LEARNMODELS
What Makes a Sports Model Well Calibrated?
A calibrated model says 60% and it happens about 60% of the time. Calibration is checkable — which is exactly why it matters.
Calibration is the agreement between stated probabilities and observed frequencies. Gather every forecast the model made near 60%. If about 60% of them hit, the model is calibrated in that range. Repeat across the scale.
Scores, not vibes
Brier scores and log-loss turn calibration into a single number you can track across versions. Lower is better; published is better than argued.
Calibration before hot streaks
A model can be calibrated and still lose a week. An uncalibrated model can win one. Calibration is the property that makes a probability trustworthy enough to base decisions on — over the long run, not the weekend.
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