If you want to study mean-reversion on prediction markets, the data you actually need does not exist publicly. Most "Polymarket datasets" are either: Synthetic — generated for academic papers, no real money behind them. Aggregate — hourly volume and last-price across thousands of markets. Useless for tactical signal research. So I built one and open-sourced it: cross-signal-data . pip install cross-signal-data Enter fullscreen mode Exit fullscreen mode from cross_signal_data import load df = load () # pandas DataFrame, 308 rows print ( df [ " is_profitable " ]. mean ()) # 0.802 Enter fullscreen mode Exit fullscreen mode This is the actual labeled outcomes of 308 closed trades from a live Polymarket crash-recovery bot, with the signal features and the resolved outcome for each trade. Also mirrored on HuggingFace: huggingface.co/datasets/LuciferForge/cross-signal-data .…