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Strategy Evaluation Metrics for Prediction Markets

Raw return alone hides a lot. Worth tracking alongside it: win rate against resolved outcomes, average slippage vs. simulated fills, exposure duration per position, and drawdown across the backtest period — all computable from orderbook, trade, and resolution data together.

Related

• Working with resolved prediction market data
• Common backtesting mistakes

Related guides

• Prediction Market Data for Academic Research
• Building a Polymarket Backtesting Framework in Python
• Common Backtesting Mistakes in Prediction Markets
• Data Cleaning for Prediction Market Backtests

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