In Which City Is Elaine Luria Registered To Vote

Our poll shows a shut race.

Our poll result is about what was expected. But call up: It's just one poll, and we talked to simply 508 people. Each candidate'southward total could easily be five points different if nosotros polled everyone in the commune. And having a small-scale sample is only one possible source of error.

Where we called:

Each dot shows one of the 3 4 1 three 4 calls we made.

Vote option: Dem. Rep. Don't know Didn't answer

To preserve privacy, exact addresses have been concealed. The locations shown hither are judge.

Explore the 2016 election in detail with this interactive map.

Near the race

Elaine Luria is a former Naval commander and a small-concern owner. 45% favorable rating; 28% unfavorable; 27% don't know

Based on 508 interviews
Scott Taylor is the electric current representative and a sometime member of the Navy SEALs. 51% favorable rating; 32% unfavorable; 18% don't know

Based on 508 interviews
This district includes Virginia Embankment, the Norfolk Naval Base of operations and the Virginia portion of Delmarva. It has been in Republican easily for all simply one term of the final two decades. Donald J. Trump carried the commune by three points.
(We polled this district from Sept. 26 to Oct. 1. That showed the incumbent with a modest lead.)
Ms. Luria is among a crop of Democratic women with a military or national security groundwork who are making a offset venture into politics.
Allegations surfaced last month that members of Mr. Taylor's staff forged signatures to help get an contained candidate on the ballot, presumably with the aim of siphoning votes from Ms. Luria. A special prosecutor has been appointed. Mr. Taylor conceded that he was "enlightened of the attempt to become signatures," simply "what I was not enlightened of at all was any wrongdoing by everyone at the fourth dimension."

Other organizations' ratings:

Previous election results:

2016 President	+3 Trump
2012 President	+two Romney
2016 House	+23 Rep.

How our poll result changed

As we attain more people, our poll volition get more than stable and the margin of sampling fault will compress. The changes in the timeline below reflect that sampling fault, not real changes in the race.

I reason we're doing these surveys live is so you can meet the doubtfulness for yourself.

If sampling error were the simply blazon of error in a poll, we would expect candidates who trail by iii points in a poll of 508 people to win about one out of every four races. Only this probably understates the total error by a factor of two.

Our turnout model

There'south a big question on tiptop of the standard margin of error in a poll: Who is going to vote? It'southward a peculiarly challenging question this year, since special elections take shown Democrats voting in large numbers.

To estimate the likely electorate, we combine what people say about how probable they are to vote with information most how oftentimes they take voted in the past. In previous races, this arroyo has been more than accurate than simply taking people at their give-and-take. But there are many other ways to do information technology.

Assumptions near who is going to vote may be particularly important in this race.

Our poll under dissimilar turnout scenarios

Who will vote?	Est. turnout	Our poll result
The types of people who voted in 2014	192k	Taylor +6
People whose voting history suggests they will vote, regardless of what they say	207k	Taylor +iii
Our guess	207k	Taylor +3
People who say they will vote, adapted for by levels of truthfulness	225k	Luria +1
People who say they are almost certain to vote, and no one else	253k	Luria +i
The types of people who voted in 2016	299k	Even
Every active registered voter	431k	Luria +half dozen

All estimates based on 508 interviews

In these scenarios, higher turnout tends to be better for Democrats.

The types of people we reached

Even if we got turnout exactly right, the margin of fault wouldn't capture all of the fault in a poll. The simplest version assumes we take a perfect random sample of the voting population. We do non.

People who respond to surveys are virtually always also old, as well white, too educated and too politically engaged to accurately stand for everyone.

