Trap One: Extrapolating Past Your Data
This is the big one. A model is only tested where you actually measured. Use it between your data points — that's interpolation, and it's usually fine. But stretch it far beyond the last point — that's extrapolation — and you're guessing about territory the model has never been checked in. A trend that looks perfectly straight across the range you measured can quietly bend the moment you leave it. Predict a bean plant's height at 100 litres of water a day from data taken between 0 and 2 litres, and the model will happily promise you a beanstalk to the moon. Reality drowns the plant.
Trap Two: Garbage in, Garbage Out
A model is only ever as good as the data you fed it. Measure carelessly, or with a dodgy instrument, or only on a Tuesday, and the model faithfully learns your mess. It can't tell good data from bad — it just fits whatever it's given. So a confident-looking prediction built on rubbish measurements is still rubbish, dressed up in a tidy line. Garbage in, garbage out. Before you trust any prediction, ask what data it was built on.
And the Quiet One: Correlation Still Isn't Causation
Just because two things rise together and your model fits them beautifully, it does not mean one causes the other. Ice-cream sales and shark attacks both climb in summer, and you could fit a gorgeous line between them — but ice cream doesn't summon sharks. Hot weather drives both. A model can capture a pattern without capturing a cause, and using it to claim “more X makes more Y” is a trap even when the fit is flawless.
A Depth Study to Take It Further
If you want to chase this one down: pick any real model you can find a prediction from — a weather forecast, a sports tipping model, a “your phone battery will last X hours” estimate — and log its prediction against what actually happened over a week. Where did it stay honest, and where did it drift? Was the drift worst when it reached furthest ahead? That little logbook is exactly how real scientists keep their models honest, and it's a tidy depth study to write up.