South Carolina · Governor

Who is running?

Jermaine Johnson (Democratic), Alan Wilson (Republican), Michael Addison (no party recorded), Walid Hakim (Green). The margin below is Jermaine Johnson minus the other candidate in the main contest; the rest are on the ballot and not in it.

The race, in brief

South Carolina elects a new governor on November 3, 2026: Republican Henry McMaster cannot seek a third consecutive term. Democrats have not won a gubernatorial election in the state since 1998. The state profile records a median household income of 66818.0, a white non-Hispanic share of 0.6 and a college share of 0.3.

The Republican nominee is Attorney General Alan Wilson, in office since 2011, with state senator Mike Reichenbach as running mate. Lieutenant Governor Pamela Evette led the June 9 first round with 28.9%, helped by President Trump's endorsement, to Wilson's 26.2%; after Trump announced support for both, Wilson won the June 23 runoff with 68.6%. The Democratic nominee is state representative Jermaine Johnson, with Sam Skardon as running mate; he won the June 9 primary with 59.7% over Billy Webster and Mullins McLeod. United Citizens Party nominee Michael Addison and Green nominee Walid Hakim are also running.

Every rater listed calls the race R: the Cook Political Report, Decision Desk HQ, Fox News, Inside Elections, RealClearPolitics, Sabato's Crystal Ball and Silver Bulletin; the Cook, Inside Elections and Sabato calls date from 2025. The two general-election polls, both from Democratic firms, have Wilson ahead: Hart Research (August 12–15, 2026) 50% to 42%, and Public Policy Polling (July 16–17, 2026) 45% to 37%.

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: facts.forecast carries no basis field, so it is not stated whether the model used the two general-election polls the text lists.; Both general-election polls in the text come from Democratic-aligned firms; no nonpartisan or Republican general-election poll is listed.; The text gives no fundraising figures for any candidate.; The text gives no presidential results for the state and no vote shares from earlier gubernatorial elections.; No rating is finer than 'R'; three of the seven ratings predate the primaries.

Read from the district's section of Wikipedia's state page (CC BY-SA), archived as 8900d10988b4; written by claude-fable-5-1 (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 3.2 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 ±0.2 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 -29.6 and +5.7 points. Election day: -29.2 to +8.6. The election-day interval is 2.4 points wider, which is the 33 days of movement still to come.

What is the uncertainty made of?

Total sd 11.53 points, made of latent opinion 65%, race-specific polling error 19%, drift to election day 12%, correlated polling error 4%. 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?

2 polls, most recent 2026-08-15. 50% verified against a primary source.

What changed since the last run?

Shaded band is the 90% interval, line is the central estimate, positive is Jermaine Johnson ahead of Alan Wilson. Over 13 stored forecasts the central estimate moved -2.1 points. There were 6 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 ee563dad-beb9-4d01-825d-7a00b6bf8c07 and election-day run ea44f718-6082-4fe7-a7ef-ab803305fd2a, model single_race_latent/0.8.1 at commit bdf7e83107c17a2399efe61a44ef1bbee48f9284, seeds 20260924 and 20260924.