Tick-level bid/ask/spread/volume snapshots from BOTH Polymarket AND Kalshi sports prediction markets, score-synced with live game state. Two independently-recorded feeds: Kalshi runs Dec 28 2025 – Jan 30 2026 (broad sport coverage); Polymarket runs Jan 18 – Jan 29 2026. Dense capture but not gap-free — the included schema lists per-sport coverage and known gaps (e.g. NFL moneyline ends Jan 19). Polymarket publishes no historical orderbook API, so this is the only commercial source for backtest-ready depth across both venues. Sold as-is.
Neither Polymarket nor Kalshi publishes historical orderbook data — their public APIs give you trades and last price, never the full book over time, and never joined to the game. That makes this data physically non-reconstructable retroactively: the score-sync has to be captured live, tick by tick, as each game happens. We have been recording it. A provider starting today cannot backfill what they did not capture. Every snapshot here carries the live score, period and clock at tick time — the one thing every other "tick data" seller is missing.
136M snapshots (25.7M Polymarket + 110.5M Kalshi). Kalshi Dec 28 2025 – Jan 30; Polymarket Jan 18 – 29. Per-sport coverage + known gaps in the schema. Schema PDF included
Join your win-probability output on event and clock, and measure how many seconds the book trailed a real probability shift after a score.
Full depth lets you model slippage and partial fills against what the market actually showed — not an assumption that you hit last price.
With Polymarket and Kalshi on one timeline, measure which book moves first after a scoring event — the basis for cross-venue arbitrage research.
Citable depth and trade data for prediction-market efficiency and price-discovery studies, with provenance metadata.
We publish real score-synced sample rows — not a marketing mockup. Load them in DuckDB, check the schema, confirm the score-join is there, then decide.