The Calibration Trap: Why Your Perfect Model Fails in the Real World

And how confusing a historical diagnostic for a future guarantee is the most common mistake in forecasting.

I’ve read yet another paper from a brilliant team that has painstakingly trained a model to produce beautifully calibrated, probabilistic forecasts. They used the right tools—CRPS for forecasting, Log Loss for classification. They ran the right che…