June 2016: This explanation from 2012 captures the concept of the Bayesian predictor, but in 2016 the prior is set differently. As of now, I am using national Clinton v. Trump poll median for all 2016, along with a large SD (+/-7%), to set a fairly weak prior. This assumption will eventually be replaced with statistics on the Meta-Margin history once there’s enough of that to be useful.
This prediction is based on the amount that the Meta-Margin is likely to shift over short periods of time, emphasizing the limits set by the long-range prediction. As of today, the predicted “strike zone” is 314-347 EV and the November Obama re-elect probability is 97%.
The rest is very math-y…
OK, you asked for it.
During 2012, the Obama-Romney Meta-Margin’s typical movement (the standard deviation) has been about 1% in 1 week, and about 1.8% in 3 weeks or longer. On average, the movement forward in time has been near zero, as shown by the black curve in the middle of this plot.
As an example, right now the Meta-margin is 5.04%, and the election is 38 days away. Therefore movement in either direction today of +/-1.8% leads to a 1-standard-deviation (SD) range of Obama +3.24 to +6.84%.
The long-range prediction, which you’ve been watching for weeks, excluded the upper part of this range, suggesting that movement above +6% is relatively unlikely. So that part gets compressed. This is done by using the long-range expectation as a “Bayesian prior,” whose distribution is multiplied by the movement-from-today distribution. This gives the actual prediction. As the election draws near, the red curve below will move toward the black curve, which itself will become very narrow.
This allows us to calculate a win probability. Based on Drift-from-now alone, the win probability is 97%. If we use the Bayesian prior to sharpen things up, it becomes 99%. To be conservative (in the nonpolitical sense) I report 97% in the topline for nontechnical readers.
Then it is necessary to convert the predicted Meta-Margin range to electoral votes. This is possible using the relationship between the two quantities as the campaign unfolded this year:
This plot shows all available data since June. Data from mid-August were used for extrapolation.
The end result is the electoral vote (EV) range shown in the red “maximum strike zone” above. This is where the Presidential election is most likely to end up (68% confidence interval).
The yellow zone above is more complicated. It starts from the 95% range, calculated in the same way. This is combined with today’s 95% nominal confidence interval, the gray zone you’ve been seeing all along, which includes pollster-to-pollster variations. The yellow zone is defined as the union of these two ranges. Therefore pollster variation and the maximum possible drift are both contained in this wider “watch zone.”
These red and yellow zones will be updated from now until Election Day.
For geeks, an even more technical description and MATLAB script are provided here.