampled bids and asks with freshness and one-sided-book limitations; quoted gaps are not demonstrated fills or profit.
Group quote behavior by the finalized market result without building a separate settlement join.
Use the manifest and per-day counts to keep missing capture windows out of the test set.
We publish real sample rows — not a marketing mockup. Load them in DuckDB, inspect the schema and coverage contract, then decide.