No matter who wins the presidential election on Tuesday, fewer than one-third of the public is going to be excited about the results, a new HuffPost/YouGov survey finds.

Just 24 percent of Americans say they’ll be enthusiastic if Hillary Clinton wins the presidential election, while just 20 percent would be enthusiastic about a Donald Trump victory. Thirty-five percent would be outright upset if Clinton wins, while 44 percent say the same of Trump.

Overall, Americans’ feelings on the prospect of a Clinton victory are split: 46 percent of Americans would be at least satisfied if she wins, while 47 percent would be dissatisfied or upset. The majority, however, would be unhappy to see Trump elected. Just 38 percent would be at least satisfied to see Trump elected, while 55 percent would be either dissatisfied or upset.

As might be expected in such a polarizing election, most Americans have a strong preference one way or the other. Just 4 percent would be at least satisfied with either possible election outcome. Thirty-four percent would only be satisfied with a Trump win, while 41 percent would only be satisfied to see Clinton elected, and 14 percent wouldn’t be happy either way.

Voter enthusiasm as a whole is down compared to four years ago. Fifty-one percent of registered voters described themselves as “extremely enthusiastic” or “very enthusiastic” about voting, down from 73 percent in the final Economist/YouGov poll taken before the 2012 election. But despite the significantly lowered enthusiasm, voters aren’t paying any less attention ― 58 percent say they’re following news about the election very closely, compared to 55 percent in 2012.

Americans’ general lack of excitement about either candidate may bode poorly for the next president’s job approval, and the relatively dampened enthusiasm for voting may explain why the vast majority of Americans wish the election were over. But, despite the plethora of ink spilled over voter enthusiasm, it may not be a particularly useful metric for predicting who’ll turn out to vote.

After polls understated President Barack Obama’s margin of victory in 2012, some onlookers, including Obama pollster Joel Benenson, concluded that likely voter models measuring voters’ self-reported levels of attention and enthusiasm were part of the problem.

“I’m not very enthusiastic about using enthusiasm” to measure who’s likely to turn out to vote, said Lee Miringoff, director of the Marist Institute for Public Opinion, which doesn’t use it as part of their likely voter model. “I think it’s more fear of the other than enthusiasm for the person they’re supporting.”

This year, negative emotions may be just as likely as positive ones to drive people to the polls. Surveys have found that many voters, especially those backing Trump, are driven as much by distaste for their rival as they are by support for their candidate.

Earlier this year, 53 percent of Trump voters said they were mostly voting against Clinton, and 46 percent of Clinton voters that they were mostly voting against Trump according to a Pew Research survey. In 2008, just 35 percent of McCain supporters, and 25 percent of Obama supporters, said they were voting largely against the opposing candidate.

The HuffPost/YouGov poll consisted of 1,000 completed interviews conducted Nov. 3-5 among U.S. adults, using a sample selected from YouGov’s opt-in online panel to match the demographics and other characteristics of the adult U.S. population.

The Huffington Post has teamed up with YouGov to conduct daily opinion polls.You can learn more about this project and take part in YouGov’s nationally representative opinion polling. Data from all HuffPost/YouGov polls can be found here. More details on the polls’ methodology are available here.

Most surveys report a margin of error that represents some, but not all, potential survey errors. YouGov’s reports include a model-based margin of error, which rests on a specific set of statistical assumptions about the selected sample, rather than the standard methodology for random probability sampling. If these assumptions are wrong, the model-based margin of error may also be inaccurate. Click here for a more detailed explanation of the model-based margin of error.