Forecast - Brazil 2026 general elections: Federal Senate

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PL leads the Senate renewal
Le Millénaire · 20 000 simulations · updated October 2, 2026 · first round on October 4, 2026
Polls through 2026-10-01 · election in 2 days
The balance of power on October 4
13.3
PL · expected seats of 54
7.4
MDB · expected seats of 54
19
toss-up races

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.

The 27 federal units, in three views

One race. Its numbers. Its calculation. Hover, tap or search for a state.

Balance of power

54 of 81 seats up. Expected seats by party, 90% range and chances of winning the most seats.

PartyExpected seats90%Most seats
PL13.39–1892%
MDB7.45–103%
PT6.73–105%
PP4.22–7
União Brasil3.72–6
PSB3.62–5
PSD3.41–6
Republicanos2.81–5
Podemos2.11–3
PDT2.00–4
Novo1.60–3
PSDB1.20–3
REDE1.00–2
PSOL0.60–2

Candidates in the 25–75% range

StateCandidatePollsChances of election
SP São PauloSimone Tebet PSB20.4%50%
DF Federal DistrictLeila do Vôlei PDT21.8%50%
RS Rio Grande do SulManuela d'Ávila PSOL20.7%51%
AP AmapáRandolfe PT20.6%48%
SE SergipeDelegado André David Republicanos18.1%52%
SP São PauloMarina Silva REDE20.7%52%
SC Santa CatarinaCarlos Bolsonaro PL21.3%52%
CE CearáLuizianne REDE24.6%52%
AL AlagoasRenan MDB23.5%52%
MG Minas GeraisCarlos Viana PSD18.4%47%
CE CearáCapitão Wagner União Brasil25.2%54%
RO RondôniaBruno Scheid PL19.6%46%
TO TocantinsAlexandre Guimarães MDB16.6%46%
RO RondôniaSílvia Cristina PP19.4%45%
SP São PauloGuilherme Derrite PP21.6%55%
PR ParanáFilipe Barros PL19.0%45%
MA MaranhãoFufuca PP18.4%44%
PI PiauíCiro Nogueira PP25.4%56%
AP AmapáLucas Barreto PSD19.5%43%
PA ParáDelegado Éder Mauro PL22.0%57%
SC Santa CatarinaEsperidião Amin PP22.3%57%
PR ParanáAlexandre Curi Republicanos18.6%43%
RJ Rio de JaneiroCarlos Jordy PL16.3%42%
AC AcreMarcio Bittar PL21.6%58%
