MASSIVE New Poll Shows Trump Getting Crushed By Blue Wall Bulwark Takes

[Jmb 4 Harris-Walz]

Tim Miller

[Fiendish Thingy]

1. 2-3% lead with a 4% MOE isn't exactly"getting crushed" nt

[TwilightZone]

3. Great minds and all that...

I should have refreshed before submitting my post, though it's a point that should be made.

It's no wonder that people get unrealistic expectations.

[OKIsItJustMe]

5. It isn't of course

On the other hand a lot of people were getting depressed when the polls were the other way. (i.e. Harris was down 2 point.) It really is a “Margin of Error Election.”

I loved David Brooks’ comment a few weeks ago to the effect that, “This campaign started out tied, and has only gotten closer since then.”

[Earthrise]

11. It's the title of the video - Tim Miller named it

I usually avoid any and all videos using overly dramatic titles - crush, destroyed, etc.

[TwilightZone]

2. A 2-3% lead in polls that have an MOE isn't even remotely "crushed"

This isn't helping.

[NoRethugFriends]

4. Just check the poster's bio

[OKIsItJustMe]

6. Sources

FWIW:

• https://maristpoll.marist.edu/polls/marist-pennsylvania-poll-u-s-presidential-contest-in-pennsylvania-november-2024/
• https://maristpoll.marist.edu/polls/marist-michigan-poll-u-s-presidential-contest-in-michigan-november-2024/
• https://maristpoll.marist.edu/polls/marist-wisconsin-poll-u-s-presidential-contest-in-wisconsin-november-2024/

[Deminpenn]

7. There is too much value being put on MOE

The theory of some posters is that Harris could be anywhere from 3 or 4 pts either up or down at any given time. We might expect some polls to show her at 52 or 53%, but none of them do. Conversely, we might expect some polls to show her at 45 or 46 %, but none of them show that either.

Trump might be expected to break 50% in some polls or bottom out around 44% in others. But that hasn't happened either.

And there have been a lot of polls.

What is true is that the race is remarkably stable with Harris around 50% and Trump around his ceiling of 46-47%.

[TwilightZone]

8. MOE isn't a theory.

It's math. Just because one thinks it should only apply in one direction doesn't mean it does.

The assertion that Trump has never been, nor could he ever be, above 47% in the polls is a myth that won't die. It's only true if one ignores every poll that's ever been above that.

Trump has been at 49-50% as recently as last weekend. Emerson had him at 49%. They're in the top 10 on 538's ratings. YouGov had him at 49% on the poll that ended on the 25th. They're #4. Other polls have also shown him at 49%-50%.

To be clear, I don't think he'll end up above 47%. Just pointing out that the assertion has no basis in fact.

[Deminpenn]

9. It's your theory and conclusion

that neither candidate is ahead or behind because theoretically adding the max to one candidate and subtracting it from the other could change the outcome.

But that's not what the evidence shows. Neither candidate's vote share is moving much at all indicating the race is stable, not volatile.

[TwilightZone]

10. No clue where you got that idea.

I said nothing about the state of the race other than that I think it's unlikely Trump will get more than 47%.

I said nothing about movement in the polls or that it's tied or that no one is ahead or anything of the sort.

Where you got that impression is anyone's guess.

What I did say is that your interpretation of MOE is incorrect. MOE isn't something that's just pulled out of thin air. It's a specific statistical calculation. It represents a range, not fixed values. It neither proves or shows that the race is tied, nor does it prove or show that it is not. If you're interpreting it otherwise, you are mistaken. It's an integral part of poll reporting.

I also stated that the 47% theory on Trump's approval/polls is false, which is obvious if one looks at the polls or polling averages like NYT's, which currently has him at 48%*. It's just something some blogger or pundit made up that everyone latched on to.

* https://www.nytimes.com/interactive/2024/us/elections/polls-president.html

[Deminpenn]

13. I understand MOE is a statistical calculation

just as is the number of respondents needed for a statistically valid sample.

But you consistently cite MOE as if it was the be all and end all of poll results.

Here is an apples to apples example from the F&M Poll in Pennsylvania of presidential preferences between Harris and Trump starting in Aug after Biden dropped out. MOE is +/- 4%

Aug: Harris 46, Trump 43
Sep: Harris 49, Trump 46
Oct: Harris 48, Trump 44
(For comparison in Feb, it was Biden 42, Trump 37)

Harris' percent isn't jumping around between 50 and 42 or 53 and 45 or 52 and 44. Trump's number isn't jumping around either. Harris has a consistent 3 to 4 pt lead. It's simply wrong to imply, by citing MOE, that the election in Pennsylvania can/should be considered tied.

