His model predicted a Trump win. So what’s it say NOW?

By Dan Cirucci | via Dan Cirucci’s Blogspot

Stony Brook University Alumni Association;Cocktail Reception and Panel Discussion  "Forecasting the 2012 Presidential Election."At the office of Stony Brook Alumnus, James Keneally, '79 - Partner, Kelly Drye LLP101 Park Avenue (Between 40th and 41st)New York, NY 10178Featuring:Political Game Theory:Sandro Brusco, PhD, Professor and Chair, Economics2012 Presidential Election Forecast:Helmut Norpoth, PhD, Professor, Political ScienceMatthew Lebo, PhD,  Associate Professor and Acting Chair, Political Science
Photo Credit: Stony Brook University Alumni Association

Remember the political science professor who came forward in February with a prognosticating model that virtually guaranteed a Trump victory in November?

Stony Brook University’s Dr. Helmut Norpoth has reportedly claimed that the model he uses (tied to election cycles) has correctly called the results of every election except for one in the last 104 years. Th exception was 1960 when Kennedy defeated Nixon by an eyelash.

Earlier this year, based on that model, Dr. Norpoth said there was a 97 to 99 percent chance Trump would be the next President of the United States.

But we hadn’t heard much from the good professor since then. Yes, there was a burst of national (and even international) news about the model’s prediction when the story first emerged but since then, crickets.

So, we asked Dr. Norpoth “Does your prediction still hold. What does the model predict right now, today?”

And here’s his answer:

“I am stuck on Trump with 87% certainty. Come hell or high water. My model may self-destruct but it is not for updating.”

So, you heard it here first. An 87% chance (slightly down from that all-but-certain 97-99%) that Trump will win. Those are still damned good odds.

And, should the model “self-destruct,” well it won’t be the first thing to self-destruct this year and it may not be the last.

Fasten your seatbelt, everybody! We ain’t seen the end of the tumult.