RS Rio Grande do SulMarcel van Hattem Novo22.4%59%
DF Federal DistrictBia Kicis PL20.1%41%
RR RoraimaNicoletti PL22.2%59%
SE SergipeRogerio Carvalho PT16.1%40%
BA BahiaJaques Wagner PT25.1%60%
PI PiauíJúlio César o Julim do Lula PSD25.3%60%
SE SergipeDelegado Alessandro MDB16.0%40%
SP São PauloAndré do Prado PL18.4%40%
RS Rio Grande do SulSanderson PL18.0%39%
PR ParanáDeltan Dallagnol Novo22.7%61%
MT Mato GrossoJanaina Riva MDB21.8%62%
SE SergipeAndré Moura União Brasil15.7%37%
MG Minas GeraisDomingos Sávio PL16.2%37%
MG Minas GeraisMarília Campos PT21.1%63%
TO TocantinsGaguim União Brasil15.2%37%
RR RoraimaHelena da Asatur PSD17.8%36%
MA MaranhãoLahesio Bonfim Novo17.0%36%
RJ Rio de JaneiroCarlos Portinho PL15.1%36%
MG Minas GeraisAécio Neves PSDB15.0%36%
GO GoiásGustavo Gayer PL21.5%64%
AL AlagoasMarina JHC PSDB26.2%65%
PR ParanáGleisi PT17.2%35%
PE PernambucoHumberto Costa PT24.5%66%
AM AmazonasCapitão Alberto Neto PL26.4%66%
PE PernambucoMendonça Filho PL18.2%34%
BA BahiaJoão Roma PL19.5%33%
GO GoiásDr Zacharias Calil MDB15.5%33%
AC AcreMara Rocha Republicanos16.6%33%
AL AlagoasArthur Lira PP26.9%67%
ES Espírito SantoFabiano Contarato PT13.1%32%
RN Rio Grande do NorteZenaide Maia PSD24.0%68%
AC AcreJorge Viana PT16.1%31%
AC AcreGladson Camelí PP24.0%69%
MT Mato GrossoZé Medeiros PL15.8%31%
RS Rio Grande do SulPimenta PT16.3%30%
RR RoraimaChico Rodrigues PSB16.6%30%
MA MaranhãoRoseana Sarney MDB24.2%70%
ES Espírito SantoSergio Meneguelli PSD12.9%30%
PA ParáChicão União Brasil16.0%29%
SC Santa CatarinaCarol de Toni PL26.0%71%
DF Federal DistrictErika Kokay PT17.4%28%
MA MaranhãoWeverton Rocha PDT14.7%28%
BA BahiaAngelo Coronel Republicanos18.0%27%
PB ParaíbaVeneziano MDB25.2%73%
RR RoraimaTeresa Surita MDB25.7%74%
CE CearáCid Gomes PSB29.9%74%
PB ParaíbaNabor Republicanos16.8%26%
AM AmazonasWilson Lima União Brasil17.5%26%

