These are the updated probability obtained running the Python code that computes the Bayesian posterior distribution over the electoral votes using near-ignorance priors. The worst and best case distribution for Clinton are in red and respectively, blue..

- Winning probability above 0.99 (for both worst and best scenario).
- Electoral votes between 322 and 335 (mean of the worst and best distribution)

The state-by-state situation is here

Code and Data are on my Github repo https://github.com/benavoli/blog