22 public data & analytics examples on Kalshi and Polymarket, each with its source.
Last updated .
Data and analytics projects collect, store and visualize prediction-market data: historical prices, order books, trades and resolutions. They are the usual starting point for research and backtesting.
Common tools here: Python (17), Parquet (3), Kalshi API (3), TypeScript (2), Polymarket data (2). Compare them side by side → · Kalshi bot guide · Polymarket bot guide
Framework for collecting and analyzing prediction-market data, including a large public Kalshi prediction market dataset.
Dataset stat Becker Kalshi dataset: 7.68M markets; 23.9% of settled markets resolved YES. Method on detail page.
Scripts to collect Polymarket market and trade data for analysis.
Unified API for trading on Polymarket, Kalshi and more.
MCP server that gives AI assistants Polymarket market data: prices, probabilities, market details and price history.
Performance tracker for Kalshi traders.
WebSocket client that streams and charts tick-by-tick data from Kalshi and Polymarket.
Read-only research repo that samples resolved Polymarket markets, prices them 7 days before scheduled end, and measures calibration and favorite-longshot bias with Brier decomposition, recalibration slopes and event-clustered errors, broken out by category and volume. The author's findings (self-reported) are that deviations are small and smaller than trading costs; a second part on arbitrage and order books is still collecting data.
Research repo on pricing Kalshi's MLB contracts: a data pipeline rebuilt from public MLB and Kalshi APIs, a market-making simulator, a paper-trading bot and contract-math helpers. Its README reports mostly negative findings for the game-winner contract (author's own backtests, unverified). Places no real orders.
Turns split-conformal price forecasts on public EIA WTI crude data into probabilities for threshold questions like 'will WTI close above $X by date Y?', with backtests and a dated forward track record. Analysis only; it never touches a Kalshi account.
Event-driven backtesting framework for binary markets such as Kalshi, Polymarket and PredictIt, with pluggable strategies, a simulated broker, settlement handling and a Streamlit UI showing equity curve, trade log and metrics.
Data and code for a 2026 preprint that measures Kalshi calibration while stepping from the displayed price to the order-book midpoint, the executable quote and the fee-adjusted taker return. Includes per-market JSONL logs, frozen outputs and a script that runs deterministic checks against the paper's tables.
Dependency-free JavaScript functions that compute taker fees with the shared rate x contracts x p x (1 - p) formula, using each venue's rate, plus an all-in cost per contract. The README explains maker vs. taker fees, Kalshi's round-up to the cent, and per-market Polymarket rates. The author says the tests were checked against real order tickets (self-reported).
Research project that streams Binance trades, builds per-second features and estimates the probability that a Polymarket 5-minute crypto Up/Down window closes up, comparing a Bayesian model with a LightGBM challenger against the market price. Ships a write-up of the ways the research produced false edges and how each was caught; the author's conclusion that there is no tradeable edge at this latency is self-reported.
Python study of resolved Polymarket yes/no markets that measures calibration, Brier skill and favorite-longshot bias at 1, 7 and 30 days before close, broken out by category, with an out-of-sample test of whether a recalibration fit could be traded. Includes reliability diagrams; all results are the author's own (self-reported).
Open research repo with a short paper comparing Kalshi and Polymarket Fed-decision markets with S&P 500 futures, USD/JPY and Treasury bills around CPI and payrolls releases (2023 to 2026). Measures whether both venues resolved correctly, how closely they agree, and how fast each absorbs macro news. Findings are self-reported by the author.
Minute-level research pipeline testing whether Polymarket geopolitical and military contracts lead oil futures, defense equities, Treasuries, VIX and gold ETFs, with control markets, closed-hours and reopen-gap designs and a draft paper. Results are self-reported by the author and not independently verified.
Read-only recorder that runs continuously on GitHub Actions, saving hourly snapshots of Polymarket markets ending within 45 days, their order books and taker trades, plus minute-level books and trades for markets with the largest liquidity-reward pools, as gzipped JSON bundles. Uses public Gamma, CLOB and Data API endpoints; no trading.
Open Python research project that checks whether Kalshi and Polymarket prices match how often outcomes actually happen. It measures prices at fixed horizons before close, tests for the favourite-longshot bias, and asks whether any mispricing survives trading costs. Includes CI and an interactive results page. Findings are the author's own and not independently verified.
Standard-library Python backtester for Kalshi's 15-minute Bitcoin up/down markets. It replays public one-minute candles and trade prints, charges Kalshi taker fees, runs parameter sweeps, and ships unit tests. The simulator has no network access; a separate fetcher caches public data. Backtest results are self-reported.
Docker Compose pipeline that streams Polymarket order book, trade and comment data into Kafka, archives raw events to Parquet, rebuilds order books in memory, computes real-time metrics, models history with dbt-duckdb, and serves a Grafana dashboard. Paper trading and replay backtesting are listed as next steps; real-money trading is out of scope.
Student research notebook (Rennes School of Business graduating project) that compares the probability distribution implied by SPXW and NDX option prices, using a fitted SVI smile, with the distribution quoted by Kalshi's S&P 500 and Nasdaq-100 range contracts for the same expiry. Uses Yahoo Finance option data and the Kalshi public API, with a saved snapshot in the repo. Findings are self-reported and based on a single snapshot.
Rust collector that records the full-depth order book of every live Polymarket market. It merges redundant websocket connections by first arrival, writes level updates plus a per-minute snapshot of every book in an SBE binary format, parses prices as fixed-point integers rather than floats, and ships inspect and latency-test tools. Built for an engineering challenge; data collection only, no trading.
New public Kalshi & Polymarket builds, each with a source. No spam.
Form not loading? Subscribe on beehiiv. Handled by beehiiv; see privacy. Unsubscribe any time.