Seats that would change party

Compared with the two senators elected in 2018, whose terms end. 45 of 54.

StateElected in 20182026 favoriteChancesRating
ES Espírito SantoFabiano Contarato REDERenato Casagrande PSB96%Toss-up
MS Mato Grosso do SulNelsinho Trad PTBReinaldo Azambuja PL91%Likely
MT Mato GrossoJayme Campos DEMMauro Mendes União Brasil91%Leans
RN Rio Grande do NorteCapitão Styvenson REDEStyvenson Valentim Podemos90%Leans
AP AmapáRandolfe REDERayssa Furlan Podemos86%Toss-up
AM AmazonasPlinio Valerio PSDBEduardo Braga MDB85%Leans
MS Mato Grosso do SulSoraya Thronicke PSLCapitão Contar PL82%Likely
RO RondôniaMarcos Rogério DEMDr Fernando Máximo PL80%Toss-up
TO TocantinsEduardo Gomes SOLIDARIEDADEEduardo Gomes PL80%Toss-up
GO GoiásVanderlan PPGracinha Caiado União Brasil79%Leans
DF Federal DistrictLeila do Vôlei PSBMichelle Bolsonaro PL79%Toss-up
PI PiauíCiro Nogueira PPMarcelo Castro MDB79%Toss-up
RJ Rio de JaneiroFlávio Bolsonaro PSLBenedita da Silva PT75%Toss-up
CE CearáCid Gomes PDTCid Gomes PSB74%Toss-up
RR RoraimaChico Rodrigues DEMTeresa Surita MDB74%Toss-up
PB ParaíbaDaniella Ribeiro PPVeneziano MDB73%Leans
MA MaranhãoWeverton PDTRoseana Sarney MDB70%Toss-up
AC AcrePetecão PSDGladson Camelí PP69%Toss-up
RN Rio Grande do NorteDr Zenaide Maia PHSZenaide Maia PSD68%Leans
PE PernambucoJarbas MDBHumberto Costa PT66%Leans
AL AlagoasRenan MDBMarina JHC PSDB65%Toss-up
GO GoiásJorge Kajuru PRPGustavo Gayer PL64%Leans
MG Minas GeraisRodrigo Pacheco DEMMarília Campos PT63%Toss-up
MT Mato GrossoFávaro PSDJanaina Riva MDB62%Leans
PR ParanáProfessor Oriovisto Guimaraes PodemosDeltan Dallagnol Novo61%Toss-up
BA BahiaAngelo Coronel PSDJaques Wagner PT60%Leans
RR RoraimaMecias de Jesus PRBNicoletti PL59%Toss-up
RS Rio Grande do SulLuis Carlos Heinze PPMarcel van Hattem Novo59%Toss-up
AC AcreMárcio Bittar MDBMarcio Bittar PL58%Toss-up
SC Santa CatarinaJorginho Mello PREsperidião Amin PP57%Toss-up
PA ParáZequinha Marinho PSCDelegado Éder Mauro PL57%Toss-up
SP São PauloMajor Olimpio PSLGuilherme Derrite PP55%Toss-up
CE CearáEduardo Girão PROSCapitão Wagner União Brasil54%Toss-up
SP São PauloMara Gabrilli PSDBMarina Silva REDE52%Toss-up
SE SergipeDelegado Alessandro Vieira REDEDelegado André David Republicanos52%Toss-up
RS Rio Grande do SulPaulo Paim PTManuela d'Ávila PSOL51%Toss-up
DF Federal DistrictIzalci PSDBLeila do Vôlei PDT50%Toss-up
AP AmapáLucas Barreto PTBRandolfe PT48%Toss-up
MG Minas GeraisJornalista Carlos Viana PHSCarlos Viana PSD47%Toss-up
RO RondôniaConfucio Moura MDBBruno Scheid PL46%Toss-up
TO TocantinsIrajá PSDAlexandre Guimarães MDB46%Toss-up
PR ParanáFlavio Arns REDEFilipe Barros PL45%Toss-up
MA MaranhãoEliziane Gama PPSFufuca PP44%Toss-up
RJ Rio de JaneiroArolde de Oliveira PSDCarlos Jordy PL42%Toss-up
ES Espírito SantoMarcos do Val PPSFabiano Contarato PT32%Toss-up

