There are a number of other statistical forecasting systems, most of which rely on polls, economic variables or some combination thereof.
I tracked down about every one of these models that I could find, subject to the condition that it couched its forecast in probabilistic terms (or that it was well-documented enough to allow this to be inferred with relative ease, like from the standard error that the model stated).
In my view, it’s in estimating the uncertainty in a forecast where most of the challenge and intrigue lies. To paraphrase Charles Barkley, any knucklehead can make a point prediction — but it takes brains to calculate a confidence interval.
These models are all over the map, forecasting everything from a nearly certain Obama victory to the substantial likelihood of his defeat. But more of them have Mr. Obama as the favorite. If you simply average their win probability estimates together, you get about a 61 percent likelihood of his winning the election.