Superforecasters represented the cream of the crop of the Good Judgment Project forecasters. And they’ve proven themselves time and time again since turning professional in 2015. Below, we present data about their track record in both absolute and relative terms.
Superforecasters beat all competing research teams in the IARPA ACE tournament by 35-72%.
Learn more »Good Judgment was over 30% more accurate than intelligence analysts with access to classified information.
Learn more »Superforecasters outperformed both client experts & a crowd-wisdom group in forecasting the new administration's policies.
Learn more »100 Superforecasters defeated hybrid systems combining machine learning with crowd forecasts from 1,000+ people.
Learn more »“Team Good Judgment, led by Philip Tetlock and Barbara Mellers of the University of Pennsylvania, beat the control group by more than 50%. This is the largest improvement in judgmental forecasting accuracy observed in the literature.”
Steven Rieber, Program Manager, IARPAAn analysis of Good Judgment Project forecasts by UC-Irvine decision scientist Mark Steyvers found that Superforecasters anticipated events 400 days in advance as accurately as regular forecasters could see those events 150 days ahead.
Our professional Superforecasters have tackled hundreds of forecasting questions since 2015. The statistics below summarize average performance over the 554 questions that have “resolved” (in other words, questions for which the outcome is known) as of 11 September 2023. For purposes of this analysis, the “correct” outcome means the answer option that actually occurred and resolved the forecasting question.
We’ll update this information periodically as additional questions close.
Forecasting questions posed to the Superforecasters that have "resolved"
Average percentage of days on which our forecasts placed the highest probability on the "correct" outcome
Percent of forecasts on which Superforecasters beat hybrid human + machine teams
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