Polls and coverage

Polls published since July 3, from the least to the best covered states.

StatePollsPollstersLatestDaysRegistered with TSE
Roraima7524/09887%
Paraíba12927/09596%
Rondônia12629/09396%
Mato Grosso16829/09383%
Rio Grande do Sul16928/09488%
Santa Catarina16930/09287%
Amapá17729/093>99%
Amazonas191529/09382%
Mato Grosso do Sul20930/09294%
Maranhão211024/09893%
Piauí211128/09484%
Bahia221228/09486%
Espírito Santo22829/09396%
Tocantins221125/097>99%
Sergipe231426/09696%
Acre251229/09370%
Rio de Janeiro25901/10192%
Goiás261227/09594%
Minas Gerais261001/10193%
Pará261228/09481%
Ceará271028/09480%
Alagoas281229/09393%
Federal District331301/10185%
Rio Grande do Norte342328/09484%
São Paulo351530/09289%
Pernambuco381901/10194%
Paraná381101/10199%

All races

StateFirstSecondSecond’s chancesThird’s chancesRatingElected in 2018
AcreGladson Camelí PPMarcio Bittar PL58%33%Toss-upPetecão PSD
Márcio Bittar MDB
AlagoasArthur Lira PPMarina JHC PSDB65%52%Toss-upRodrigo Cunha PSDB
Renan MDB
AmazonasEduardo Braga MDBCapitão Alberto Neto PL66%26%LeansPlinio Valerio PSDB
Eduardo Braga MDB
AmapáRayssa Furlan PodemosRandolfe PT48%43%Toss-upRandolfe REDE
Lucas Barreto PTB
BahiaRui Costa PTJaques Wagner PT60%33%LeansJaques Wagner PT
Angelo Coronel PSD
CearáCid Gomes PSBCapitão Wagner União Brasil54%52%Toss-upCid Gomes PDT
Eduardo Girão PROS
Federal DistrictMichelle Bolsonaro PLLeila do Vôlei PDT50%41%Toss-upLeila do Vôlei PSB
Izalci PSDB
Espírito SantoRenato Casagrande PSBFabiano Contarato PT32%30%Toss-upFabiano Contarato REDE
Marcos do Val PPS
GoiásGracinha Caiado União BrasilGustavo Gayer PL64%33%LeansVanderlan PP
Jorge Kajuru PRP
MaranhãoRoseana Sarney MDBFufuca PP44%36%Toss-upWeverton PDT
Eliziane Gama PPS
Minas GeraisMarília Campos PTCarlos Viana PSD47%37%Toss-upRodrigo Pacheco DEM
Jornalista Carlos Viana PHS
Mato Grosso do SulReinaldo Azambuja PLCapitão Contar PL82%18%LikelyNelsinho Trad PTB
Soraya Thronicke PSL
Mato GrossoMauro Mendes União BrasilJanaina Riva MDB62%31%LeansJayme Campos DEM
Fávaro PSD
ParáHelder MDBDelegado Éder Mauro PL57%29%Toss-upJader Barbalho MDB
Zequinha Marinho PSC
ParaíbaJoao Azevêdo PSBVeneziano MDB73%26%LeansVeneziano PSB
Daniella Ribeiro PP
PernambucoMarília Arraes PDTHumberto Costa PT66%34%LeansHumberto Costa PT
Jarbas MDB
PiauíMarcelo Castro MDBJúlio César o Julim do Lula PSD60%56%Toss-upCiro Nogueira PP
Marcelo Castro MDB
ParanáDeltan Dallagnol NovoFilipe Barros PL45%43%Toss-upProfessor Oriovisto Guimaraes Podemos
Flavio Arns REDE
Rio de JaneiroBenedita da Silva PTCarlos Jordy PL42%36%Toss-upFlávio Bolsonaro PSL
Arolde de Oliveira PSD
Rio Grande do NorteStyvenson Valentim PodemosZenaide Maia PSD68%17%LeansCapitão Styvenson REDE
Dr Zenaide Maia PHS
RondôniaDr Fernando Máximo PLBruno Scheid PL46%45%Toss-upMarcos Rogério DEM
Confucio Moura MDB
RoraimaTeresa Surita MDBNicoletti PL59%36%Toss-upChico Rodrigues DEM
Mecias de Jesus PRB
Rio Grande do SulMarcel van Hattem NovoManuela d'Ávila PSOL51%39%Toss-upLuis Carlos Heinze PP
Paulo Paim PT
Santa CatarinaCarol de Toni PLEsperidião Amin PP57%52%Toss-upEsperidião Amin PP
Jorginho Mello PR
SergipeDelegado André David RepublicanosRogerio Carvalho PT40%40%Toss-upDelegado Alessandro Vieira REDE
Rogerio Carvalho Santos PT
São PauloGuilherme Derrite PPMarina Silva REDE52%50%Toss-upMajor Olimpio PSL
Mara Gabrilli PSDB
TocantinsEduardo Gomes PLAlexandre Guimarães MDB46%37%Toss-upEduardo Gomes SOLIDARIEDADE
Irajá PSD

How it works

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.

Why it is sturdier than a single poll

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.

Past polling errors

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.

Governors and Senate

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.

Twenty thousand simulations

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.

No probability at 0 or 100%

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.

Sources

Election results and candidacies: Superior Electoral Court. 2026 polls: surveys published by pollsters and registered with the Superior Electoral Court.

