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2012 US election a 'Moneyball' win for geeks
by Staff Writers
Washington (AFP) Nov 7, 2012

Nate Silver's model correctly predicted the presidential outcome in 49 states, and will be correct in all 50 if Obama's lead holds in Florida.

It was not just a victory for President Barack Obama, it was validation for the number-crunchers and statistical model geeks, including a New York Times blogger who became a target for conservatives.

Tuesday's election made a star out of Nate Silver, whose FiveThirtyEight blog for the US daily tracked the president's statistical odds and on election day offered a 90.9 percent probability of an Obama win.

Silver's model correctly predicted the presidential outcome in 49 states, and will be correct in all 50 if Obama's lead holds in Florida.

"Here is the absolute, undoubted winner of this election: Nate Silver and big data," said Chris Taylor in an opinion column on the website Mashable.

"What does this victory mean? That mathematical models can no longer be derided by 'gut-feeling' pundits. That Silver's contention -- TV pundits are generally no more accurate than a coin toss -- must now be given wider credence."

It was a similar result for three other models, including from Princeton University neuroscientist Sam Wang, Stanford's Simon Jackman and Emory University's Drew Linzer.

The results evoked the popular book and film starring Brad Pitt "Moneyball," which showed how statistical models can help win in baseball.

Obama's victory "is also a victory for the Moneyball approach to politics," said John Sides, a political scientist at George Washington University.

"It shows us that we can use systematic data -- economic data, polling data -- to separate momentum from no-mentum, to dispense with the gaseous emanations of pundits' 'guts,' and ultimately to forecast the winner," he said in a blog post.

In the weeks leading up to the election, Silver -- whose FiveThirtyEight blog is named geekily after the number of electoral college votes up for grabs -- and others had been pilloried by conservative commentators.

"The mainstream media-commissioned polls have been far more skewed this election season than most in the past," said conservative analyst Dean Chambers on September 26, as he predicted a win for Republican Mitt Romney.

Chambers, seen as the head of the so-called "unskewed movement," on Monday predicted a narrow Romney win in electoral votes.

Conservative consultant Dick Morris had argued that the polls "understate" the number of people who favored Romney, and ahead of the election predicted a "landslide" for the Republican.

"All of the polling out there uses some variant of the 2008 election turnout as its model for weighting respondents and this overstates the Democratic vote by a huge margin," Morris said in September.

On Wednesday, Morris acknowledged he was wrong: "I've got egg on my face," he said, arguing that the impact of superstorm Sandy "stopped Romney's post-debate momentum."

The predictions from Silver and other analysts -- who for the technically literate use techniques known as quantitative forecasting or Bayesian analysis, named for mathematician Thomas Bayes -- drew wide audiences during the campaign, and prompted many to place bets on accuracy.

Former Republican congressman called Silver an "ideologue" on MSNBC and bet Silver $1,000 on the race.

Princeton's Wang said he would "eat a bug" if Romney won Ohio, and expressed relief on Wednesday after the results.

Wang had accurately predicted 49 states and called Florida "a tossup." He had on Tuesday given a 99.2 percent probability of Obama's re-election.

The popular vote total giving Obama a slight edge "exactly matches my prediction," Wang said. "Bottom line: I will not have to eat a bug."

Yet some said the four predictions were simply aggregations of individual polls, and cautioned against giving too much credit to the aggregators.

George Washington University political scientist Henry Farrell said the popularity of these systems might lead to "less incentive to produce these individual polls" and make the predictions less accurate.

"The models might, over the longer term, drive the individual polls out of the market, cannibalizing the conditions of their own existence unless someone figures out a new business model," Farrell said.


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