Blog

Insights on prediction markets, trading strategies, and how to leverage historical data for alpha discovery.

Atlanta weather probabilities over time
weathertemperature markets

Warm Sector, Cold Truth: Atlanta's 28°F Crash and What Polymarket Missed

The March 2026 megastorm delivered the sharpest temperature swing in the US this winter. We tracked how Polymarket's daily weather markets priced — and mostly failed to anticipate — Atlanta's 28°F temperature collapse in 72 hours.

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Empty office building, symbolizing job losses and economic downturn
economicsjobs

Polymarket's $644M February Jobs Bet: How the Worst Payrolls Print in Years Was Priced

February payrolls came in at -92,000. Polymarket had $644M wagered across seven range markets and still priced the correct outcome at 22 cents the morning it happened. Here's the full price path.

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Aerial view of Tehran city buildings during daytime
irangeopolitics

The Oman Fake-Out: How Polymarket Priced Khamenei's Death at 7.5 Cents the Morning Before It Happened

On Feb 27, the US/Israel strikes Iran market hit 7.5¢ after an Oman diplomatic breakthrough. Less than 24 hours later, Khamenei was dead. Here's what the full data shows.

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Laptop with code and charts open for prediction market research
tutorialapi

Getting Started with Polymarket Historical Data

Set up a clean first workflow with Polymarket historical data: fetch markets, pull minute data, and structure your first reproducible research notebook.

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Code and analytics dashboards used for strategy backtesting
backtestingpython

How to Backtest Polymarket Strategies with 1-Minute Data in Python

Build an execution-aware Polymarket backtest in Python: align minute bars, apply liquidity filters, and simulate realistic fills from historical L2 depth.

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Developer workstation running local agent workflows and market analysis
openclawpolymarket

OpenClaw + Polymarket: Build a Local Trading Agent With Historical L2 Data

A research-hardened guide to using OpenClaw for Polymarket workflows with strict agent contracts, historical L2 execution checks, and reproducible backtests.

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Multi-screen trading desk showing order books and price ladders
slippageorder-book

How to Calculate Polymarket Slippage with Historical L2 Order Books

Estimate realistic fill prices on Polymarket using historical L2 depth, weighted fills, and basis-point slippage reporting by regime.

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Sports stadium under lights representing event-driven market volatility
sportspolymarket

Polymarket Sports Trading Strategies: Model Slippage With Historical L2 Data

Use historical L2 order books to build sports-market backtests that include spread shocks, partial fills, and execution-aware position sizing.

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