See recent polls, with their registration number
  • Delta, AC-00288/2026, Acre, Senate, fieldwork ended 29/09, n = 800
  • Quaest, AC-08968/2026, Acre, Senate, fieldwork ended 24/09, n = 804
  • Real Time Big Data, AC-01699/2026, Acre, Senate, fieldwork ended 19/09, n = 1600
  • Paraná Pesquisas, AL-01237/2026, Alagoas, Senate, fieldwork ended 29/09, n = 1400
  • Ranking, AL-00905/2026, Alagoas, Senate, fieldwork ended 26/09, n = 1200
  • Índice, AL-00782/2026, Alagoas, Senate, fieldwork ended 26/09, n = 1200
  • Real Time Big Data, AP-08579/2026, Amapá, Senate, fieldwork ended 29/09, n = 1600
  • Paraná Pesquisas, AP-03035/2026, Amapá, Senate, fieldwork ended 27/09, n = 1000
  • Quaest, AP-02117/2026, Amapá, Senate, fieldwork ended 23/09, n = 804
  • Viva Voz, AM-08120/2026, Amazonas, Senate, fieldwork ended 27/09, n = 1500
  • IPEN/G6, AM-00196/2026, Amazonas, Senate, fieldwork ended 25/09, n = 1200
  • Veritá, AM-06152/2026, Amazonas, Senate, fieldwork ended 24/09, n = 1220
  • AtlasIntel, BA-02425/2026, Bahia, Senate, fieldwork ended 28/09, n = 2000
  • IFP, BA-00073/2026, Bahia, Senate, fieldwork ended 26/09, n = 2000
  • Real Time Big Data, BA-01777/2026, Bahia, Senate, fieldwork ended 26/09, n = 1600
  • Paraná Pesquisas, CE-03967/2026, Ceará, Senate, fieldwork ended 25/09, n = 1352
  • Datafolha, CE-00198/2026, Ceará, Senate, fieldwork ended 24/09, n = 1204
  • Real Time Big Data, CE-00688/2026, Ceará, Senate, fieldwork ended 24/09, n = 1600
  • Real Time Big Data, ES-01627/2026, Espírito Santo, Senate, fieldwork ended 29/09, n = 1600
  • Perfil/ES Hoje, ES-04513/2026, Espírito Santo, Senate, fieldwork ended 24/09, n = 1800
  • Quaest, ES-01978/2026, Espírito Santo, Senate, fieldwork ended 24/09, n = 804
  • Datafolha, DF-00905/2026, Federal District, Senate, fieldwork ended 01/10, n = 910
  • IGAPE, DF-09910/2026, Federal District, Senate, fieldwork ended 29/09, n = 2000
  • Quaest, DF-02515/2026, Federal District, Senate, fieldwork ended 28/09, n = 1104
  • Goiás Pesquisas/Mais Goiás, GO-09899/2026, Goiás, Senate, fieldwork ended 25/09, n = 1250
  • Veritá, GO-08703/2026, Goiás, Senate, fieldwork ended 24/09, n = 1525
  • Quaest, GO-01667/2026, Goiás, Senate, fieldwork ended 23/09, n = 804
  • Quaest, MA-07074/2026, Maranhão, Senate, fieldwork ended 24/09, n = 900
  • Ranking, MA-07878/2026, Maranhão, Senate, fieldwork ended 21/09, n = 1000
  • Viva Voz, MA-02471/2026, Maranhão, Senate, fieldwork ended 20/09, n = 1320
  • Paraná Pesquisas, MT-02094/2026, Mato Grosso, Senate, fieldwork ended 29/09, n = 1352
  • Quaest, MT-08098/2026, Mato Grosso, Senate, fieldwork ended 24/09, n = 804
  • Paraná Pesquisas, MT-09335/2026, Mato Grosso, Senate, fieldwork ended 17/09, n = 1352
  • Instituto Ranking Brasil, MS-09269/2026, Mato Grosso do Sul, Senate, fieldwork ended 30/09, n = 2000
  • Novo Ibrape, MS-01465/2026, Mato Grosso do Sul, Senate, fieldwork ended 28/09, n = 1000
  • Instituto Ranking Brasil, MS-09415/2026, Mato Grosso do Sul, Senate, fieldwork ended 25/09, n = 2000
  • DataFolha, MG-09729/2026, Minas Gerais, Senate, fieldwork ended 01/10, n = 1204
  • Quaest, MG-02019/2026, Minas Gerais, Senate, fieldwork ended 28/09, n = 1506
  • Real Time Big Data, MG-03351/2026, Minas Gerais, Senate, fieldwork ended 26/09, n = 2000
  • Neokemp, PR-05345/2026, PR-05600/2026, Paraná, Senate, fieldwork ended 01/10, n = 1008
  • Real Time Big Data, PR-04181/2026, Paraná, Senate, fieldwork ended 28/09, n = 1600
  • Ágili, PR-03158/2026, Paraná, Senate, fieldwork ended 28/09, n = 1200
  • TDL, PB-01280/2026, Paraíba, Senate, fieldwork ended 27/09, n = 2000
  • Anova, PB-06564/2026, Paraíba, Senate, fieldwork ended 22/09, n = 2000
  • Quaest, PB-01325/2026, Paraíba, Senate, fieldwork ended 21/09, n = 804
  • Doxa, PA-05494/2026, PA-08418/2026, Pará, Senate, fieldwork ended 28/09, n = 2000
  • Real Time Big Data, PA-09993/2026, Pará, Senate, fieldwork ended 26/09, n = 1600
  • Quaest, PA-07402/2026, Pará, Senate, fieldwork ended 25/09, n = 804
  • DataFolha, PE-06822/2026, Pernambuco, Senate, fieldwork ended 01/10, n = 1204
  • Quaest, PE-00324/2026, Pernambuco, Senate, fieldwork ended 28/09, n = 1302
  • Folha/IPESPE, PE-04196/2026, Pernambuco, Senate, fieldwork ended 26/09, n = 1000
  • Datamax, PI-07373/2026, Piauí, Senate, fieldwork ended 19/09, n = 1200
  • Datafolha, PI-03643/2026, Piauí, Senate, fieldwork ended 16/09, n = 826
  • IPPI, PI-07031/2026, Piauí, Senate, fieldwork ended 10/09, n = 1200
  • Seta, RN-06302/2026, Rio Grande do Norte, Senate, fieldwork ended 24/09, n = 1500
  • Quaest, RN-01492/2026, Rio Grande do Norte, Senate, fieldwork ended 24/09, n = 804
  • Exatus/Agora RN, RN-00755/2026, Rio Grande do Norte, Senate, fieldwork ended 23/09, n = 1500
  • Real Time Big Data, RS-05412/2026, Rio Grande do Sul, Senate, fieldwork ended 28/09, n = 1600
  • Neokemp, RS-08358/2026, Rio Grande do Sul, Senate, fieldwork ended 24/09, n = 1008
  • Quaest, RS-01390/2026, Rio Grande do Sul, Senate, fieldwork ended 23/09, n = 900
  • DataFolha, RJ-02070/2026, Rio de Janeiro, Senate, fieldwork ended 01/10, n = 1204
  • Real Time Big Data, RJ-08712/2026, Rio de Janeiro, Senate, fieldwork ended 29/09, n = 2000
  • Quaest, RJ-04419/2026, Rio de Janeiro, Senate, fieldwork ended 28/09, n = 1302
  • Real Time Big Data, RO-03623/2026, Rondônia, Senate, fieldwork ended 29/09, n = 1600
  • Veritá, RO-08063/2026, Rondônia, Senate, fieldwork ended 25/09, n = 1220
  • Quaest, RO-08556/2026, Rondônia, Senate, fieldwork ended 23/09, n = 804
  • Quaest, RR-03658/2026, Roraima, Senate, fieldwork ended 24/09, n = 804
  • Census, RR-07346/2026, Roraima, Senate, fieldwork ended 13/09, n = 1500
  • Real Time Big Data, RR-03170/2026, Roraima, Senate, fieldwork ended 09/09, n = 1600
  • Neokemp, SC-05312/2026, Santa Catarina, Senate, fieldwork ended 30/09, n = 1008
  • Rumo, SC-04705/2026, Santa Catarina, Senate, fieldwork ended 26/09, n = 2100
  • Quaest, SC-04783/2026, Santa Catarina, Senate, fieldwork ended 23/09, n = 804
  • IFP, SE-01807/2026, Sergipe, Senate, fieldwork ended 26/09, n = 1300
  • Quaest, SE-09343/2026, Sergipe, Senate, fieldwork ended 23/09, n = 804
  • Real Time Big Data, SE-02030/2026, Sergipe, Senate, fieldwork ended 21/09, n = 1600
  • DataFolha, SP-01367/2026, São Paulo, Senate, fieldwork ended 30/09, n = 1610
  • Gerp, SP-04091/2026, São Paulo, Senate, fieldwork ended 30/09, n = 1500
  • Vox, SP-01943/2026, São Paulo, Senate, fieldwork ended 29/09, n = 1480
  • Veritá, TO-07961/2026, Tocantins, Senate, fieldwork ended 25/09, n = 1220
  • Real Time Big Data, TO-04340/2026, Tocantins, Senate, fieldwork ended 24/09, n = 1600
  • Correio do Povo, TO-05725/2026, Tocantins, Senate, fieldwork ended 24/09, n = 1600

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Credits

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