As for Trump's 46-47% ceiling, he got 46% of the popular vote in 2016. In 2020, he got 46.8% of the popular vote.

[OKIsItJustMe]

12. A wild supposition

Suppose, there was some systematic sampling error. (Say… a certain demographic does not like to reply to polls, or is ashamed to tell polsters the truth.)

https://www.pewresearch.org/short-reads/2016/11/09/why-2016-election-polls-missed-their-mark/

NOVEMBER 9, 2016
Why 2016 election polls missed their mark
BY ANDREW MERCER, CLAUDIA DEANE AND KYLEY MCGEENEY

The results of Tuesday’s presidential election came as a surprise to nearly everyone who had been following the national and state election polling, which consistently projected Hillary Clinton as defeating Donald Trump. Relying largely on opinion polls, election forecasters put Clinton’s chance of winning at anywhere from 70% to as high as 99%, and pegged her as the heavy favorite to win a number of states such as Pennsylvania and Wisconsin that in the end were taken by Trump.

How could the polls have been so wrong about the state of the election?

There is a great deal of speculation but no clear answers as to the cause of the disconnect, but there is one point of agreement: Across the board, polls underestimated Trump’s level of support. With few exceptions, the final round of public polling showed Clinton with a lead of 1 to 7 percentage points in the national popular vote. State-level polling was more variable, but there were few instances where polls overstated Trump’s support.

The fact that so many forecasts were off-target was particularly notable given the increasingly wide variety of methodologies being tested and reported via the mainstream media and other channels. The traditional telephone polls of recent decades are now joined by increasing numbers of high profile, online probability and nonprobability sample surveys, as well as prediction markets, all of which showed similar errors.

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https://www.pewresearch.org/methods/2021/03/02/what-2020s-election-poll-errors-tell-us-about-the-accuracy-of-issue-polling/

MARCH 2, 2021
What 2020’s Election Poll Errors Tell Us About the Accuracy of Issue Polling
BY SCOTT KEETER, NICK HATLEY, ARNOLD LAU AND COURTNEY KENNEDY

Most preelection polls in 2020 overstated Joe Biden’s lead over Donald Trump in the national vote for president, and in some states incorrectly indicated that Biden would likely win or that the race would be close when it was not. These problems led some commentators to argue that “polling is irrevocably broken,” that pollsters should be ignored, or that “the polling industry is a wreck, and should be blown up.”

The true picture of preelection polling’s performance is more nuanced than depicted by some of the early broad-brush postmortems, but it is clear that Trump’s strength was not fully accounted for in many, if not most, polls. Election polling, however, is just one application of public opinion polling, though obviously a prominent one. Pollsters often point to successes in forecasting elections as a reason to trust polling as a whole. But what is the relevance of election polling’s problems in 2020 for the rest of what public opinion polling attempts to do? Given the errors in 2016 and 2020, how much should we trust polls that attempt to measure opinions on issues?1

A new Pew Research Center analysis of survey questions from nearly a year’s worth of its public opinion polling finds that errors of the magnitude seen in some of the 2020 election polls would alter measures of opinion on issues by an average of less than 1 percentage point. Using the national tally of votes for president as an anchor for what surveys of voters should look like, analysis across 48 issue questions on topics ranging from energy policy to social welfare to trust in the federal government found that the error associated with underrepresenting Trump voters and other Republicans by magnitudes seen in some 2020 election polling varied from less than 0.5 to 3 percentage points, with most estimates changing hardly at all. Errors of this magnitude would not alter any substantive interpretations of where the American public stands on important issues. This does not mean that pollsters should quit striving to have their surveys accurately represent Republican, Democratic and other viewpoints, but it does mean that errors in election polls don’t necessarily lead to comparable errors in polling about issues.

How is it possible that underestimating GOP electoral support could have such a small impact on questions about issues?

Why did we choose to test a 12-point Biden lead as the alternative to an accurate poll?

We created a version of our surveys with an overstatement of Biden’s advantage in the election (a “tilted version”) to compare with a “balanced version” that had the correct Biden advantage of 4.4 percentage points. The 12 percentage point Biden lead used in the “tilted” version of the simulation is arbitrary, but it was chosen because it was the largest lead seen in a national poll released by a major news organization in the two weeks prior to Election Day, as documented by FiveThirtyEight. Several polls had Biden leads that were nearly as large during this time period. The simulation, including the manipulation of party affiliation among nonvoters, is described in greater detail below.

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