If Republican and Democratic voters had their primaries to do over again ... the results would probably look pretty much the same, according to a HuffPost/YouGov survey.
Plenty of Republican and Republican-leaning voters are less than thrilled with their presumptive nominee. While 44 percent consider him the best option out of this year's pool of candidates, an equal 44 percent say he wasn't the best choice, according to the survey, which was taken June 7-9.
But just like the first time around, the opposition to Trump remains hopelessly divided. Asked who they would most like to see as the nominee if they could start the primary from scratch, 29 percent picked Trump and 15 percent picked Sen. Ted Cruz (R-Texas). Ohio Gov. John Kasich took 9 percent, followed by former neurosurgeon Ben Carson and Florida Sen. Marco Rubio at 8 percent each. The rest of the pack failed to make it past 5 percent.
Democrats are more content with the results of their primary, although a significant minority remain unhappy. Fifty-six percent of Democratic and Democratic-leaning voters say that Clinton was their party's best option, while 32 percent don't think she was.
Given the option for a mulligan, 50 percent still chose Clinton, with 29 percent picking Sanders and a handful opting for one of the other contenders.
The HuffPost/YouGov poll consisted of 1,000 completed interviews conducted June 7 through June 9 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.