[_delirium]

> So the order that results come in should not affect the prediction.

This model uses a frequentist prediction interval, which assumes independently drawn samples, meaning reporting order must be random for the assumptions to be valid. If reporting is non-random, e.g. how early or late a district reports is correlated with things like region, demographics, population density, etc., then the prediction interval is probably narrower than it should be, especially early on in the reporting (meaning the model is overconfident in its prediction).

The headline prediction is more robust if you just want to know which outcome is more likely given current results, but the probabilities being badly calibrated due to these kinds of model assumptions is a common issue in quantitative polisci models.