The Democrats' Best Senate Hopes: An Unorthodox Ranking

April 27, 2014

photo credit: MANDEL NGAN/AFP/Getty Images
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font-weight:300; } /* W-VIRGINIA */ .chart-wrapper .box#w-virginia .header-wrapper { width:170px; margin-top:-4px; } .chart-wrapper .box#w-virginia .main-text .header-wrapper h2 { margin-top:-1px; } .chart-wrapper .box#w-virginia .main-text .header-wrapper h3 { top:-24px; left:-5px; position:relative; } .chart-wrapper .box#w-virginia .state { position:relative; margin-top:-65px; right:-120px; } .chart-wrapper .box#w-virginia .def-number { margin-top:75px; } .chart-wrapper .box#w-virginia .def-number h1 { margin-bottom:-250px; } /* ALASKA */ .chart-wrapper .box#alaska .header-wrapper { width:175px; margin-top:-4px; } .chart-wrapper .box#alaska .header-wrapper h2 { margin-top:-1px; } .chart-wrapper .box#alaska .main-text .header-wrapper h3 { top:8px; left:-5px; position:relative; } .chart-wrapper .box#alaska .state { position:relative; margin-top:-85px; right:-18px; } .chart-wrapper .box#alaska .def-number { margin-bottom:-230px; margin-top:45px; } .chart-wrapper .box#alaska .more { margin-top:25px; } /* MONTANA */ .chart-wrapper .box#montana .header-wrapper { width:205px; margin-top:-4px; } .chart-wrapper .box#montana .header-wrapper h2 { margin-top:-1px; } .chart-wrapper .box#montana .header-wrapper h3 { top:8px; position:relative; } .chart-wrapper .box#montana .state { position:relative; right:-95px; margin-top:40px; } .chart-wrapper .box#montana .def-number { margin-top:130px; margin-bottom:-240px; } /* N.HAMP */ .chart-wrapper .box#new-hampshire .header-wrapper { width:235px; margin-top:-4px; } .chart-wrapper .box#new-hampshire .header-wrapper h2 { margin-top:-1px; } .chart-wrapper .box#new-hampshire .header-wrapper h3 { top:-24px; left:-5px; position:relative; } .chart-wrapper .box#new-hampshire .state { position:relative; margin-top:-55px; right:-130px; } .chart-wrapper .box#new-hampshire .def-number { margin-top:85px; margin-bottom:-245px; } /* IOWA */ .chart-wrapper .box#iowa .header-wrapper { width:135px; margin-top:-4px; } .chart-wrapper .box#iowa .header-wrapper h2 { margin-top:-1px; } .chart-wrapper .box#iowa .header-wrapper h3 { top:8px; left:-5px; position:relative; } .chart-wrapper .box#iowa .state { position:relative; margin-top:-75px; right:-90px; } .chart-wrapper .box#iowa .def-number h1 { font-size:118px; } .chart-wrapper .box#iowa .def-number { margin-top:125px; margin-bottom:-210px; } /* LOUISIANA */ .chart-wrapper .box#louisiana .header-wrapper { width:218px; margin-top:-4px; } .chart-wrapper .box#louisiana .header-wrapper h2 { margin-top:-1px; } .chart-wrapper .box#louisiana .header-wrapper h3 { top:8px; left:-5px; position:relative; } .chart-wrapper .box#louisiana .state { position:relative; margin-top:-50px; right:-125px; } .chart-wrapper .box#louisiana .def-number h1 { font-size:125px; } .chart-wrapper .box#louisiana .def-number { margin-top:80px; margin-bottom:-225px; } /* ARKANSAS */ .chart-wrapper .box#arkansas .header-wrapper { width:208px; margin-top:-4px; } .chart-wrapper .box#arkansas .header-wrapper h2 { margin-top:-1px; } .chart-wrapper .box#arkansas .header-wrapper h3 { top:8px; left:-5px; position:relative; } .chart-wrapper .box#arkansas .state { position:relative; margin-top:-50px; right:-120px; } .chart-wrapper .box#arkansas .def-number h1 { font-size:125px; } .chart-wrapper .box#arkansas .def-number { margin-top:90px; margin-bottom:-245px; } /* KENTUCKY */ .chart-wrapper .box#kentucky .header-wrapper { width:215px; margin-top:-4px; } .chart-wrapper .box#kentucky .header-wrapper h2 { margin-top:-1px; } .chart-wrapper .box#kentucky .header-wrapper h3 { top:8px; left:-5px; position:relative; } .chart-wrapper .box#kentucky .state { position:relative; margin-top:-35px; right:-100px; } .chart-wrapper .box#kentucky .def-number h1 { font-size:125px; } .chart-wrapper .box#kentucky .def-number { margin-top:140px; margin-bottom:-225px; } /* MICHIGAN */ .chart-wrapper .box#michigan .header-wrapper { width:210px; margin-top:-4px; } .chart-wrapper .box#michigan .header-wrapper h2 { margin-top:-1px; } .chart-wrapper .box#michigan .header-wrapper h3 { top:8px; left:-5px; position:relative; } .chart-wrapper .box#michigan .state { position:relative; margin-top:-85px; right:-15px; } .chart-wrapper .box#michigan .def-number h1 { font-size:123px; } .chart-wrapper .box#michigan .def-number { margin-top:-140px; margin-bottom:-220px; } /* COLORADO */ .chart-wrapper .box#colorado .header-wrapper { width:258px; margin-top:-4px; } .chart-wrapper .box#colorado .header-wrapper h2 { margin-top:-1px; } .chart-wrapper .box#colorado .header-wrapper h3 { top:8px; left:-5px; position:relative; } .chart-wrapper .box#colorado .state { position:relative; margin-top:-45px; right:-135px; } .chart-wrapper .box#colorado .def-number h1 { font-size:123px; } .chart-wrapper .box#colorado .def-number { margin-top:120px; margin-bottom:-225px; } /* N.CAROLINA */ .chart-wrapper .box#north-carolina .header-wrapper { width:225px; margin-top:-4px; } .chart-wrapper .box#north-carolina .header-wrapper h2 { margin-top:-1px; } .chart-wrapper .box#north-carolina .header-wrapper h3 { top:-24px; 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While pundits cite polls, the political pros who steer campaigns keep their eyes on different figures: how many actual votes their candidate needs to prevail, and where those votes will come from. Proprietary formulas reveal the number of votes that a contender can count on going in, which leaves a shortfall that can be closed through mobilization. With field studies having determined a price for each additional vote yielded by the most effective turnout tactics, we were able to compare the relative difficulty and costliness of this year’s most competitive Senate races. Ranked from easiest to most difficult, our list of the 2014 Senate races that Democrats have the best chances of winning through mobilization looks like this:

1

West
Virginia

Natalie Tennant
Shelley Moore Capito*

democratic
vote deficit

53,125

Total Registered Voters: 1,202,886

Turnout Score: 44.82

Expected Total Vote: 539,191

Win Number: 280,379


Total Reflex Voters: 448,236

Weighted Party Score: 0.507

Core Democratic Vote: 227,254


Democratic Vote Deficit: 53,125


Total Unreliable Voters: 216,747

Weighted Party Score: 0.5802

Democratic-Leaning Unreliables: 107,760


New Registrants: 32,298

Democratic-Leaning New Registrants: 15,037


Conversion Cost: $2,496,875

Volunteer Need: 123,958hrs

2

Alaska

Mark Begich
Dan Sullivan
or Mead Treadwell

democratic
vote deficit

69,014

Total Registered Voters: 499,497

Turnout Score: 54.09

Expected Total Vote: 270,178

Win Number: 140,493


Total Reflex Voters: 209,861

Weighted Party Score: 0.341

Core Democratic Vote: 71,479


Democratic Vote Deficit: 69,104


Total Unreliable Voters: 89,641

Weighted Party Score: 0.439

Democratic-Leaning Unreliables: 20,779


New Registrants: 44,616

Democratic-Leaning New Registrants: 17,985


Conversion Cost: $3,242,658

Volunteer Need: 161,033hrs

3

Montana

John Walsh
Steve Daines

democratic
vote deficit

77,868

Total Registered Voters: 655,745

Turnout Score: 64.46

Expected Total Vote: 422,667

Win Number: 219,787


Total Reflex Voters: 343,749

Weighted Party Score: 0.413

Core Democratic Vote: 141,918


Democratic Vote Deficit: 77,868


Total Unreliable Voters: 138,136

Weighted Party Score: 0.5408

Democratic-Leaning Unreliables: 34,664


New Registrants: 22,041

Democratic-Leaning New Registrants: 10,247


Conversion Cost: $3,659,796

Volunteer Need: 181.692hrs

4

New
Hampshire

Jeanne Shaheen
Scott Brown

democratic
vote deficit

85,502

Total Registered Voters: 877,673

Turnout Score: 58.31

Expected Total Vote: 511,771

Win Number: 266,121


Total Reflex Voters: 409,966

Weighted Party Score: 0.441

Core Democratic Vote: 180,619


Democratic Vote Deficit: 85,502


Total Unreliable Voters: 302,298

Weighted Party Score: 0.5293

Democratic-Leaning Unreliables: 123,356


New Registrants: N/A


Conversion Cost: $4,108,594

Volunteer Need: 199,505hrs

5

Iowa

Bruce Braley
Joni Ernst
or Mark Jacobs

democratic
vote deficit

144,929

Total Registered Voters: 2,124,755

Turnout Score: 54.20

Expected Total Vote: 1,151,530

Win Number: 598,796


Total Reflex Voters: 1,008,745

Weighted Party Score: 0.450

Core Democratic Vote: 453,867


Democratic Vote Deficit: 144,929


Total Unreliable Voters: 545,675

Weighted Party Score: 0.56

Democratic-Leaning Unreliables: 250,269


New Registrants: 55,417

Democratic-Leaning New Registrants: 27,066


Conversion Cost: $6,811,663

Volunteer Need: 338,168hrs

6

Louisiana

Mary Landrieu
Bill Cassidy

democratic
vote deficit

198,164

Total Registered Voters: 2,957,892

Turnout Score: 45.28

Expected Total Vote: 1,339,304

Win Number: 696,438


Total Reflex Voters: 1,224,477

Weighted Party Score: 0.407

Core Democratic Vote: 498,274


Democratic Vote Deficit: 198,164


Total Unreliable Voters: 775,135

Weighted Party Score: 0.6077

Democratic-Leaning Unreliables: 426,084


New Registrants: 62,426

Democratic-Leaning New Registrants: 34,906


Conversion Cost: $9,313,708

Volunteer Need: 462,383hrs

7

Arkansas

Mark Pryor
Tom Cotton

democratic
vote deficit

213,510

Total Registered Voters: 1,596,331

Turnout Score: 53.93

