Election Prediction: Nate Silver Gives Clinton A 70 Percent Chance Of Winning Based On Latest Polls


Polling guru and FiveThirtyEight editor Nate Silver is giving Democratic presidential candidate Hillary Clinton a 70 percent chance of winning the election based on the latest polling to come out on the eve of Election Day.

“Hillary Clinton has a 70 percent chance of winning the election, according to both the FiveThirtyEight polls-only and polls-plus models,” Silver proclaimed in an article posted to the site Monday. “That’s up from a 65 percent chance on Sunday night, so Clinton has had a good run in the polls in the final days of the campaign.”

Silver also noted that Clinton’s projected margin of victory in the popular vote had increased from 2.9 percent to 3.5 percent in recent days.

An election prediction is often a tricky proposition, but Nate Silver boasts a pretty impressive record when it comes to projecting political winners. For instance, a previous post on FiveThirtyEight points out that Silver’s team accurately predicted the outcomes of 91 percent of caucus and primary contests to date in 2016.

Part of his success comes from his years as a sports statistician and his emphasis on data journalism, which he describes as the tendency to “apply the scientific method to the news.”

In this case Nate Silver, and Clinton supporters, can take comfort in knowing that FiveThirtyEight is not alone in suggesting that the Democratic candidate will indeed win the election.

RealClearPolitics‘ (RCP) polling aggregate doesn’t offer an outright election prediction, but it does provide a running average of poll results. As of this post, RCP gives Clinton an aggregate lead of 3.3 percentage points over Republican rival Donald Trump, suggesting their data corresponds very closely to that of FiveThirtyEight.

In terms of state-by-state match-ups, RCP’s “Battle for the White House” Electoral College map shows Clinton going into Election Day with a secured Electoral College vote lead of 203 to 164 over Trump, with the remaining 171 Electoral College votes left to swing states.

Trump would have to win 106 of those remaining 171 votes to take the White House. That’s tough math, especially for someone who is trailing by several points in many swing states.

There is one big caveat to all of this. If you take all the “swing” out of the swing states and assign them to a candidate based on whomever is currently leading in that state, regardless of how thin the margin may be, the Electoral College map gets a lot tighter — a whole lot tighter.

According to RCP’s “No Toss Up States” map, Clinton leads Trump by only 272 Electoral College votes to 266. A candidate needs 270 Electoral College votes to win, meaning she would secure the presidency if these numbers held, but that’s a much closer race than the election prediction Silver lays out.

In general, however, Nate Silver’s election prediction arguably carries more weight than the RCP averages because it take other factors into consideration with polling data. He takes not only the polls themselves but trends and margins into account when making an election prediction.

“As a lot of you noticed, Nevada, North Carolina and Florida flipped from red to blue over the course of Monday,” he writes in the post predicting Clinton will win the election. “We don’t think that’s a particularly meaningful metric, because the forecasts are probabilistic — Clinton’s chances of winning Florida increased to 54 percent from 48 percent, for instance, which is nontrivial but not an especially large change.”

And he also takes acknowledges the fickle nature of election polls.

“It’s unlikely that any further states will flip to Clinton in our final forecast, as she’s too far behind in Ohio, the next-closest state,” Silver says. “It’s possible that Florida and North Carolina could flip back to Trump by tomorrow morning, though probably not Nevada, where Clinton’s lead is a bit larger.

One way or the other, we have less than 24 hours to wait and see if Nate Silver proves himself right on yet another election prediction.

[Featured Image by Drew Angerer/Getty Images]

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