Midterm Election Poll: Illinois’s 14th District, Hultgren vs. Underwood

NYT Upshot / Siena College Poll

We polled voters in Illinois’s 14th Congressional District.

This poll was conducted from Oct. 3 to Oct. 8.

Can a young Democratic challenger win on health care? We made 41004 calls, and 501 people spoke to us.

Randy Hultgren, the Republican candidate, has a slight edge in our poll.

Given expectations, our poll is a decent result for Democrats. But remember: It’s just one poll, and we talked to only 501 people. Each candidate’s total could easily be five points different if we polled everyone in the district. And having a small sample is only one possible source of error.

Siena College Research Institute logo This survey was conducted by The New York Times Upshot and Siena College.

Where we called:

Each dot shows one of the 41004 calls we made.

Vote choice: Dem. Rep. Don’t know Didn’t answer

To preserve privacy, exact addresses have been concealed. The locations shown here are approximate.

Explore the 2016 election in detail with this interactive map.

About the race

  • Lauren Underwood is a nurse and former senior adviser at the Department of Health and Human Services under President Obama. 31% favorable rating; 14% unfavorable; 55% don’t know

    Based on 501 interviews

  • Randy Hultgren is the incumbent, seeking a fifth term. 31% favorable rating; 27% unfavorable; 42% don’t know

    Based on 501 interviews

  • This district, in the exurbs west of Chicago, has long had a Republican bent. Dennis Hastert, the longest-serving Republican Speaker of the House in history, represented it from 1987 to 2007.

  • Mr. Hultgren hasn’t had a serious challenge since 2010 and says his conservative record suits the district. He voted for the Republican tax bill and is promoting the strong economy.

  • Ms. Underwood, a 31-year-old Naperville native, embraces the progressive label and said Mr. Hultgren’s vote to repeal the Affordable Care Act was her catalyst to run. She is putting health care at the center of her campaign.

  • Ms. Underwood, an African-American candidate in an overwhelmingly white district, said, “This is my home, and the idea that I might not be a good fit is an idea I never gave a lot of consideration to.”

Other organizations’ ratings:

Cook Political Report Tossup
FiveThirtyEight Lean Dem.
Center for Politics Lean Rep.
Inside Elections Tilt Rep.

Previous election results:

2016 President +4 Trump
2012 President +10 Romney
2016 House +19 Rep.

It’s generally best to look at a single poll in the context of other polls:

Polls Dates Underwood Hultgren Margin
Siena College/New York Times n = 428 lv Oct. 31-Nov. 4 49% 43% Underwood +5
Public Policy Polling (D.) 682 v Apr. 16-17 41% 45% Hultgren +4

Sign up for The Campaign Reporter

How our poll result changed

As we reach more people, our poll will become more stable and the margin of sampling error will shrink. The changes in the timeline below reflect that sampling error, not real changes in the race.

One reason we’re doing these surveys live is so you can see the uncertainty for yourself.

If sampling error were the only type of error in a poll, we would expect candidates who trail by five points in a poll of 501 people to win about one out of every seven races. But this probably understates the total error by a factor of two.

Our turnout model

There’s a big question on top of the standard margin of error in a poll: Who is going to vote? It’s a particularly challenging question this year, since special elections have shown Democrats voting in large numbers.

To estimate the likely electorate, we combine what people say about how likely they are to vote with information about how often they have voted in the past. In previous races, this approach has been more accurate than simply taking people at their word. But there are many other ways to do it.

Our poll under different turnout scenarios
Who will vote? Est. turnout Our poll result
The types of people who voted in 2014 235k Hultgren +8
People who say they are almost certain to vote, and no one else 247k Even
Our estimate 265k Hultgren +5
People whose voting history suggests they will vote, regardless of what they say 267k Hultgren +4
People who say they will vote, adjusted for past levels of truthfulness 288k Hultgren +5
The types of people who voted in 2016 329k Hultgren +6
Every active registered voter 470k Hultgren +1

All estimates based on 501 interviews

Just because one candidate leads in all of these different turnout scenarios doesn’t mean much by itself. They don’t represent the full range of possible turnout scenarios, let alone the full range of possible election results.

