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.
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.