The core idea
A simple crowd average treats every forecaster equally — the analyst who has been right for years counts the same as someone predicting for the first time. Smart Consensus instead weights each contributor by how accurate they have actually been, so proven forecasters move the number more than newcomers or chronically-off predictors.
How the weighting works
Each user's weight is derived from their difficulty-adjusted mean error — being accurate on a hard, thinly-covered name counts for more than nailing an easy, heavily-covered one. The weighted mean is Σ(wᵢ · forecastᵢ) ÷ Σ(wᵢ), with weights clamped to a sensible range and any single contributor's influence capped so one account can't dominate.
Minimum history and privacy
Weighting only activates once a user has enough resolved estimates to judge them — below that threshold everyone gets a neutral weight (a plain average). Community figures are also only shown once enough independent forecasters have contributed and their answers actually differ, so no individual's prediction can be reverse-engineered.
Related tools
See how the consensus estimate is built in the Earnings Season course lesson on how the consensus estimate is set.
Read the exact formula in the Smart Consensus methodology, or see where the crowd most diverges from Wall Street on the crowd-vs-Street board.