Run several independent forecasting models on the same event — an Elo rating, a polling model, a fundamentals model, a machine-learning classifier — and average them into one combined probability, sizing your bet by how far that blended number sits from the market price. The edge is that averaging multiple models cancels out each one's errors, giving a sharper estimate than the single public model the crowd tends to anchor on.
Markets on Polymarket where ensemble forecast vs market-implied edge is the natural play:
