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Chance the Democrat wins (16.7%)
Chance the Republican wins (83.3%)
We'll be updating our forecasts every time new data is available, every day through Nov. 6.
The Classic version of our model projects a race’s outcome by taking a weighted average of polls of a district (if available), polls of similar districts (CANTOR) and non-polling factors (fundamentals). It is then reverted toward a mean based on long-term trends in midterms and presidential approval ratings.
R+7.6
Adjusted polls
R+15.1
CANTOR
R+2.7
Fundamentals
R+19.5
Experts
R+10.3
Lite
R+5.7
Classic
R+10.3
Deluxe
<0.1
<0.1
Historical adjustment
Key
More weight
Less
We've collected one poll for the Indiana 9th. We’re adjusting poll results in three ways: Polls of registered voters or all adults are adjusted to a likely-voter basis; older polls are adjusted based on shifts in the generic congressional ballot since the poll was conducted; and polls are adjusted for house effects (the tendency for a firm’s polls to lean toward Democrats or Republicans). Polls with larger sample sizes and those conducted by higher-quality polling agencies are given more weight, as are more recent polls.
Adjustments | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
dates | pollster | sample | weight | Watson | Hollingsworth | margin | likely voter | Time-line | House effects | Adjusted margin | |
Oct. 27-29 10/27-29 | Change Research | 541 | LV | 1.29 | 45% | 52% | R+7.0 | — | <0.1 | 0.6 | R+7.6 |
Key
A = adults
RV = Registered voters
V = voters
LV = likely voters
= partisan poll
Our district similarity scores are based on demographic, geographic and political characteristics; if two districts have a score of 100, it means they are perfectly identical. These scores inform a system we use — CANTOR, or Congressional Algorithm using Neighboring Typologies to Optimize Regression — to infer what polling would say in unpolled or lightly polled districts, given what it says in similar districts.
Sim. score | Polling avg. | ||
---|---|---|---|
IN-4 | 82 | — | |
OH-5 | 79 | — | |
OH-15 | 78 | — | |
KS-2 | 76 | D+0.1 | |
MI-2 | 75 | R+8.0 | |
IN-8 | 75 | — | |
IN-3 | 74 | R+13.7 | |
OH-8 | 73 | — | |
IL-16 | 73 | R+14.6 | |
MI-7 | 72 | R+6.6 |
The Classic and Deluxe versions of our model use several non-polling factors to forecast the vote share margin in each district.
Factor | Impact | Explanation |
---|---|---|
Incumbency | 3.2 | Trey Hollingsworth has been elected to 1 term. Congress has only a 20.1% approval rating, reducing the incumbency advantage. |
District partisanship | 9.3 | IN-9 is 25.3 percentage points more Republican-leaning than the country overall, based on how it has voted in recent presidential and state legislative elections. It voted for Trump in 2016 and Romney in 2012. |
Incumbent's margin in last election | 7.1 | Hollingsworth won by 13.7 percentage points in 2016 in an open-seat race. |
Generic ballot | 7.0 | Democrats lead by an average of 8.6 percentage points in polls of the generic congressional ballot. |
Fundraising | 9.0 | As of Oct. 17, Liz Watson had raised $1,873,000 in individual contributions (85% of all such contributions to the major-party candidates); Hollingsworth had raised $322,000 (15%). |
Incumbent's voting record in Congress | 1.5 | Hollingsworth has voted with Republicans 84% of the time in roll-call votes in recent sessions of Congress. |
Challenger experience | 0.7 | Watson has never held elected office. |
Scandals | 0.0 | Neither candidate is involved in a scandal. |
Total | R+2.7 |
The Deluxe version of our model calculates an implied margin for each race based on expert race ratings from The Cook Political Report, Inside Elections and Sabato's Crystal Ball; it then adjusts that margin toward its estimate of the national political environment.
Equivalent Margin | |||
---|---|---|---|
Expert | Rating | Raw | Adjusted |
Cook Political Report | R+23.8 | R+23.2 | |
Inside Elections | R+23.8 | R+22.9 | |
Sabato's Crystal Ball | R+12.1 | R+12.5 | |
Average | R+19.9 | R+19.5 |
Nate Silver explains the methodology behind our 2018 midterms forecast. Read more …
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