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The complete Kalshi historical archive

Kalshi Historical Data

Every Kalshi market and trade — ready to query, chart, export, and backtest.

Instantly access 7.68M+ unique markets and 72.1M+ historical trades since July 2021, including prices, volume, outcomes, and orderbook history — no code, no setup or data pipeline required.

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  • Trade history
  • Orderbook history
  • CSV/XLSX/JSON exports
  • No-code querying
  • Backtesting-ready

10,000+ researchers, traders, quants, and analysts use Lychee.

43,400,000+ historical data requests were served from the archive in June 2026 alone.

7.68M+

unique markets

72.1M+

historical trades

36GB+

compressed archive

Since July 2021

Every Kalshi market and trade since launch

What's inside the Kalshi historical dataset?

Complete Kalshi market history, trades, prices, outcomes, categories, and orderbook behavior — ready to query, chart, export, and backtest from your browser.

  • Markets

    Tickers, titles, categories, open/close times, market status, volume, event metadata, and final outcomes.

  • Trades

    Historical executions with timestamps, prices, quantities, tickers, market IDs, and YES/NO side data.

  • Orderbook history

    Historical bid/ask behavior, spreads, liquidity, market depth, and orderbook changes where available.

  • Categories and events

    Weather, politics, sports, finance, crypto, economics, culture, and other Kalshi market categories.

  • Resolution data

    Final outcomes for calibration, accuracy studies, backtesting, lifecycle analysis, and strategy research.

  • Exports

    Download query results as CSV, XLSX, or JSON depending on your plan limits.

Kalshi Historical is just one layer of Lychee.

Every paid plan also includes Kalshi Live, Polymarket Historical, Polymarket Live, no-code charts, dashboards, exports, alerts, and quant workflows — so you can compare historical markets against what is happening now.

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Compare Kalshi historical data sources

Most Kalshi data options give you raw endpoints, partial history, or developer infrastructure. Lychee gives you the complete Kalshi historical archive, live Kalshi data, cleaned analysis tables, exports, charts, dashboards, and quant workflows — all no-code.

Feature / workflow
LycheeMost complete no-code workspace
Kalshi API
Dome
Predexon
Allium
Kalshi website
DIY scripts / notebooks
Historical Kalshi coverage
Complete launch-to-present archive: markets, trades, prices, categories, outcomes, and orderbook history where available.
Official raw API with live/historical split. You query, paginate, store, clean, and join data yourself.
Developer API for live and historical data. Not a no-code workspace or full launch-to-present Kalshi archive.
Endpoint-specific access. Kalshi orderbook history documented from Jan 7, 2026 — narrower than Lychee’s archive.
Warehouse/SQL access including Kalshi orderbook tables. Strong for data teams, not no-code research.
Manual browsing of current/recent markets. Not a historical archive.
Only as complete as what you collect, backfill, store, and maintain.
Live Kalshi data
Kalshi Live included alongside Kalshi Historical.
Yes — official live market endpoints.
Yes — API/websocket live prediction market infrastructure.
Depends on endpoint and provider coverage.
Primarily warehouse access, not a point-and-click live workspace.
Yes — live market interface for trading and browsing.
Possible, but you build and maintain collectors.
Other data sources / integrations
Kalshi Historical + Live, Polymarket Historical + Live, Chainlink, Binance, CoinGecko, GeckoTerminal, Twitter/social signals, and more — all no-code in one workspace.
Kalshi only. Official exchange API for Kalshi markets, trades, orders, fills, and historical/live Kalshi data.
Prediction-market API coverage across Kalshi, Polymarket, and other markets. Developer/API-first, not a no-code research workspace.
Infrastructure across Polymarket, Kalshi, Limitless, Opinion, Predict.fun, Hyperliquid, Binance reference data, and Chainlink streams. Developer/API-first.
Warehouse-style access across Polymarket, Hyperliquid prediction markets, and broad on-chain ecosystems. Strong for SQL/data teams, not no-code workflows.
Kalshi only. Good for browsing and trading Kalshi markets, not combining external data sources.
Anything you build manually — every integration, schema, refresh, join, chart, and export maintained by you.
No-code access
point, click, filter, query, chart, export, and analyze in the browser.
No — requires code and API work.
No — developer/API-first.
No — developer/API-first.
No — SQL/data-team oriented.
Yes for browsing/trading, not bulk historical analysis.
No.
Data cleaning, joins, and normalization
Already handled. Markets, trades, outcomes, categories, prices, and live/historical data connected for analysis.
You handle schemas, pagination, storage, joins, retries, cleanup, and normalization.
Simplifies developer access; you still work through API responses and build downstream analysis.
Endpoint-specific access; you build research logic and downstream analysis.
Structured access, but you write SQL/queries and build analysis workflows.
Not available for research workflows.
You build everything.
Exports
CSV, XLSX, and JSON exports depending on plan limits.
Raw API responses; you build the export flow.
API responses; you build the export flow.
API responses; you build the export flow.
Warehouse query outputs; technical export workflow.
No bulk analyst-ready export workflow.
Possible, but user-built.
Built-in analysis
Volatility, Brier scores, calibration, lifecycle analysis, backtesting, category analysis, volume analysis, and quant workflows.
None built in.
Developer infrastructure, not no-code quant analysis.
Data endpoints, not a full analysis workspace.
Powerful if you write queries, but not packaged no-code workflows.
Basic market views only.
Only what you implement.
Charts and dashboards
Built-in charts, dashboards, embeds, saved workflows, and reusable research outputs.
No; build UI and charts separately.
Not a no-code dashboard product; you build the UI layer.
Not a no-code dashboard product.
Data infrastructure, not a no-code chart/dashboard builder.
Basic single-market charts.
Possible, but user-built.
Best for
Traders, analysts, researchers, quants, creators, and teams wanting complete Kalshi analysis without building infrastructure.
Developers who want official raw endpoints and full control.
Developers building apps, bots, agents, or infrastructure across prediction markets.
Developers needing specific Kalshi endpoints or orderbook snapshots.
Technical teams that prefer warehouse/SQL access.
Traders checking individual live markets.
Technical users with time to build and maintain their own pipeline.

