Read the result, then trace it back to the races and sources. Each state has its calculation card: hover over the map, search a name or pick a state.
One race. Its numbers. Its calculation. Hover, tap or search for a state.
27 posts. Expected governorships by party, 90% range, chances of winning the most, and governors elected in 2022.
| Party | Expected | 90% | Most | 2022 |
|---|---|---|---|---|
| PSD | 5.3 | 4–7 | 53% | 2 |
| PL | 5.2 | 4–7 | 41% | 2 |
| Republicanos | 3.6 | 2–5 | 6% | 2 |
| PP | 3.5 | 3–4 | 2 | |
| MDB | 2.6 | 1–4 | 1% | 3 |
| União Brasil | 2.6 | 2–3 | 4 | |
| PT | 1.9 | 1–3 | 4 | |
| PSDB | 1.2 | 0–2 | 3 | |
| Podemos | 0.5 | 0–1 | 0 | |
| PDT | 0.3 | 0–1 | 0 | |
| PSB | 0.3 | 0–1 | 3 |
| State | Favorite | Rival | Chances |
|---|---|---|---|
| AC Acre | Mailza Assis PP | Alan Rick Republicanos | 51% |
| PA Pará | Dr Daniel Podemos | Hana Ghassan MDB | 52% |
| CE Ceará | Ciro Gomes PSDB | Elmano de Freitas PT | 55% |
| BA Bahia | ACM Neto União Brasil | Jerônimo Rodrigues PT | 56% |
| AL Alagoas | JHC PSDB | Renan Filho MDB | 66% |
| MT Mato Grosso | Otaviano Pivetta Republicanos | Wellington Fagundes PL | 68% |
| RS Rio Grande do Sul | Zucco PL | Juliana Brizola PDT | 68% |
| ES Espírito Santo | Ricardo Ferraço MDB | Lorenzo Pazolini Republicanos | 68% |
| PE Pernambuco | Raquel Lyra PSD | João Campos PSB | 70% |
The 2026 favorite is not from the party of the governor elected in 2022. 22 of 27.
| State | Elected in 2022 | 2026 favorite | Chances | Rating |
|---|---|---|---|---|
| TO Tocantins | Wanderlei Barbosa Republicanos | Professora Dorinha União Brasil | >99% | Safe |
| MS Mato Grosso do Sul | Eduardo Riedel PSDB | Eduardo Riedel PP | >99% | Safe |
| PB Paraíba | João PSB | Lucas Ribeiro PP | >99% | Safe |
| GO Goiás | Ronaldo Caiado União Brasil | Daniel Vilela MDB | >99% | Safe |
| RR Roraima | Antonio Denarium PP | Arthur Henrique PL | >99% | Safe |
| MG Minas Gerais | Zema Novo | Cleitinho Azevedo Republicanos | 98% | Safe |
| AP Amapá | Clécio SOLIDARIEDADE | Dr Furlan PSD | 98% | Safe |
| DF Federal District | Ibaneis Rocha MDB | Celina Leão PP | 94% | Likely |
| RN Rio Grande do Norte | Fatima Bezerra PT | Allyson União Brasil | 93% | Likely |
| PR Paraná | Carlos Massa Ratinho Junior PSD | Sergio Moro PL | 93% | Likely |
| RO Rondônia | Coronel Marcos Rocha União Brasil | Marcos Rogério PL | 91% | Likely |
| RJ Rio de Janeiro | Cláudio Castro PL | Eduardo Paes PSD | 91% | Likely |
| MA Maranhão | Carlos Brandão PSB | Eduardo Braide PSD | 87% | Likely |
| AM Amazonas | Wilson Lima União Brasil | Omar Aziz PSD | 78% | Likely |
| PE Pernambuco | Raquel Lyra PSDB | Raquel Lyra PSD | 70% | Leans |
| ES Espírito Santo | Renato Casagrande PSB | Ricardo Ferraço MDB | 68% | Leans |
| RS Rio Grande do Sul | Eduardo Leite PSDB | Zucco PL | 68% | Leans |
| MT Mato Grosso | Mauro Mendes União Brasil | Otaviano Pivetta Republicanos | 68% | Leans |
| AL Alagoas | Paulo Dantas MDB | JHC PSDB | 66% | Leans |
| BA Bahia | Jerônimo PT | ACM Neto União Brasil | 56% | Toss-up |
| CE Ceará | Elmano de Freitas PT | Ciro Gomes PSDB | 55% | Toss-up |
| PA Pará | Helder MDB | Dr Daniel Podemos | 52% | Toss-up |
Polls published since July 3, from the least to the best covered states.
