Right now, for instance, polls are pretty clear on the fact that most potential Democratic voters haven’t made up their minds.

Early horserace polling gets a bad rap. But far from being useless, it’s often excellent at providing a snapshot of the opening stages of a campaign.

Zoonar RF via Getty Images Posting a strong showing in early polls is certainly better news for a candidate than languishing near the bottom.

That lines up with other data suggesting that, when given the option to express some uncertainty about their jam-packed field of options, a lot of voters will take it. In a recent Economist/YouGov survey that asked Democratic primary voters to choose all the candidates that they might consider backing, just 27% picked only a single name. Most were weighing multiple options, often across ideological lines ― half of those considering Biden, for instance, also said they’d be open to voting for Vermont Sen. Bernie Sanders.

And when a Washington Post/ABC poll released this Monday asked an open-ended question about the primary, they found that 54% of Democratic and Democratic-leaning independents didn’t have any particular name in mind.

“[T]he high and persistent level of uncertainty suggests that many Democratic voters are considering multiple options or have yet to pay much attention nine months before the Iowa caucuses,” The Washington Post’s Scott Clement and Dan Balz wrote. “It also indicates that support for most candidates is more tenuous than suggested by surveys that ask respondents to choose among the lengthy list of Democratic contenders.”

That dynamic is present even in the early-voting states that have already seen significant attention from the campaigns. In New Hampshire, where candidates have made hundreds of visits, just 9% of Democratic primary voters say they’ve made up their minds about whom they’ll vote for, according to the Granite State Poll. Another 14% are leaning toward someone, but the vast majority, 77%, are still trying to decide. (They’re unlikely to rush: In 2016, nearly half of Democratic voters in the state told exit pollsters they hadn’t made up their minds until a month or less before the election.)

It’s not that early primary polls have no predictive value: In recent history, at least, they often have. Per analysis from CNN, even two years out, the vast majority of candidates who’ve gone on to win their parties’ primaries were already polling in their party’s top three.

“[N]ational surveys conducted in the year before a presidential primary are relatively good indicators of which candidates will advance to the general election, especially when polling averages are adjusted to reflect how well known each candidate was,” FiveThirtyEight’s Geoffrey Skelley concluded earlier this month after reviewing primary polls dating back to 1972.

At this point in 2015, of course, the GOP field was still a tenuous jumble of candidates. But by late summer, Donald Trump was visibly rising to the top of the pack ― a lead that he never ended up relinquishing, despite repeated predictions of his downfall.

Posting a strong showing in early polls, in other words, is certainly better news for a candidate than languishing near the bottom. Biden could consolidate his lead just as easily as he could be superseded by one of his rivals. But right now, there’s still ample time, and far more than enough ambivalent voters, for either of those things to happen.

The HuffPost/YouGov poll consisted of 1,000 completed interviews conducted April 23-24 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.

HuffPost has teamed up with YouGov to conduct daily opinion polls. You can learn more about this project andtake part in YouGov’s nationally representative opinion polling. More details on the polls’ methodology are availablehere.

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.