With raw APIs and third-party feeds, you still have to collect, store, clean, join, export, chart, and analyze the data yourself. With Lychee, that work is already done — so you can go straight from question to answer.

Get Access NowExplore for free

Try Lychee’s Kalshi Historical Data Explorer

Search historical Kalshi markets and trades, preview real rows, apply filters, and export clean results without writing code.

Historical Data

Example Kalshi historical workflows

Start with simple workflows, then scale into deeper research.

  • Top Kalshi markets by volume

    Find the highest-volume historical Kalshi markets since launch.

  • Resolved politics markets

    Filter finalized political markets and study probability, volume, and outcome behavior.

  • Weather market history

    Pull historical weather markets by location, contract type, or time window.

  • Trade history export

    Select trades, choose fields, and export a clean CSV/XLSX/JSON sample.

  • Volume by category

    Group markets by category to see where Kalshi trading activity concentrates.

  • Backtesting dataset

    Use resolved markets, prices, volume, and outcomes to test prediction market strategies.

Choose a guided workflow and Lychee will walk you through every step—from selecting the historical dataset and applying filters to running the query, inspecting the results, and building the final chart or export.

Try it now →

Research and Guides

Guides

Volume

Guides

Dashboards

Politics

Research

Weather

Research

Charts

Guides

Dashboards

Charts

Every published chart built on Kalshi historical data — volume trends, probability convergence, calibration curves, and more. Run any chart for yourself with your own parameters.

Video Instructions

Step-by-step walkthroughs for building Kalshi weather market charts on historical data — probability convergence, calibration, and volatility.

  • Build a Kalshi Probability Convergence Chart

    Watch how to pull historical trades, bucket by time, and chart VWPA-style probability convergence for weather markets.

    Read the full step-by-step guide →

  • Build a Kalshi Weather Probability Calibration Chart

    See how to bucket market outcomes and compare implied probabilities to long-run resolution rates.

    Read the full step-by-step guide →

  • Build a Kalshi Weather Volatility Chart

    Follow the full workflow for returns, rolling standard deviation, and intraday volatility clustering on weather trades.

    Read the full step-by-step guide →

Kalshi Historical FAQ

Does Lychee include all Kalshi historical markets?
Lychee is built around a complete Kalshi historical archive covering markets, trades, prices, volume, outcomes, and orderbook history since Kalshi launched. It is designed for users who want to search, analyze, chart, export, and backtest Kalshi data without building their own data pipeline.
Can I download Kalshi historical data?
Yes. Lychee supports CSV, XLSX, and JSON exports from query results. Export size depends on your plan limits, so you can start with small samples and upgrade for larger historical pulls.
Does Lychee provide a Kalshi historical data API?
Not yet. Lychee currently provides no-code browser access, query tools, charts, dashboards, exports, and research workflows. The point is to let you use Kalshi historical data without writing API scripts or maintaining your own pipeline.
Can I use Lychee for Kalshi backtesting?
Yes. Lychee's historical Kalshi data can be used for backtesting and research workflows involving historical trades, market outcomes, price movement, volume, category behavior, and orderbook history.
What is the difference between Kalshi Historical and Kalshi Live?
Kalshi Historical is for analyzing past markets, trades, outcomes, and historical market behavior. Kalshi Live is for current and recent market monitoring. Lychee lets users combine historical and live Kalshi workflows inside the same platform.
Do I need Python or SQL?
No. You can search, filter, sort, chart, dashboard, and export Kalshi historical data through Lychee's visual workspace. Developers can still export data for their own stack, but code is not required to start.

Start analyzing Kalshi historical data

Run a free sample query, inspect historical markets and trades, then unlock larger pulls, exports, dashboards, and backtesting workflows.

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