AFOS-Analytics1/brazil-2026-electoral-divergence

AFOS — Brazil 2026 Electoral Divergence Dataset

🌐 English · Português · Español

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English

Open, auditable daily dataset that cross-references prediction markets (Polymarket) × polling institutes (TSE-registered) × press coverage for Brazil's 2026 presidential cycle, with explicit divergence between sources instead of smoothed averages.

Maintained by AFOS Analytics — open-source civic infrastructure for electoral political-risk intelligence. This is the public mirror of the same data the platform serves live, updated daily. Files are dated and append-only: each day adds new files, past dates are never overwritten, and every update is a git commit — so the full history is preserved natively.

🔒 No personal data (privacy / LGPD): contains only public electoral data (market odds, registered polls, news links). No subscriber data, no emails, no leads, no personal information of any kind. The export pipeline is database-free by construction and never accesses any user table. Brazil's LGPD and equivalent principles are respected in full.

License (dual): Data → CC BY 4.0 (LICENSE-CC-BY-4.0); code/scripts → Apache 2.0 (LICENSE-APACHE-2.0). Both require attribution to AFOS Analytics.

Cite: AFOS Analytics. Brazil 2026 Electoral Divergence Dataset. Hugging Face, 2026. CC BY 4.0.

Permanent archive: also deposited at the Harvard Dataverse — DOI 10.7910/DVN/2D0UK7.

Disclaimer: observational research. Not investment advice, not voting guidance. AFOS observes the markets — it does not trade them.

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Português

Dataset diário aberto e auditável que cruza mercados de previsão (Polymarket) × institutos de pesquisa (registrados no TSE) × cobertura de imprensa para o ciclo presidencial brasileiro de 2026, com divergência explícita entre as fontes em vez de médias suavizadas.

Mantido pela AFOS Analytics — infraestrutura cívica open-source de inteligência de risco político eleitoral. É o espelho público dos mesmos dados que a plataforma serve ao vivo, atualizado diariamente. Os arquivos são datados e append-only: cada dia adiciona novos arquivos, datas passadas nunca são sobrescritas, e cada atualização é um commit git — o histórico completo fica preservado nativamente.

🔒 Sem dados pessoais (privacidade / LGPD): contém apenas dados eleitorais públicos (odds de mercado, pesquisas registradas, links de notícia). Nenhum dado de assinante, nenhum email, nenhum lead, nenhuma informação pessoal. O pipeline de export é database-free por construção e nunca acessa qualquer tabela de usuário. A LGPD e princípios equivalentes são respeitados integralmente.

Licença (dual): Dados → CC BY 4.0 (LICENSE-CC-BY-4.0); código/scripts → Apache 2.0 (LICENSE-APACHE-2.0). Ambas exigem atribuição à AFOS Analytics.

Citação: AFOS Analytics. Brazil 2026 Electoral Divergence Dataset. Hugging Face, 2026. CC BY 4.0.

Arquivo permanente: também depositado no Harvard Dataverse — DOI 10.7910/DVN/2D0UK7.

Aviso: pesquisa observacional. Não é recomendação de investimento nem orientação de voto. A AFOS observa os mercados — não opera neles.

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Español

Dataset diario abierto y auditable que cruza mercados de predicción (Polymarket) × encuestadoras (registradas en el TSE) × cobertura de prensa para el ciclo presidencial brasileño de 2026, con divergencia explícita entre las fuentes en lugar de promedios suavizados.

Mantenido por AFOS Analytics — infraestructura cívica open-source de inteligencia de riesgo político electoral. Es el espejo público de los mismos datos que la plataforma sirve en vivo, actualizado diariamente. Los archivos son fechados y append-only: cada día agrega archivos nuevos, las fechas pasadas nunca se sobrescriben, y cada actualización es un commit git — el historial completo se preserva de forma nativa.

🔒 Sin datos personales (privacidad / LGPD): contiene solo datos electorales públicos (odds de mercado, encuestas registradas, enlaces de noticias). Ningún dato de suscriptor, ningún email, ningún lead, ninguna información personal. El pipeline de exportación es database-free por construcción y nunca accede a ninguna tabla de usuarios. La LGPD y principios equivalentes se respetan íntegramente.

Licencia (dual): Datos → CC BY 4.0 (LICENSE-CC-BY-4.0); código/scripts → Apache 2.0 (LICENSE-APACHE-2.0). Ambas requieren atribución a AFOS Analytics.

