HOW TO · PAPER PRACTICE

How to use Historical Calibration

Learn to compare probability groups with observed frequencies while checking the data behind a chart.

Before you start

The current tool displays a seed dataset and may overlay fetched data. It is not a personal forecast journal or a verified performance audit.

Open Historical Calibration

Step by step

  1. Open the chart and inspect the dataset label before interpreting any score.
  2. Select a category and read the horizontal probability buckets and vertical outcome frequencies.
  3. Compare the points with the diagonal reference line. Above it means more YES outcomes than the stated probabilities suggest; below means fewer.
  4. Keep a separate notebook for your own timestamped predictions. Only score them after checking the specified resolution source.

Worked example

If ten independent paper forecasts at 70% produce seven YES outcomes, that small group matches 70%. One group of ten is far too small to establish lasting accuracy. A 70% forecast resolving NO is not automatically a bad forecast.

What the result means

Seed or mixed charts illustrate the concept; they do not establish your skill or platform-wide accuracy. A standard binary Brier score is the mean of (forecast − outcome)², with outcomes 0 or 1. Lower is better for the same evaluation set; compare with a baseline.

If something goes wrong

If live data is absent, read the seed label literally. Do not report a demonstration score as a measured result. Reloading cannot turn seed data into validated history.

Check your understanding

A 70% forecast scores 0.09 for YES and 0.49 for NO. Calculate both, then start a dated paper journal of ten questions.