The types of people we reached

Even if we got turnout exactly right, the margin of error wouldn’t capture all of the error in a poll. The simplest version assumes we have a perfect random sample of the voting population. We do not.

People who respond to surveys are almost always too old, too white, too educated and too politically engaged to accurately represent everyone.

How successful we were in reaching different kinds of voters
Called Inter-
viewed
Success
rate
Our
respon­ses
Goal
18 to 29 2100 30 1 in 70 6% 8%
30 to 64 20043 316 1 in 63 63% 64%
65 and older 6273 155 1 in 40 31% 28%
Male 12596 242 1 in 52 48% 48%
Female 15854 259 1 in 61 52% 52%
White 22418 403 1 in 56 80% 78%
Nonwhite 3283 44 1 in 75 9% 10%
Cell 17727 298 1 in 59 59%
Landline 10723 203 1 in 53 41%

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

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

Here, we’re weighting by age, primary vote, gender, likelihood of voting, race, education and region, mainly using data from voting records files compiled by L2, a nonpartisan voter file vendor.

But weighting works only if you weight by the right categories and you know what the composition of the electorate will be. In 2016, many pollsters didn’t weight by education and overestimated Hillary Clinton’s standing as a result.

Here are other common ways to weight a poll:

Our poll under different weighting schemes
Our poll result
Don’t weight by primary vote, like most public polls Hultgren +4
Weight using census data instead of voting records, like most public polls Hultgren +4
Don’t weight by education, like many polls in 2016 Hultgren +4
Our estimate Hultgren +5

All estimates based on 501 interviews

Just because one candidate leads in all of these different weighting scenarios doesn’t mean much by itself. They don’t represent the full range of possible weighting scenarios, let alone the full range of possible election results.

Undecided voters

About 10 percent of voters said that they were undecided or refused to tell us whom they would vote for.

If they were to break 3 to 1 in favor of Democrats, that alone would be enough to change the lead in our poll, assuming we did everything else perfectly. (We could also be wrong on turnout or our sample could be unrepresentative. Or other voters could change their minds.)

Issues and other questions

We're asking voters whether they support Brett Kavanaugh's nomination to the Supreme Court and whether they believe the sexual assault accusations against him.

We're also asking voters about feminism and whether they think it's important to elect more women to public office.

Do you approve or disapprove of the job Donald Trump is doing as president?
ApproveDisapp.Don’t know
Voters n = 500 46% 49% 5%
Would you prefer Republicans to retain control of the House of Representatives or would you prefer Democrats to take control?
Reps. keep HouseDems. take HouseDon’t know
Voters n = 501 50% 43% 7%
Do you support or oppose Brett Kavanaugh’s nomination to the United States Supreme Court?
supportopposeDon’t know
Voters n = 501 51% 45% 5%
As you may know, Supreme Court nominee Brett Kavanaugh has been accused of committing sexual assault when he was a teenager. Would you say you believe the allegations, you do not believe the allegations, or you simply are unable to come to a conclusion?
BelieveDo not believeDon’t know
Voters n = 501 32% 36% 32%
Do you support electing more people who describe themselves as feminists?
supportopposeDon’t know
Voters n = 501 50% 35% 15%
Is it important to elect more women to public office?
agreedisagreeDon’t know
Voters n = 500 77% 14% 9%
As you think about your member of Congress, would you prefer your representative to support President Trump and his agenda, or to serve as a check on the president and his agenda?
SupportCheckDon’t know
Voters n = 501 43% 51% 6%

Percentages are weighted to resemble likely voters.

What different types of voters said

Voters nationwide are deeply divided along demographic lines. Our poll suggests divisions too. But don’t overinterpret these tables. Results among subgroups may not be representative or reliable. Be especially careful with groups with fewer than 100 respondents, shown here in stripes.

Gender
Dem.Rep.Und.
Female n = 259 / 52% of voters 50% 42% 9%
Male 242 / 48% 35% 54% 11%
Age
Dem.Rep.Und.
18 to 29 n = 33 / 8% of voters 43% 52% 5%
30 to 44 89 / 16% 51% 33% 16%
45 to 64 218 / 48% 41% 48% 11%
65 and older 161 / 28% 41% 54% 6%
Race
Dem.Rep.Und.
White n = 425 / 83% of voters 39% 51% 10%
Nonwhite 63 / 14% 60% 35% 6%
Race and education
Dem.Rep.Und.
Nonwhite n = 63 / 14% of voters 60% 35% 6%
White, college grad 228 / 45% 40% 48% 12%
White, not college grad 197 / 38% 38% 54% 9%
Education
Dem.Rep.Und.
H.S. Grad. or Less n = 64 / 15% of voters 38% 56% 6%
Some College Educ. 159 / 29% 42% 48% 10%
4-year College Grad. 147 / 35% 42% 45% 13%
Post-grad. 127 / 20% 48% 44% 8%
Party
Dem.Rep.Und.
Democrat n = 124 / 25% of voters 93% 4% 3%
Republican 165 / 34% 3% 90% 7%
Independent 196 / 39% 46% 40% 15%
Another party 9 / 1% 16% 55% 29%
Primary vote
Dem.Rep.Und.
Democratic n = 166 / 32% of voters 87% 7% 6%
Republican 217 / 43% 10% 80% 10%
Other 118 / 25% 42% 43% 15%
Intention of voting
Dem.Rep.Und.
Almost certain n = 316 / 65% of voters 43% 47% 10%
Very likely 136 / 29% 43% 50% 8%
Somewhat likely 19 / 3% 35% 58% 7%
Not very likely 10 / 1% 42% 25% 33%
Not at all likely 16 / 1% 18% 17% 65%