Expected Total Vote: 860,957

Win Number: 447,698


Total Reflex Voters: 697,186

Weighted Party Score: 0.336

Core Democratic Vote: 234,187


Democratic Vote Deficit: 213,510


Total Unreliable Voters: 359,396

Weighted Party Score: 0.5508

Democratic-Leaning Unreliables: 116,601


New Registrants: 97,909

Democratic-Leaning New Registrants: 49,237


Conversion Cost: $10,034,970

Volunteer Need: 498,190hrs

8

Kentucky

Alison Lundergan Grimes
Mitch McConnell

democratic
vote deficit

225,441

Total Registered Voters: 3,077,868

Turnout Score: 44.98

Expected Total Vote: 1,384,451

Win Number: 719,914


Total Reflex Voters: 1,199,775

Weighted Party Score: 0.412

Core Democratic Vote: 494,473


Democratic Vote Deficit: 225,441


Total Unreliable Voters: 595,542

Weighted Party Score: 0.5389

Democratic-Leaning Unreliables: 284,417


New Registrants: 227,756

Democratic-Leaning New Registrants: 121,780


Conversion Cost: $10,595,727

Volunteer Need: 526,029hrs

9

Michigan

Gary Peters
Terri Lynn Land

democratic
vote deficit

229,870

Total Registered Voters: 6,161,521

Turnout Score: 47.76

Expected Total Vote: 2,942,742

Win Number: 1,530,226


Total Reflex Voters: 1,224,477

Weighted Party Score: 0.492

Core Democratic Vote: 1,300,356


Democratic Vote Deficit: 229,870


Total Unreliable Voters: 1,999,327

Weighted Party Score: 0.6187

Democratic-Leaning Unreliables: 654,950


New Registrants: 370,346

Democratic-Leaning New Registrants: 220,121


Conversion Cost: $10,803,890

Volunteer Need: 536,363hrs

10

Colorado

Mark Udall
Cory Gardner

democratic
vote deficit

239,862

Total Registered Voters: 3,570,769

Turnout Score: 53.93

Expected Total Vote: 1,925,716

Win Number: 1,001,372


Total Reflex Voters: 1,641,894

Weighted Party Score: 0.464

Core Democratic Vote: 761,510


Democratic Vote Deficit: 239,862


Total Unreliable Voters: 910,585

Weighted Party Score: 0.5585

Democratic-Leaning Unreliables: 420,444


New Registrants: 129,873

Democratic-Leaning New Registrants: 67,254


Conversion Cost: $11,273,514

Volunteer Need: 559,678hrs

11

North
Carolina

Kay Hagan
Thom Tillis
or Greg Brannon

democratic
vote deficit

542,079

Total Registered Voters: 6,487,485

Turnout Score: 48.21

Expected Total Vote: 3,127,700

Win Number: 1,626,404


Total Reflex Voters: 2,447,961

Weighted Party Score: 0.443

Core Democratic Vote: 1,084,325


Democratic Vote Deficit: 542,079


Total Unreliable Voters: 2,027,448

Weighted Party Score: 0.5672

Democratic-Leaning Unreliables: 1,027,777


New Registrants: 207,682

Democratic-Leaning New Registrants: 105,390


Conversion Cost: $25,447,713

Volunteer Need: 1,264,851hrs

12

Georgia

Michelle Nunn
Jack Kingston
or David Perdue

democratic
vote deficit

663,699

Total Registered Voters: 6,162,629

Turnout Score: 45.95

Expected Total Vote: 2,831,749

Win Number: 1,472,509


Total Reflex Voters: 2,314,297

Weighted Party Score: 0.349

Core Democratic Vote: 808,810


Democratic Vote Deficit: 663,699


Total Unreliable Voters: 1,569,574

Weighted Party Score: 0.5591

Democratic-Leaning Unreliables: 712,813


New Registrants: 203,300

Democratic-Leaning New Registrants: 107,476


Conversion Cost: $31,193,853

Volunteer Need: 1,548,631hrs

*Candidates listed are likely party nominees; in primary races without clear frontrunners, multiple contenders are included.

