Princeton's Sam Wang Said He'd Eat A Bug If Hillary Lost—Watch Him Do It
November 12, 2016, 05:25 PM
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From Wired last Monday, an article in praise of forecaster Sam Wang, who gave Hillary a 99% chance:
2016’s Election Data Hero Isn’t Nate Silver. It’s Sam Wang

Forget Nate Silver. There’s a new king of the presidential election data mountain. His name is Sam Wang, Ph.D.


Jeff Nesbit is executive director of Climate Nexus, a DC-based communications firm focused on climate change. He was the communications director to former Vice President Dan Quayle (R-IN) at the White House and the legislative and public affairs director at the National Science Foundation. He is the author of Poison Tea: How Big Oil and Big Tobacco Invented the Tea Party and Captured the GOP.

Haven’t heard of him just yet? Don’t worry. You will. Because Wang has sailed True North all along, while Silver has been cautiously trying to tack his FiveThirtyEight data sailboat (weighted down with ESPN gold bars) through treacherous, Category-Five-level-hurricane headwinds in what has easily been the craziest presidential campaign in the modern political era.

When the smoke clears on Tuesday—and it will clear—what will emerge is Wang and his Princeton Election Consortium website and calculations (which have been used, in part, to drive some of the election poll conclusions at The New York Times’ Upshot blog and The Huffington Post’election site). What will be vindicated is precisely the sort of math approach that Silver once rode to fame and fortune.

Wang says his method differs from Silver’s in its approach to uncertainty. “They score individual pollsters, and they want to predict things like individual-state vote shares,” he wrote in his blog on Sunday. “Achieving these goals requires building a model with lots of parameters, and running regressions and other statistical procedures to estimate those parameters. However, every parameter has an uncertainty attached to it. When all those parameters get put together to estimate the overall outcome, the resulting total is highly uncertain.” By contrast, he says, PEC’s model relies on a snapshot of all state polls every day, and then makes sure unrelated fluctuations are averaged out.

… Most likely, it’s because presidential forecasting isn’t Wang’s real job. He’s a professor of neuroscience at Princeton. …

This year, Wang called the election at 8:55 PM on October 18. He promised to eat more than just his hat if Clinton loses: “It is totally over. If Trump wins more than 240 electoral votes, I will eat a bug,” Wang tweeted to his 23,000 followers. He expects Clinton to receive at least 298 electoral votes.

When Michigan is eventually called for Trump, he will have 306 Electoral Votes.
Wang has been the intrepid election data explorer furthest out this election cycle, never once wavering from his certainty of a Clinton win. The only real uncertainty left on Tuesday, he said, is how many people show up to vote. But even that doesn’t change the presidential election outcome.

… Even if you factor this voting uncertainty into his election model by 5 percent—which is an unprecedented level historically, Wang says—Clinton still wins. It is precisely this sort of deep analysis that has endeared Wang to both financial analysts who make a living with math-based market predictions and to political journalism analysts who handicap elections. …

Wang has said for months that it was a five-point race; that there haven’t been dramatic swings in polling, only non-responses from depressed voters in the middle of news cycle swings; and that this has actually been the most stable election in a long time. What’s different, Wang has said to those willing to listen, is the media coverage of the “full meltdown” of emotion as Trump has seized control of the GOP. …

Natalie Jackson, the senior polling editor at The Huffington Post, told me that Wang uses the HuffPost Pollster data feed and that they both use the same polls, which explains the similarity.1 “Our forecast has been in line with Sam’s for most of the time it’s been up (we posted Oct. 3), and our probability of Clinton winning never dipped below 84 percent,” she said. “The polling data has never consistently shown anything but a Clinton win.”

Jackson, who coordinates site’s Pollster section, said that the data is truly what matters, and it’s been consistent at the presidential level. “With everything we know about polling in general elections—that opinions are fairly stable, and fluctuations in national polls aren’t necessarily reflecting people changing their voting decisions—it makes sense to keep a calm, steady approach to aggregating and forecasting,” she said. “It might not be the best way to generate news, but it’s a very good way to model noisy data.”

The Huffington Post Washington bureau chief Ryan Grim has been in a very public feud with Silver in recent days over precisely this question of “noisy data.” Grim accused Silver of deliberately skewing his own data at FiveThirtyEight with what amounts to political punditry. Silver fired back on social media with some ugly language. G

Silver, after blowing the Republican primary, gave Trump a higher chance to beat Hillary than his rivals did, some of whom denounced him for giving aid and comfort to Trump supporters.
So when the smoke clears on Tuesday; when enough non-white and female voters haven’t been harassed or intimidated enough to stay home; when Clinton crosses the finish line with something close to 300 Electoral College votes and a popular vote victory somewhere between two and five percentage points; and Nate Silver is telling his 1.7 million Twitter followers that he’d been right all along this election, Sam Wang will be standing tall above the fray, draped in his “median-based probability election” cloak.

Long live the new election data king.