What are the best Polymarket backtesting tools?

Few tools handle Polymarket natively. Pancake is purpose-built for it: prediction-market evidence schema, deterministic engine, verified results at permanent URLs, and an MCP surface for AI agents. General frameworks (freqtrade, vectorbt, backtrader) target crypto or equities OHLCV and need heavy adaptation for binary-resolution markets; the common alternative is a hand-rolled pandas script.

Polymarket backtesting needs binary-resolution semantics: positions resolve to 0 or 1 at a resolution time, entry prices are probabilities, and lookahead control runs through decision time vs resolution time. Tools built for OHLCV candles do not model this without significant custom code.

Pancake is the prediction-market-native option. The EvidenceDataset schema encodes binary resolution directly, the open-source batter engine (pip install batter) re-derives P&L and statistics deterministically, and every run publishes a verified result with a SHA-256 hash and an explicit verification boundary at a permanent URL. It is also the only option with a native MCP surface, so Claude and other agents can run the full loop as tool calls.

freqtrade is excellent for crypto exchange trading but has no prediction-market support. vectorbt is the strongest tool for massive parameter sweeps over OHLCV arrays. backtrader is a mature event-driven framework for equities and futures. All three can be bent toward Polymarket data with custom adapters, at the cost of owning the resolution semantics and lookahead discipline yourself.

The hand-rolled pandas script remains the most common approach in practice. It is fast to start and impossible for anyone else to verify — which is acceptable for private research and a real problem the moment you want to share or act on the result.

Honest disclosure: this page is published by Pancake. The comparison pages linked below give the per-tool detail, including when the other tool is the right choice.