Percentages are weighted to resemble likely 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. 4-6
Illinois 12 Downstate Illinois Sept. 4-6
Illinois 6 Chicago suburbs Sept. 4-6
Kentucky 6 Lexington area Sept. 6-8
Minnesota 3 Minneapolis suburbs Sept. 7-9
Minnesota 8 Iron Range Sept. 6-9
West Virginia 3 Coal Country Sept. 8-10
Virginia 7 Richmond suburbs Sept. 9-12
Texas 23 South Texas Sept. 10-11
Wisconsin 1 Southeastern Wisconsin Sept. 11-13
Colorado 6 Denver Suburbs Sept. 12-14
Maine 2 Upstate, Down East Maine Sept. 12-14
Kansas 2 Eastern Kansas Sept. 13-15
Florida 26 South Florida Sept. 13-17
New Mexico 2 Southern New Mexico Sept. 13-18
Texas 7 Houston and suburbs Sept. 14-18
California 25 Southern California Sept. 17-19
New Jersey 7 Suburban New 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 7 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, central New Jersey Sept. 22-26
Nebraska 2 Omaha area Sept. 23-26
Washington 8 Seattle suburbs and beyond Sept. 24-26
Michigan 8 Lansing, Detroit suburbs Sept. 28-Oct. 3
Virginia 2 Coastal Virginia Sept. 26-Oct. 1
Arizona 2 Southeastern Arizona Sept. 26-Oct. 1
Iowa 3 Southwest Iowa Sept. 27-30
Ohio 1 Southwestern Ohio Sept. 27-Oct. 1
Minnesota 2 Minneapolis suburbs, southern Minn. Sept. 29-Oct. 2
Michigan 11 Detroit suburbs Oct. 1-6
Illinois 14 Chicago exurbs Oct. 3-8
North Carolina 9 Charlotte suburbs, southern N.C. Oct. 1-5
New York 1 Eastern Long Island Oct. 4-8
Texas 31 Central Texas, Round Rock Oct. 1-5
North Carolina 13 Piedmont Triad Oct. 3-8
Pennsylvania 16 Northwestern Pa. Oct. 5-8
Texas Senate The Lone Star State Oct. 8-11
Tennessee Senate The Volunteer State Oct. 8-11
Nevada Senate The Silver State Oct. 8-10
Pennsylvania 1 Delaware Valley Oct. 11-14
Arizona 6 Northeastern Phoenix suburbs Oct. 11-15
Minnesota 8 Iron Range Oct. 11-14
Virginia 10 Northern Virginia Oct. 11-15
Colorado 6 Denver Suburbs Oct. 13-17
Washington 3 Southwest Washington Oct. 14-19
Texas 23 South Texas Oct. 13-18
West Virginia 3 Coal Country Oct. 14-18
Kansas 3 Eastern Kansas suburbs Oct. 14-17
Arizona Senate The Grand Canyon State Oct. 15-19
Florida 27 South Florida Oct. 15-19
Maine 2 Upstate, Down East Maine Oct. 15-18
New Jersey 11 Northern New Jersey suburbs. Oct. 13-17
Pennsylvania 8 Wyoming Valley Oct. 16-19
Florida 15 Tampa Exurbs Oct. 16-19
Virginia 5 Central, southern Virginia Oct. 16-22
California 39 East of Los Angeles Oct. 18-23
Illinois 12 Downstate Illinois Oct. 18-22
Virginia 2 Coastal Virginia Oct. 18-22
California 49 Southern California Oct. 19-24
Florida 26 South Florida Oct. 19-24
Texas 7 Houston and suburbs Oct. 19-25
Illinois 13 Downstate Illinois Oct. 21-25
New Mexico 2 Southern New Mexico Oct. 19-23
Illinois 6 Chicago suburbs Oct. 20-26
Ohio 1 Southwestern Ohio Oct. 20-24
California 10 Central Valley farm belt Oct. 21-25
New Jersey 3 South, central New Jersey Oct. 21-25
Pennsylvania 10 South, central Pennsylvania Oct. 23-26
New York 11 Staten Island, southern Brooklyn Oct. 23-27
Florida Senate The Sunshine State Oct. 23-27
Florida Governor The Sunshine State Oct. 23-27
Utah 4 South of Salt Lake City Oct. 24-26
New York 27 Western New York Oct. 24-29
Iowa 3 Southwest Iowa Oct. 25-27
California 25 Southern California Oct. 25-28
California 45 Southern California Oct. 26-Nov. 1
Pennsylvania 1 Delaware Valley Oct. 26-29
North Carolina 9 Charlotte suburbs, southern N.C. Oct. 26-30
Kansas 2 Eastern Kansas Oct. 27-30
New Jersey 7 Suburban New Jersey Oct. 28-31
Georgia 6 Northern Atlanta suburbs Oct. 28-Nov. 4
Iowa 1 Northeastern Iowa Oct. 28-31
Texas 32 Suburban Dallas Oct. 29-Nov. 4
California 48 Orange County Oct. 29-Nov. 4
Virginia 7 Richmond suburbs Oct. 30-Nov. 4
Illinois 14 Chicago exurbs Oct. 31-Nov. 4
Washington 8 Seattle suburbs and beyond Oct. 30-Nov. 4
Iowa 4 Northwestern Iowa Oct. 31-Nov. 4
Michigan 8 Lansing, Detroit suburbs Oct. 31-Nov. 4
Kentucky 6 Lexington area Nov. 1-4
New York 19 Catskills, Hudson Valley Nov. 1-4
New York 22 Central New York Nov. 1-4

About this poll

  • Most responses shown here are delayed about 30 minutes. Some are delayed longer for technical reasons.
  • The design effect of this poll is 1.09. That’s a measure of how much weighting we are doing to make 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 Upshot and Siena College.

Siena College Research Institute logo

Data collection by Reconnaissance Market Research, M. Davis and Company, the Institute for Policy and Opinion Research at Roanoke College, the Survey Research Center at the University of Waterloo, the University of North Florida and the Siena College Research Institute.