[dragonwriter]

> Comparing models across multiple elections and calculating the Bayesian regret is one way to do it. The models get tweaked each election so this isn’t exact,

As long as the same inputs aren’t fundamentally unavailable (and even then if the model has systematic handling of missing data, though the validity of that comparison is less clear) you can run the tweaked model on past elections (the main problem there is since those are probably the data used to generate them, it rewards overfitting; you might do better by running them against past elections with differing sets of random dropout of input data points [individual instances of particular polls, etc.] to mitigate that.)