Can a former Democratic governor flip a Senate seat in a deep red state? We made 28670 calls, and 593 people spoke to us.

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

Hey, I’m Alex Burns, a politics correspondent for The Times. I’ll give you the latest reporting and intel on the midterms and take your questions from the campaign trail.

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

At a recent fund-raider for her, President Trump said, “A vote for Marsha is really a vote for me and everything that we stand for.”

Ms. Blackburn has developed a reputation as a hard-right firebrand , and has tied herself closely to President Trump. She signed onto a letter formally nominating him for the Nobel Peace Prize for trying to end tensions on the Korean peninsula.

Mr. Bredesen released a statement last week supporting Brett Kavanaugh’s Supreme Court nomination. He said of the Senate minority leader, Chuck Schumer: “I don’t even support him.”

He is running as a moderate, promoting himself as a pro-business consensus builder. He helped bring an N.F.L. franchise to Nashville when he was the city’s mayor.

Mr. Bredesen is well known in the state from his previous leadership roles. He carried all of the state’s 95 counties when he was re-elected as governor in 2006.

Democrats were very pleased that Mr. Bredesen decided to run, and Republicans are worried that the race has seemed so close in a reliably Republican state.

is a House member representating Tennessee’s Seventh District, first elected in 2002, and a former state representative. 51% favorable rating; 38% unfavorable; 11% don’t know

is a businessman, a former governor of Tennessee and a former mayor of Nashville. 44% favorable rating; 43% unfavorable; 13% don’t know

Each dot shows one of the 28670 calls we made.

But sampling error is not the only type of error in a poll.

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

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.

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 1.3m Blackburn +21 People whose voting history suggests they will vote, regardless of what they say 1.8m Blackburn +14 Our estimate 1.8m Blackburn +14 People who say they will vote, adjusted for past levels of truthfulness 2m Blackburn +14 People who say they are almost certain to vote, and no one else 2m Blackburn +11 The types of people who voted in 2016 2.2m Blackburn +15 Every active registered voter 3.3m Blackburn +9 In these scenarios, higher turnout tends to be better for Democrats. 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 3 1 2 3 3 8 1 in 82 6% 8% 30 to 64 1 4 2 7 8 3 5 9 1 in 40 61% 58% 65 and older 5 1 1 5 1 9 6 1 in 26 33% 33% Male 1 0 0 0 2 2 5 7 1 in 39 43% 46% Female 1 2 5 1 6 3 3 6 1 in 37 57% 54% White 1 7 8 0 0 4 8 4 1 in 37 82% 80% Nonwhite 3 5 4 2 7 6 1 in 47 13% 15% Cell 1 5 0 2 4 3 2 5 1 in 46 55% — Landline 7 4 9 4 2 6 8 1 in 28 45% — 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 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. Even after weighting, our poll does not have as many of some types of people as we would like. Here are other common ways to weight a poll: Our poll under different weighting schemes Our poll result Don’t weight by education, like many polls in 2016 Blackburn +12 Weight using census data instead of voting records, like most public polls Blackburn +13 Don’t weight by primary vote, like most public polls Blackburn +14 Our estimate Blackburn +14 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.