California · Governor

Who is running?

Xavier Becerra (Democratic), Steve Hilton (Republican). The margin below is Xavier Becerra minus the other candidate in the main contest; the rest are on the ballot and not in it.

The race, in brief

California elects a governor on November 3, 2026, and the seat is open: Democratic incumbent Gavin Newsom is ineligible for a third term. The text notes that Republicans have not won a California governor's race since 2006. The state profile on file records a Hispanic share of 0.4, a white non-Hispanic share of 0.3 and a college share of 0.365.

The June 2 top-two primary had 61 candidates. Democrat Xavier Becerra, former U.S. secretary of health and human services and former state attorney general, finished first with 27.98%, and Republican Steve Hilton, a political commentator and former adviser to David Cameron, second with 24.59%. Tom Steyer (22.79%) and Chad Bianco (10.17%) followed. Before the primary, Donald Trump's endorsement of Hilton eased fears of a two-Republican general. Eric Swalwell suspended his campaign in April after sexual assault allegations and left Congress on April 14.

All seven raters listed call the race D, dated from June 5, 2026 (RealClearPolitics) to September 23, 2026 (Decision Desk HQ). The page's polling average is Becerra 57.7%, Hilton 34.5%, Becerra +23.2%. The latest listed polls are Berkeley IGS (September 15–20, 2026), Becerra 58% to 33%, and SurveyUSA (September 15–20, 2026), 55% to 33%. The only fundraising figures are primary-period reports as of May 31, 2026: Becerra raised $6,051,826 and Hilton $7,332,985. A CNN debate is set for September 30, 2026.

A paragraph quoting a model forecast from the day this brief was written is omitted; the current forecast is at the top of this page.

The facts, each beside its sentence

Not in the source: No general-election fundraising figures; the only reports are primary-period, as of May 31, 2026.; The forecast rows carry no basis field, so the brief cannot say what the model rests on.; Rater calls are given only as 'D', with no Lean/Likely/Safe detail.; No state presidential results or previous governor's race margins are given in the text.; The September 30, 2026 debate outcome is not in the text.

Read from the district's section of Wikipedia's state page (CC BY-SA), archived as c9698f558950; written by claude-opus-5-5 (batch reader) on 2026-09-30 and checked mechanically: every quote occurs verbatim in the archived text, every number in the brief occurs in the inputs. No probability here is the reader's.

How it has voted for president

A shift of 11.4 points toward the Republicans from 2016 to 2024. county returns summed; MEDSL county file (2016), an MIT-licensed county file (2020, checked against certified state results) and MEDSL precinct returns (2024). For a district split across counties this is an estimate, and where the state published the exact 2024 figure for these lines, that exact figure is the one the model uses.

The state in numbers

ACS 5-year state tables; BLS county unemployment and BEA county income, transfers and jobs summed to the state. Every figure is a named column of a named public-domain table, archived before it was read.

Who is ahead, and by how much?

Two numbers because they answer two questions. The nowcast is where opinion stands; the election-day forecast is where it is likely to end up.

How likely is each to win?

Monte Carlo error is ±0.0 points. A change smaller than that is simulation noise rather than news, and this page will not describe it as movement.

How wide is the range?

Nowcast: 90% of simulations fall between +10.1 and +32.8 points. Election day: +9.0 to +34.9. The election-day interval is 3.2 points wider, which is the 33 days of movement still to come.

What is the uncertainty made of?

Total sd 8.17 points, made of race-specific polling error 37%, latent opinion 30%, drift to election day 24%, correlated polling error 9%. The decomposition is stored with the forecast rather than reconstructed, so a probability whose dominant input is a placeholder is visibly that.

What evidence is this built on?

64 polls, most recent 2026-09-20. 27% verified against a primary source.

What changed since the last run?

Shaded band is the 90% interval, line is the central estimate, positive is Xavier Becerra ahead of Steve Hilton. Over 15 stored forecasts the central estimate moved +0.3 points. There were 7 specification changes (marked on the axis) and no new polls arrived over this window — so every movement in this chart is a change to the model, not a change in the race.

Since 2026-10-01: margin +0.00 points, win probability +0.0 points, on +0 polls.

Not answered here: why it changed. Splitting a move into new polls, time and specification means re-running the earlier model against the later inputs -- two extra posterior fits -- so it is computed on a cadence (scripts/attribute_forecasts.py) rather than while you wait. This pair of runs has not been decomposed yet. The size of the move is shown; the cause is not guessed at.

How has this model done before?

Measured on 230 forecasts across 230 races in cycles 2016,2018,2020,2022,2024: mean absolute error 4.56 points, Brier score 0.0543. The nominal 90% interval contained the result 94% of the time, the 80% interval 84%, and the 50% interval 47%. Read that with care: a national polling miss moves every race in a cycle at once, so the sample size for a question about the intervals is 5 cycle(s), not 230 forecasts. Per cycle -- bias +1.644 pts; 2016: n=43 bias=+4.68 cov90=0.860; 2018: n=63 bias=-0.52 cov90=1.000; 2020: n=35 bias=+5.44 cov90=0.886; 2022: n=54 bias=-0.60 cov90=0.944; 2024: n=35 bias=+1.48 cov90=1.000.

Where did every number come from?

Nowcast run b5bfa13a-3a47-45cc-b55e-fe04e6e664d8 and election-day run d97a22f8-a3d1-4e65-ad4f-a30126f3a0f8, model single_race_latent/0.8.1 at commit bdf7e83107c17a2399efe61a44ef1bbee48f9284, seeds 20260924 and 20260924.