**Sam Wang**: *Is 99% a Reasonable Probability?*: "Three sets of data point in the same direction:

- The state poll-based Meta-Margin is Clinton +2.6%.
- National polls give a median of Clinton +3.0 +/- 0.9% (10 polls with a start date of November 1st or later).
- Early voting patterns approximately match 2012, a year when the popular vote was Obama +3.9%.
Based on this evidence, if Hillary Clinton does not win on Tuesday it will be a giant surprise.

There’s been buzz about the Princeton Election Consortium’s win probability for Clinton, which for some time has been in the 98-99% range. Tonight let me walk everyone through how we arrive at this level of confidence. I will also give a caveat on how it is difficult to estimate win probabilities above 90%. An obvious contrast with PEC’s calculation is the FiveThirtyEight win probability, which has been in the 60-70% range....

We start by generating the sharpest possible snapshot, based on state polls.... The snapshot gets converted to a Meta-Margin, which is defined as how far all polls would have to move, in the same direction, to create a perfect toss-up. The Meta-Margin is great because it has units that we can all understand: a percentage lead. At the moment, the Meta-Margin is Clinton +2.6%.... To turn the Meta-Margin into a win probability, the final step is to estimate how far the results of tomorrow’s election will be from today’s Meta-Margin. As a community, pollsters have pretty good judgment, but their average estimate of who will vote may be off a little. In past years, the snapshot has been quite good, ending up within a few electoral votes of the final outcome. That is equivalent to an uncertainty of less than one percentage point....

To turn the Meta-Margin into a hard probability, I had to estimate the likely error on the Meta-Margin. For the home stretch, the likely-error fomula in my code assumed an Election Eve error of 0.8% on average, following a t-distribution (parameter=3 d.f.). The t-distribution is a way of allowing for “longer-tail” outcomes than the usual bell-shaped curve. So... there’s only one parameter to estimate. Again, hooray! However, estimating it was an exercise in judgment, to put it mildly....

However, a 5% across-the-board error in state polls, going against the front-runner, has no precedent in data that I can see. Bottom line: Using the Princeton Election Consortium’s methods, even the most conservative assumptions lead to a Clinton win probability of 91%.