So how did we come up with all the numbers that led to those ratings? We did it the way campaign strategists would.

As Sasha Issenberg explains in this issue’s cover story, the first crucial piece of election math is known as a win number–generally 52 percent of however many ballots were cast in comparable races, with those extra two-percentage points included in order to play things safe. Then a campaign determines how many votes it can consider in the bank, a tally that’s the product of a four-step calculation. Here’s how we came up with those “base votes” in our rankings of the races that will decide which party will control the Senate next year.

First, there’s the number of registered voters in the jurisdiction, a matter of public record. Then there’s their average turnout score, a 0-to-100 probability scale indicating how likely they are to go to the polls. This is determined via voting histories and proprietary models, the results of which may vary; the turnout scores we used come from our collaborators at Clarity Campaign Labs. (Other projections below were provided by TargetSmart Communications.)

Multiplying those two numbers told us how many of the people who are registered to vote in each of our dozen states almost definitely will. (Reflex voters is The New Republic’s term for them.) That number times the Reflex voters’ average partisanship score—another Clarity statistical model that draws upon myriad variables in consumer and political databases to project which party someone aligns with—tells you how many of the Reflex voters will vote for your side.

And the difference between that answer and the win number is your vote deficit.

Mobilization is the only proven way for a campaign to close that gap. In an electorate highly polarized along partisan lines, few Reflex voters are susceptible to efforts to persuade them to back candidates from the opposing party–and there’s also little evidence that TV ads can have a lasting impact on voter attitudes. What can close a vote defitic, however, is identifying and turning out apathethic sympathizers.

These Unreliable voters, as we’re calling them, have their own average turnout and partisanship scores, and election science has established which tactics for turning them out are most effective. Election researchers have also figured out how much—in dollars or volunteer hours—each additional vote yielded by those tactics costs.

With that final piece of the puzzle, we were able to come up with a truly meaningful gauge of the relative competitiveness of this year’s key Senate races. The formula looks like this:

Of course, no campaign would ever rely solely on volunteer outreach or paid get-out-the-vote communications. But by calculating absolutes for both methods, we were able to compare the work ahead for Democrats in these races, and what it will take the party to hang onto or pick up the seat by transforming the midterm electorate through turnout.

A few final notes on methodology: When calculating the core Democratic vote counts we use below, TargetSmart weighted the partisanship scores in its databases to reflect each state’s actual voting patterns in recent federal elections. Reflex voters are those who voted in 2010 and 2012. New registrants are those added to the rolls since January 1, 2013. We did not include voters from the historically high-turnout election of 2008 who haven’t voted in a federal election since, nor persons who haven’t voted at all; though it’s possible for campaigns to find some votes in those populations, they are considered reaches and therefore were omitted from our ratings.

As more voters tune into the races (and in some cases change their opinions on the candidates) their partisanship scores will change; President Obama’s favorability ratings will also influence that key variable. Later this year, The New Republic will begin regularly updating these rankings based on new public polling data, in order to give you a window into these races that those polls themselves can’t provide.

About the Voter Data in This Package

The numbers at the heart of our May 12, 2014 cover story on the Democratic Party’s challenge in midterm elections were provided by TargetSmart, a Washington D.C.-based political data firm that works with the Democratic Party and helped to build the data infrastructure of the 2012 Obama campaign, as well as by TargetSmart’s sister shop, Clarity Campaign Labs, a targeting, analytics, and polling company that services Democratic and progressive clients across the United States.

TargetSmart’s political and consumer databases contain detailed records on nearly 240 million American adults, and it was from those files that the firm compiled the information that The New Republic used to build the infographics, maps, and Senate-race rankings above, as well as the infographics and maps found in other posts from this project. When certain information is unavailable for an individual voter, it is generated through statistical modeling. Those identified as Democrats are those determined, through predictive models, as likely to identify themselves that way if asked.

Additional analysis was provided by Clarity’s Tom Bonier and TargetSmart’s Chris Brill.

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Correction: Due to a data transcription era, an earlier version of this post misstated the populations and weighted partisanship scores of Unreliable voters in our featured states. Those figures have been corrected.

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Source URL: http://www.newrepublic.com//article/117533/2014-election-predictions-12-senate-races-democrats-might-win-ranked