See a few seconds of dots, an image of buildings, or a weight. Estimate the quantity. We don't just check if you're right — we check whether your confidence matches your accuracy.
What makes this one different
A right answer with high confidence is the gold standard. A wrong answer with low confidence is honest. We compute a calibration score: when you're 80% confident, are you actually right 80% of the time? Most people are over-confident.
Ideal: the line follows the diagonal. Above the line = under-confident. Below = over-confident.
No sessions yet.
Most estimation exercises focus on accuracy: were you close? But being right by luck isn't the same as being right by judgment. Calibration — the relationship between confidence and accuracy — is a better signal of "good judgment." It's measured in forecasting tournaments (Good Judgment Project), intelligence analysis, and weather prediction.
Calibration score near 0 is excellent. Below 0.05 is great. Above 0.15 means your confidence doesn't match your accuracy.
Over-confident people say "90%" but are right only 70%. Under-confident people say "60%" but are right 80%. Both are bad calibration.
Within a factor of 2 (i.e., your estimate is between half and double the truth). That's a standard "order-of-magnitude" looseness for sanity-check estimates.
Yes — there's a strong literature showing calibration improves with feedback. The trick is to treat 70% confidence as "3 out of 10 times I'm wrong."