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Models & methods

What each method is for, what zero-shot changes, and why production keeps more than one model in the race.

10 min

Forecasting models compared

Classical models are interpretable and cheap. Machine learning eats more drivers. Foundation models arrive pretrained and can go zero-shot. None of them win every series — which is why serious stacks keep a tournament, not a favorite.

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8 min

Zero-shot forecasting

Zero-shot means you get a forecast without training on your series first. A foundation model uses what it learned from many other series, then reads yours. Fine-tuning is the later step, once you have enough of your own data to make it worth the spend.

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7 min

Why one model never wins

A model that dominated last spring can lose in November. Series change, drivers change, and luck exists. Keep a challenger on the same folds, promote on evidence, and stay loyal to the score — not to the architecture that won a bake-off in March.

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Glossary in this topic

Ensemble Foundation model Zero-shot forecasting Fine-tuning Champion–challenger

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