| State | Polls | Pollsters | Latest | Days | Registered with TSE |
|---|---|---|---|---|---|
| Roraima | 8 | 5 | 24/09 | 8 | 87% |
| Rondônia | 11 | 6 | 29/09 | 3 | 96% |
| Paraíba | 14 | 9 | 27/09 | 5 | 96% |
| Mato Grosso do Sul | 15 | 9 | 30/09 | 2 | 94% |
| Santa Catarina | 15 | 9 | 30/09 | 2 | 87% |
| Amapá | 16 | 7 | 29/09 | 3 | >99% |
| Piauí | 17 | 11 | 28/09 | 4 | 84% |
| Rio Grande do Sul | 18 | 9 | 28/09 | 4 | 88% |
| Mato Grosso | 19 | 8 | 29/09 | 3 | 83% |
| Acre | 21 | 12 | 29/09 | 3 | 70% |
| Maranhão | 21 | 10 | 24/09 | 8 | 93% |
| Tocantins | 21 | 11 | 25/09 | 7 | >99% |
| Ceará | 22 | 10 | 28/09 | 4 | 80% |
| Amazonas | 25 | 15 | 29/09 | 3 | 82% |
| Espírito Santo | 26 | 8 | 29/09 | 3 | 96% |
| Bahia | 27 | 12 | 28/09 | 4 | 86% |
| Alagoas | 28 | 12 | 29/09 | 3 | 93% |
| Goiás | 28 | 12 | 27/09 | 5 | 94% |
| Sergipe | 29 | 14 | 26/09 | 6 | 96% |
| Pará | 32 | 12 | 28/09 | 4 | 81% |
| Minas Gerais | 33 | 10 | 01/10 | 1 | 93% |
| Federal District | 38 | 13 | 01/10 | 1 | 85% |
| Pernambuco | 39 | 19 | 01/10 | 1 | 94% |
| Paraná | 40 | 11 | 01/10 | 1 | 99% |
| Rio de Janeiro | 40 | 9 | 01/10 | 1 | 92% |
| Rio Grande do Norte | 40 | 23 | 28/09 | 4 | 84% |
| São Paulo | 40 | 15 | 30/09 | 2 | 89% |
| State | Favorite | Main rival | Chances | Round 1 | Rating | Incumbent (2022) |
|---|---|---|---|---|---|---|
| Acre | Mailza Assis PP | Alan Rick Republicanos | 51% | 18% | Toss-up | Gladson Cameli PP |
| Alagoas | JHC PSDB | Renan Filho MDB | 66% | 60% | Leans | Paulo Dantas MDB |
| Amazonas | Omar Aziz PSD | Professora Maria do Carmo PL | 78% | 4% | Likely | Wilson Lima União Brasil |
| Amapá | Dr Furlan PSD | Clécio União Brasil | 98% | 89% | Safe | Clécio SOLIDARIEDADE (running) |
| Bahia | ACM Neto União Brasil | Jerônimo Rodrigues PT | 56% | 42% | Toss-up | Jerônimo PT (running) |
| Ceará | Ciro Gomes PSDB | Elmano de Freitas PT | 55% | 47% | Toss-up | Elmano de Freitas PT (running) |
| Federal District | Celina Leão PP | Arruda PSD | 94% | 25% | Likely | Ibaneis Rocha MDB |
| Espírito Santo | Ricardo Ferraço MDB | Lorenzo Pazolini Republicanos | 68% | 18% | Leans | Renato Casagrande PSB |
| Goiás | Daniel Vilela MDB | Marconi Perillo PSDB | >99% | 36% | Safe | Ronaldo Caiado União Brasil |
| Maranhão | Eduardo Braide PSD | Orleans Brandão MDB | 87% | 16% | Likely | Carlos Brandão PSB |
| Minas Gerais | Cleitinho Azevedo Republicanos | Patrus Ananias PT | 98% | 31% | Safe | Zema Novo |
| Mato Grosso do Sul | Eduardo Riedel PP | Fábio Trad PT | >99% | 78% | Safe | Eduardo Riedel PSDB (running) |
| Mato Grosso | Otaviano Pivetta Republicanos | Wellington Fagundes PL | 68% | 22% | Leans | Mauro Mendes União Brasil |
| Pará | Dr Daniel Podemos | Hana Ghassan MDB | 52% | 43% | Toss-up | Helder MDB |
| Paraíba | Lucas Ribeiro PP | Efraim Filho PL | >99% | 98% | Safe | João PSB |
| Pernambuco | Raquel Lyra PSD | João Campos PSB | 70% | 51% | Leans | Raquel Lyra PSDB (running) |
| Piauí | Rafael Fonteles PT | Joel Rodrigues PP | >99% | 96% | Safe | Rafael Fonteles PT (running) |
| Paraná | Sergio Moro PL | Requião Filho PDT | 93% | 39% | Likely | Carlos Massa Ratinho Junior PSD |
