Predictive Modeling.
Forecasts with a scoring rule attached — calibration, Brier scores, market baselines.
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A forecast without a scoring rule is an opinion with decimals. Prediction is one of the few areas where honesty can be measured directly — so we measure it.
What this field actually measures
- Brier score
Mean squared error of probabilistic forecasts.
ReferenceCompared against a baseline such as the historical base rate or the market.
- Calibration curve
Predicted probability plotted against observed frequency.
ReferenceA well-calibrated 70% call should land about 70% of the time.
- Market baseline
Prices from liquid betting markets as a comparison forecast.
ReferenceA hard benchmark to beat, and the honest yardstick for any public model.
Evidence & metrics
The published work behind the numbers above, and the public datasets you can open to check us. If a claim can’t be traced here, we don’t print it.
Citations
Verification of forecasts expressed in terms of probability
Brier — Monthly Weather Review · 1950
Defined the Brier score, the standard measure of probabilistic forecast accuracy.
Superforecasting / the Good Judgment Project results
Tetlock & Mellers et al. — Science and subsequent reports · 2014–2015
Calibration training and aggregation measurably improved forecast accuracy over expert intuition.
Datasets
Metaculus public forecast archive
Metaculus · free
Resolved questions with full probability histories and scoring.
FiveThirtyEight data repository
FiveThirtyEight · free
Published forecast outputs and the raw inputs behind them.
Still open
- How should public predictions be archived so they cannot be quietly revised?
- What horizon makes sports forecasting meaningful rather than decorative?
- Where do human analysts still beat models, and why?
What we won’t say
We will not publish a prediction we are not willing to score in public afterwards.
- VO-1Evidence before wit
- VO-2Punch at claims, never at people
- VO-3Say the uncertainty out loud
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