Guides / Quant Modeling
Random Forest is an ensemble tree model useful for ranking which orderbook/trade features actually predict outcomes. Applied to prediction markets, it's typically trained on engineered features — orderbook imbalance, spread, recent trade flow, time-to-resolution — pulled from historical snapshots, with the market's eventual resolution (or a forward price move) as the label.
ProbSights doesn't run Random Forest for you — it provides the orderbook and trade history across Kalshi and Polymarket that a model like this consumes: BTC/ETH/SOL Up/Down snapshots at 5m–24h resolution on the Pro plan, and Polymarket + Kalshi data more broadly on Builder. Pull it via the API and feed it into your own training pipeline.
Data from Kalshi and Polymarket. Search live API docs Pricing