The final real-world outcome of every captured Kalshi sports game (Dec 2025 – Apr 2026), reconstructed from ~94M live quote snapshots: final scores, winners, and settled flags for 2,621 games across NCAAMB, NCAAWB, NHL, NBA, NFL and CFB. One row per game, joinable to any Kalshi tick data on game_id. Kalshi publishes no historical results keyed to its tickers — the women's college basketball coverage in particular is effectively exclusive.
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.
2,621 games · 1,990 settled (final score + winner) · 7 sports captured · includes 5-game tick sample + quickstart
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.