| Rio de Janeiro | Eduardo Paes PSD | Douglas Ruas PL | 91% | 37% | Likely | Cláudio Castro PL |
| Rio Grande do Norte | Allyson União Brasil | Álvaro Dias PL | 93% | 29% | Likely | Fatima Bezerra PT |
| Rondônia | Marcos Rogério PL | Adailton Furia PSD | 91% | 26% | Likely | Coronel Marcos Rocha União Brasil |
| Roraima | Arthur Henrique PL | Soldado Sampaio Republicanos | >99% | 68% | Safe | Antonio Denarium PP |
| Rio Grande do Sul | Zucco PL | Juliana Brizola PDT | 68% | 21% | Leans | Eduardo Leite PSDB |
| Santa Catarina | Jorginho Mello PL | João Rodrigues PSD | >99% | 79% | Safe | Jorginho Mello PL (running) |
| Sergipe | Fábio PSD | Valmir de Francisquinho Republicanos | 82% | 46% | Likely | Fábio PSD (running) |
| São Paulo | Tarcísio Republicanos | Fernando Haddad PT | 96% | 78% | Safe | Tarcísio Republicanos (running) |
| Tocantins | Professora Dorinha União Brasil | Laurez Moreira PSD | >99% | 95% | Safe | Wanderlei Barbosa Republicanos |
A predictive model is not one more poll. A poll interviews a sample and describes opinion at a given moment. A model interviews no one. It gathers what can be measured, published surveys, past election results and the electoral rules, and derives from them a distribution of possible outcomes, with their probability. It does not say a party will win so many seats. It says within which range it will finish, and what each candidate’s chances of election are.
Two pollsters published on the same day can differ by several points. The model aggregates every survey published in each state and registered with the Superior Electoral Court, taking into account their age, their size and the pollsters’ reliability.
Polls get it wrong, sometimes badly. The model builds in the size of the errors seen in past elections, without assuming in advance that one side will be underestimated. That is what gives each candidate their chances, and each list its range.
For each state, the model starts from the published polls. A governor is elected in the first round with over half the valid votes, otherwise a runoff takes place on October 25: the model simulates both. In the Senate, each voter has two votes and the top two are elected, in a single round.
A single forecast would give a false sense of certainty. The model therefore replays each race twenty thousand times, varying what is genuinely uncertain. The probability shown is the share of simulations in which the event occurs.
Uncertainty is this model’s product, never its flaw. The simulations are reproducible, and the forecast on the eve of the vote is frozen, then compared with the official results.
Election results and candidacies: Superior Electoral Court. 2026 polls: surveys published by pollsters and registered with the Superior Electoral Court.
Export gouverneurs_2026.csv ↗ · Export the forecasts as JSON ↗
All rights belong to Le Millénaire SAS, 47 rue de Vivienne, 75002 Paris.
Model designed by
Project director: William Thay
Deputy project director: Pierre Clairé
Political analysis and data: Matthieu Hocque
Data analysis, mathematics and validation: Florian Gérard-Mercier