Compare Kalshi and Polymarket Odds in Real Time
Find matching prediction markets across Kalshi and Polymarket, then compare their live YES/NO prices, charts, trading activity, volume, spreads and order books in one view. Search by event or ticker and see where the two markets agree—or disagree. Free to use with no signup required.
Find matching prediction markets across Kalshi and Polymarket, then compare their live YES/NO prices, charts, trading activity, volume, spreads and order books in one view. Search by event or ticker and see where the two markets agree—or disagree. Free to use with no signup required.
Go from raw markets to charts and dashboards in seconds—no code, no CSVs.
Free to explore here · Polymarket, Kalshi, Chainlink & more
More reading
How to Compare Kalshi and Polymarket Odds Live
Learn how to compare matching Kalshi and Polymarket odds in real time, verify settlement rules, track price gaps, and assess whether a difference is meaningful.
Why Random Sampling Matters in Data Analysis: A Polymarket Case Study
Learn how random sampling, sample size, and representative samples work through 15 seeded samples of 383,707 historical Polymarket markets.
What Does Volume Mean on Kalshi? Trading Volume Explained
Learn what volume means on Kalshi, how trading volume works, why it matters, and how to analyze Kalshi market activity using historical volume charts.
When Do Prediction Markets Become Accurate? A Kalshi Political Market Lifecycle Analysis
Are prediction markets accurate? We analyzed 3,195 resolved Kalshi political prediction markets across 25,552 lifecycle snapshots to measure when market odds become reliable.
Are 90% Prediction Markets Reliable? A Kalshi Political Calibration Study
We analyzed resolved Kalshi political markets to test whether 90–100% prediction markets are overconfident. The data showed high-probability markets were reliable, while the middle probability range was sparse and noisy.
How to Build a Kalshi Weather Volatility Chart (Step-by-Step Guide)
Step-by-step guide to calculating and visualizing volatility in Kalshi weather markets using historical trade data and no-code analysis in Lychee.