2026 forecast · California 27th

George Whitesides is all but certain to win California's 27th District.

George Whitesides vs Jason Gibbs. The model has Whitesides ahead by 31.1 points, winning 100 percent of 2,000 simulated elections.

Safe DModel D +31.1Updated October 22, 2026
George Whitesides
Democrat
65.5%
167,708 projected votes
Jason Gibbs
Republican
34.5%
88,169 projected votes
100%Whitesides
0%Gibbs
Whitesides all but certainEach square is one simulated election night, Whitesides wins about 100 of 100
RatingSafe D100% chance for Whitesides
Model marginD +31.1No polls in the race
80 percent rangeD +38.1 to D +24.02,000 simulations
Projected votes255,877Whitesides 65.5%

The district map

Every district in the state, shaded by its rating

California districts

52 districts
Safe DLikely DLean DToss upLean RLikely RSafe R

Vote share

Each candidate's projected share and the range of 80 percent of simulations

George WhitesidesDemocrat · 100% to win
65.5%
Jason GibbsRepublican · 0% to win
34.5%

Scale runs from 25 to 75 percent. The dot is the forecast, the band is the 80 percent range and the brighter tick marks 50 percent.

Projected district vote

255,877 votes
CandidateVotesShare
George Whitesides D167,70865.5%
Jason Gibbs R88,16934.5%
Total255,877100%

Each candidate's expected vote in the On Point simulation, at the forecast's projected turnout.

The trend

Each side's chance of winning over the forecast's recent updates

0%25%50%75%100%100% Whitesides0% Gibbs14 updates agoToday

Polling

Every poll in the average, and how the model reads it

The California governor polling average
25%30%35%40%45%50%55%60%65%JunJulAugSepOct54.7Becerra36.0Hilton
The line is the On Point average: a robust LOWESS fit through the polls, weighted by recency, sample, voter screen and pollster grade, refit three times so outliers count for lessDot size is each poll's weight todayHover or use the arrow keys to read any day
What moves the average today
Manhattan InstituteOct 1 · 1,000 LV · NR16%Becerra +19.0
PPICSep 10 · 1,103 LV · NR16%Becerra +22.0
Independent Voter ProjectOct 2 · 2,906 LV · NR15%Becerra +10.0
Emerson CollegeOct 19 · 1,000 LV · Gold14%Becerra +27.0
Independent Voter ProjectSep 28 · 2,906 LV · NR13%Becerra +10.0
UC Berkeley Citrin Center/TrueDot/PoliticoSep 14 · 1,983 LV · B11%Becerra +18.0
Every other poll together: 15%

This is the same On Point polling average as the full average page. The forecast reads the polls through its own Election Day projection, shown as the On Point average in the table below, and blends it with partisan lean and fundamentals.

Polls of the race

Full average
PollsterSampleAgeMargin
On Point averageWeighted averageNo polls

Each margin is the poll as the pollster published it. The forecast counts every poll after its house effect and the undecided split, which is what the trail above shows; hover a margin for the counted value. Lean R and Lean D mark partisan leaning firms.

Model margin
Whitesides +31.1
Chance of winning
George Whitesides100%
Jason Gibbs0%
Simulated vote
George Whitesides65.5%
Jason Gibbs34.5%
How the model gets there
Partisan leanR +10.0
FundamentalsD +30.9
With pollsD +29.9
Early vote turnoutD +1.2
With early voteD +31.1

Read from 0 ballots cast so far in California, against the party mix the forecast expected of them, with similar states and primary turnout. Early vote tracker

How we got here

From the state's partisan lean to the forecast, one stage at a time

D +37R +37Partisan leanthe state's baselineR +10.0Fundamentalsapproval, economy, candidatesD +30.9With pollsno pollsD +29.9With early voteturnout so farD +31.1
Methodology
Every county is rebuilt by simulating voters going to the polls, 2,000 times, from On Point Polling survey data, past results, and the polling average. How the model works.