Jay Cost has a smart post about numbers, dynamics, and the humility of predictions:

I agree that Clinton is more likely to lose than win. I also do not necessarily disagree with these low estimates. However, I disagree with the way these estimates are occasionally presented. There is sometimes an implication that these are precise predictions - when in fact a prediction like this must be very imprecise. This is why I was so vague in offering my own estimate last week.

There are reasons to expect imprecision in this kind of situation. Precision depends in part on the number of variable factors that create that which we are predicting. The more things that must happen for the prediction to come true, the less precise it is. Take an example. Suppose we are predicting whether a pitcher will strike out a batter. We can be reasonably precise. After all, there are just two factors to account for - the pitcher and the batter. Suppose, on the other hand, we're predicting who will win the World Series. Precision is very difficult here. After all, our prediction depends on thousands of factors shaking out in a certain way.

As if on cue, Slate has launched its clever (yet un-counterintuitive!) Hillary Deathwatch which calculates that Clinton's chance of winning the nomination is 12 percent.

Not 13 percent. Not 11.5 percent. 12 percent.