How successful we were in reaching different kinds of voters

	Chosen	Inter- viewed	Success charge per unit	Our responses	Goal
18 to 29	2 8 3 iv	3 4	ane in 83	7%	8%
30 to 64	i 5 5 six 6	3 0 5	1 in 51	threescore%	58%
65 and older	v 6 1 nine	1 6 ix	1 in 33	33%	33%
Male	one 0 9 0 8	ii 5 9	1 in 42	51%	46%
Female person	1 3 one 1 4	2 four 9	1 in 53	49%	54%
White	one 6 five i eight	iii 6 4	1 in 45	72%	71%
Nonwhite	five 7 1 vi	1 0 ane	1 in 57	20%	22%
Cell	1 5 8 three v	ii 8 4	1 in 56	56%	—
Landline	eight ane 8 7	2 2 4	1 in 37	44%	—

Based on administrative records. Some characteristics are missing or incorrect. Many voters are called multiple times.

Pollsters compensate past giving more weight to respondents from under-represented groups.

Hither, nosotros're weighting by age, main vote, gender, likelihood of voting, race, pedagogy and region, mainly using data from voting records files compiled by L2, a nonpartisan voter file vendor.

But weighting works just if you weight by the right categories and you lot know what the limerick of the electorate will exist. In 2016, many pollsters didn't weight past pedagogy and overestimated Hillary Clinton's standing as a result.

Here are other mutual ways to weight a poll:

Our poll nether different weighting schemes

	Our poll result
Weight using census data instead of voting records, like near public polls	Taylor +2
Don't weight past principal vote, like most public polls	Taylor +two
Our estimate	Taylor +three
Don't weight by education, similar many polls in 2016	Taylor +three

All estimates based on 508 interviews

Only because 1 candidate leads in all of these unlike weighting scenarios doesn't mean much by itself. They don't represent the full range of possible weighting scenarios, let solitary the full range of possible ballot results.

Undecided voters

Virtually 13 pct of voters said that they were undecided or refused to tell u.s.a. whom they would vote for.

Issues and other questions

Do you approve or disapprove of the job Donald Trump is doing as president?

	Approve	Disapp.	Don't know
Voters northward = 502	46%	47%	6%

Would you lot prefer Republicans to retain control of the House of Representatives or would you adopt Democrats to take control?

	Reps. keep House	Dems. take House	Don't know
Voters n = 502	47%	43%	9%

Percentages are weighted to resemble likely voters.

What different types of voters said

Voters nationwide are securely divided along demographic lines. Our poll suggests divisions besides. But don't overinterpret these tables. Results amid subgroups may not be representative or reliable. Be especially conscientious with groups with fewer than 100 respondents, shown here in stripes.

Gender

	Dem.	Rep.	Und.
Female n = 249 / 54% of voters	51%	38%	11%
Male 259 / 46%	32%	53%	15%

Age

	Dem.	Rep.	Und.
18 to 29 north = 30 / 8% of voters	58%	30%	12%
30 to 44 81 / 17%	43%	39%	xviii%
45 to 64 219 / 41%	37%	51%	12%
65 and older 172 / 33%	46%	46%	8%

Race

	Dem.	Rep.	Und.
White n = 353 / 68% of voters	37%	54%	eight%
Black 76 / 17%	76%	10%	15%
Hispanic 19 / four%	36%	48%	sixteen%
Asian 12 / 3%	42%	thirty%	29%
Other 17 / three%	nineteen%	66%	fifteen%

Race and education

	Dem.	Rep.	Und.
Nonwhite n = 124 / 26% of voters	60%	24%	16%
White, college grad 208 / 35%	43%	51%	7%
White, not college grad 145 / 33%	32%	58%	x%

Teaching

	Dem.	Rep.	Und.
H.S. Grad. or Less n = 60 / 18% of voters	43%	38%	nineteen%
Some Higher Educ. 168 / 34%	38%	50%	12%
4-year College Grad. 134 / 27%	46%	45%	9%
Post-grad. 136 / 19%	47%	45%	8%

Party

	Dem.	Rep.	Und.
Democrat due north = 137 / 28% of voters	92%	2%	half-dozen%
Republican 133 / 27%	7%	88%	4%
Independent 198 / 38%	38%	46%	15%
Another party 16 / 3%	11%	63%	27%

Primary vote

	Dem.	Rep.	Und.
Autonomous north = 144 / 28% of voters	80%	5%	15%
Republican 201 / 39%	10%	78%	12%
Other 163 / 33%	49%	twoscore%	12%

Intention of voting

	Dem.	Rep.	Und.
Already voted due north = 15 / 3% of voters	42%	53%	5%
Almost certain 337 / 66%	41%	47%	12%
Very likely 125 / 26%	47%	43%	11%
Somewhat likely ten / 2%	40%	31%	29%
Not very likely ten / i%	15%	48%	37%
Non at all probable half dozen / 0%	26%	15%	sixty%

Percentages are weighted to resemble probable voters; the number of respondents in each subgroup is unweighted. Undecided voters includes those who refused to answer.

Other districts where we've completed polls

California 48 Orange County	Sept. 4-vi
Illinois 12 Downstate Illinois	Sept. 4-six
Illinois 6 Chicago suburbs	Sept. 4-vi
Kentucky vi Lexington area	Sept. six-8
Minnesota 3 Minneapolis suburbs	Sept. 7-9
Minnesota 8 Iron Range	Sept. 6-9
Due west Virginia 3 Coal Country	Sept. 8-x
Virginia 7 Richmond suburbs	Sept. ix-12
Texas 23 South Texas	Sept. 10-eleven
Wisconsin one Southeastern Wisconsin	Sept. 11-13
Colorado half dozen Denver Suburbs	Sept. 12-14
Maine ii Upstate, Downward Due east Maine	Sept. 12-xiv
Kansas 2 Eastern Kansas	Sept. xiii-15
Florida 26 South Florida	Sept. thirteen-17
New Mexico ii Southern New Mexico	Sept. 13-18
Texas 7 Houston and suburbs	Sept. 14-eighteen
California 25 Southern California	Sept. 17-nineteen
New Jersey 7 Suburban New Bailiwick of jersey	Sept. 17-21
Iowa 1 Northeastern Iowa	Sept. 18-20
California 49 Southern California	Sept. 18-23
Texas 32 Suburban Dallas	Sept. 19-24
Pennsylvania seven The Lehigh Valley	Sept. 21-25
Kansas 3 Eastern Kansas suburbs	Sept. 20-23
California 45 Southern California	Sept. 21-25
New Jersey 3 South, key New Jersey	Sept. 22-26
Nebraska ii Omaha expanse	Sept. 23-26
Washington 8 Seattle suburbs and beyond	Sept. 24-26
Michigan eight Lansing, Detroit suburbs	Sept. 28-Oct. 3
Virginia two Littoral Virginia	Sept. 26-Oct. 1
Arizona 2 Southeastern Arizona	Sept. 26-Oct. 1
Iowa 3 Southwest Iowa	Sept. 27-thirty
Ohio one Southwestern Ohio	Sept. 27-Oct. 1
Minnesota 2 Minneapolis suburbs, southern Minn.	Sept. 29-Oct. 2
Michigan eleven Detroit suburbs	Oct. i-6
Illinois 14 Chicago exurbs	Oct. 3-8
North Carolina ix Charlotte suburbs, southern N.C.	October. 1-v
New York 1 Eastern Long Island	October. 4-8
Texas 31 Cardinal Texas, Round Rock	Oct. 1-5
North Carolina 13 Piedmont Triad	Oct. 3-eight
Pennsylvania 16 Northwestern Pa.	Oct. 5-8
Texas Senate The Alone Star Country	Oct. eight-11
Tennessee Senate The Volunteer State	October. 8-11
Nevada Senate The Silver State	October. 8-x
Pennsylvania 1 Delaware Valley	October. 11-fourteen
Arizona 6 Northeastern Phoenix suburbs	Oct. eleven-fifteen
Minnesota 8 Fe Range	Oct. 11-14
Virginia 10 Northern Virginia	October. 11-fifteen
Colorado half dozen Denver Suburbs	Oct. 13-17
Washington 3 Southwest Washington	Oct. fourteen-19
Texas 23 Southward Texas	October. 13-eighteen
West Virginia 3 Coal Land	Oct. fourteen-18
Kansas iii Eastern Kansas suburbs	October. 14-17
Arizona Senate The Grand Canyon State	October. 15-19
Florida 27 South Florida	October. xv-19
Maine 2 Upstate, Downward Due east Maine	October. 15-eighteen
New Bailiwick of jersey 11 Northern New Bailiwick of jersey suburbs.	October. 13-17
Pennsylvania 8 Wyoming Valley	Oct. xvi-19
Florida 15 Tampa Exurbs	Oct. 16-19
Virginia five Central, southern Virginia	Oct. 16-22
California 39 East of Los Angeles	October. 18-23
Illinois 12 Downstate Illinois	Oct. 18-22
Virginia ii Littoral Virginia	Oct. 18-22
California 49 Southern California	October. 19-24
Florida 26 Southward Florida	Oct. nineteen-24
Texas seven Houston and suburbs	October. 19-25
Illinois 13 Downstate Illinois	Oct. 21-25
New United mexican states ii Southern New Mexico	Oct. 19-23
Illinois 6 Chicago suburbs	Oct. twenty-26
Ohio 1 Southwestern Ohio	Oct. 20-24
California 10 Key Valley subcontract chugalug	Oct. 21-25
New Jersey 3 South, central New Jersey	Oct. 21-25
Pennsylvania 10 S, primal Pennsylvania	Oct. 23-26
New York 11 Staten Isle, southern Brooklyn	Oct. 23-27
Florida Senate The Sunshine State	Oct. 23-27
Florida Governor The Sunshine State	Oct. 23-27
Utah iv South of Salt Lake City	Oct. 24-26
New York 27 Western New York	October. 24-29
Iowa 3 Southwest Iowa	Oct. 25-27
California 25 Southern California	Oct. 25-28
California 45 Southern California	Oct. 26-Nov. one
Pennsylvania 1 Delaware Valley	October. 26-29
N Carolina 9 Charlotte suburbs, southern North.C.	Oct. 26-xxx
Kansas two Eastern Kansas	Oct. 27-30
New Jersey 7 Suburban New Jersey	Oct. 28-31
Georgia 6 Northern Atlanta suburbs	October. 28-November. four
Iowa 1 Northeastern Iowa	Oct. 28-31
Texas 32 Suburban Dallas	Oct. 29-Nov. 4
California 48 Orangish County	Oct. 29-Nov. 4
Virginia 7 Richmond suburbs	Oct. 30-Nov. 4
Illinois xiv Chicago exurbs	Oct. 31-Nov. four
Washington eight Seattle suburbs and beyond	Oct. 30-Nov. 4
Iowa 4 Northwestern Iowa	October. 31-Nov. 4
Michigan 8 Lansing, Detroit suburbs	Oct. 31-November. 4
Kentucky 6 Lexington area	November. 1-4
New York xix Catskills, Hudson Valley	November. 1-iv
New York 22 Cardinal New York	November. 1-4

Well-nigh this poll

Virtually responses shown here are delayed well-nigh 30 minutes. Some are delayed longer for technical reasons.
The design event of this poll is i.12. That's a measure of how much weighting nosotros are doing to brand our respondents resemble all voters.
Read more about the methodology for this poll.
Download the microdata behind this poll.

This survey was conducted by The New York Times Effect and Siena College.

Siena College Research Institute logo

Information drove by Reconnaissance Market place Inquiry, M. Davis and Visitor, the Found for Policy and Opinion Inquiry at Roanoke College, the Survey Research Heart at the University of Waterloo, the University of North Florida and the Siena College Research Institute.

By Michael Andre, Larry Buchanan, Matthew Bloch, Jeremy Bowers, Nate Cohn, Alastair Coote, Annie Daniel, Richard Harris, Josh Katz, Rebecca Lieberman, Blacki Migliozzi, Paul Murray, Adam Pearce, Kevin Quealy, Eden Weingart and Isaac White