Prequential log score identity (${\sum }_t\log p(y_t\mid y_{<t})=\log p(y_{1:T})$)

The probability chain rule makes a sum of sequential predictive log scores equal the log Bayesian model evidence when the forecasts are coherent Bayesian one-step predictions under proper priors. Differences of total scores are therefore log Bayes factors.