Welcome back! We didn't provide any predictions for the recent Nevada Republican caucus, because there were too few polls on which to base our models. So on we go to the upcoming South Carolina Democrat primary. Both our models forecast blowout victories for Clinton, compared with the poll averages, because of last minute movement towards Clinton. Here are the numbers:
Model 1 - Clinton 75.2%, Sanders 24.8%
Model 2 - Clinton 69.8%, Sanders 30.2%

We thought it would be interesting to provide the probability of each of the remaining 7 presidential candidates achieving the nomination of his or her party. We based a simple model on two criteria: 1) how many delegates has each candidate accumulated so far as a fraction of the total needed to secure a majority; and 2) the current standing in the national polls. Here is the result.

Clinton has the highest probability of achieving her party's nomination. However, her direct competitor Sanders is only about 5 points behind. Trump's probability of winning is a bit lower, but in a much larger field; his probability of winning is more than the second place and third place combined. Of course these numbers will be updated after delegates are awarded in the SC primary. After that, Super Tuesday is make or break for Kasich and Carson.

(Updated Feb. 19) We have been using two models so far with relative success. In Nevada, the predictions are:
Model 1 - Clinton 54.7, Sanders 45.3
There is not enough data to run model 2 in Nevada. In South Carolina, the predictions are:
Model 1 - Trump 28.8, Rubio 21.7, Cruz 17.6, Kasich 11.8, Bush 11.7, Carson 8.4
Model 2 - Rubio 27.7, Trump 26.6, Cruz 17.9, Bush 11.4, Kasich 9.5, Carson 6.9
In model 2, Rubio gets a significant surge due to stronger performance in the last few days, perhaps because of Governor Haley's endorsement.

Let's review our performance in New Hampshire.

Our models slightly underperformed the forecasts of Real Clear Politics and the Huffington Post, because of a last minute fall in support for Rubio; not only did he lose undecided voters, he also lost some of his previous support. However, the cumulative track record of our models is still better than the published averages. That is likely to be tested severely this weekend, so stay tuned. We hope to have forecasts for you next week of the SC Democrats and the NV Republicans.

Above are my forecasts for the outcomes for today's New Hampshire presidential primaries. The model 2 forecasts were so accurate in Iowa that I am publishing only model 2 this time (although I computed model 1 for reference). Noteworthy are a very slight closing of the gap on the Democrat side; and on the Republican side, a last-minute surge for Rubio, a slight surge for Kasich, and collapses for Christie, Fiorina, and Carson. These last 3 candidates will find it hard to go on after today. (NH pollsters have not been asking about Gov. Gilmore, who is at 0% nationally, and won about 0.01% of the vote in Iowa.)

Dr. Carson's campaign has suffered from a lack of attention not consistent with his 4th place position nationally. I noticed a disparity in the number of minutes each candidate was given in the last 3 Republican presidential debates. Dr. Carson received less than half the time given to the most voluble speaker; see below.

Last but not least, the Super Bowl. We were off by only 22 points... The p-value for the observed outcome was .1169, not significant. This reflects the enormous width of the prediction interval, plus or minus 28 points. Back-testing the model, it we got the right winner only once in the last 4 years. It seems that we need a new model! I think I'll wait until after the election in November.

I'll see you after New Hampshire votes are counted to see how our forecast did versus the polls, Real Clear Politics, and the Huffington Post.

OK, it doesn't get any better than this - presidential primaries and the Super Bowl! Let's get started.

The above graph represents a normal approximation to the victory margins achieved by the Carolina Panthers (blue) and Denver Broncos (red) this season. The call: Carolina by 7-8 points. 95% prediction interval: anywhere from a 35-point victory by Carolina to a 20-point victory by Denver. Last year, my model called the correct winner, and the actual victory margin differed from the predicted by just 2 points!

Next, let's call the Iowa caucuses, based on polling data from the last 4 weeks in Iowa.

The data labels show the predicted vote shares by the 3 Democrat and 12 Republican candidates in Iowa; all numbers have a margin of error of 4.5 points. Clinton should achieve a 4.5-point victory over Sanders, while Trump scores a 7.5-point victory over Cruz. Based on the Zipf's law model we discussed in an earlier post, it appears that Sanders is mounting a very strong challenge to Clinton, as are both Cruz and Rubio to Trump.

We hope to analyze the data after the vote, to see which of the polls - or the forecast above - made the most accurate call, as well as to see which types of polling may be more accurate.

Update (later the same day): I have a new model capable of detecting changing direction in the polls. If the new model is correct (and we'll discuss that after the voting), the margin for Clinton will be a mere 1.7 points, while Trump barely edges out Cruz by 2.0 points, in a near 3-way tie with Rubio. Below are the graphs - check back to see which model was more accurate.

OK, one more update, one more model. We'll see tomorrow how this model fares against the other two and the polls and the results.