Citar: AFOS Analytics. Brazil 2026 Electoral Divergence Dataset. Hugging Face, 2026. CC BY 4.0.

Archivo permanente: también depositado en el Harvard Dataverse — DOI 10.7910/DVN/2D0UK7.

Aviso: investigación observacional. No es asesoría de inversión ni orientación de voto. AFOS observa los mercados — no opera en ellos.

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📁 Structure · Estrutura · Estructura

Full column-level definitions for every file are in DATA_DICTIONARY.md. Citation metadata in CITATION.cff; version history in CHANGELOG.md.

🗳️ Electoral polls (priority) · Pesquisas eleitorais · Encuestas

Path	Rows	Content
polls/tse-registry.csv · .json	913	Official TSE poll registry — full public fields, built directly from the TSE Open Data file. Every presidential poll filed for 2026 with its complete registration sheet: institute, CNPJ, sample, field dates, declared cost, named responsible statistician + CONRE, and the full (un-truncated) methodology and sampling/weighting design — including the demographic/geographic quota design (sex, age, education, income, region) with the declared quota percentages. Registration-design fields only — no per-candidate results, and the complete questionnaire is a PesqEle attachment, not in the open-data file. (Lei 9.504/97 art. 33)
polls/national-poll-results-firstround.csv	578	Published first-round results, long format: one row per candidate × scenario × poll. Carries the TSE registration number, institute, sample, margin, field dates.
polls/national-poll-results-secondround.csv	189	Published head-to-head runoff matchups (candidate1 vs candidate2, percentages).
polls/national-polls.json	83	Full structured national polls with results (first round + runoff + methodology), reconstructed from the platform history. Each poll carries a tse_registration block (full methodology, sampling/weighting design, statistician, CONRE, CNPJ, cost) and, since 2026-06-13, fieldwork-midpoint dating (field_midpoint, days_to_first_round/runoff) plus tse_registration.sample_design (parsed sample composition/weighting — layer A).
polls/sample-demographics.csv	416	Sample-design demographics (layer A), long format: each poll's declared sex/age/education/income quota composition parsed from the TSE sampling plan, with explicit per-poll coverage (full_percentages 34/83 · mentioned_no_pct 49/83). This is sample composition/weighting — not vote-by-demographic crosstabs (layer B), which are not part of TSE open data.
polls/polls-data-{date}.json	—	Daily snapshot of the national polls referenced on that date.

🗳️ Official result · Resultado oficial · Resultado oficial

Path	Rows	Content
results/first-round-2026-official.json	1	Final TSE tally of the first round (100% of sections, generated 2026-10-05 12:51): electorate, turnout, abstention, valid, blank and null votes, all twelve candidates with votes and party, and the voting machines of the day (in use, backup, replaced, sections voting on paper), each with its TSE source.
results/first-round-2026-candidates.csv	12	One row per candidate, with votes, percentage of valid votes, party, coalition and TSE status.
results/first-round-2026-summary.csv	14	One row per figure, with the denominator of each percentage declared.
results/first-round-2026-retrospective.csv	18	What each instrument said on the eve: the nine national polls of 2026-10-03 and four Polymarket books, item by item, against the outcome.
results/first-round-2026-retrospective-summary.csv	5	The same comparison one row per instrument, as the panel card shows it: matched or not, and for the polls whether the majority of houses had the winner ahead and whether their range contained the count.

The second round will be added in the same format after 2026-10-25. Details in results/README.md.

📈 Market & divergence time-series

Path	Content
data/market-odds-timeseries.csv	Polymarket presidential odds per candidate, daily (date, candidate, party, polymarket_pct, volume_usd_m) — full history from 2026-04-04.
data/divergence-timeseries.csv	Market × poll divergence per candidate (poll_date, institute, register_tse, candidate, poll_pct, polymarket_pct, polymarket_date, divergence_pp) — each national poll joined to the market odds on its date. The dataset's namesake signal.
data/poll-divergence.csv	Poll-level market × poll pairing anchored on each poll's fieldwork midpoint; naive_gap_pp is explicitly flagged naive_winprob_minus_voteshare — the market prices P(win) while the poll reports vote share, so the gap is not scale-reconciled (reconciling the scales is a modeling choice left to the researcher).
data/divergence-{date}.csv	Per-day market × poll divergence snapshot, first round (ends 2026-10-04).
data/divergence-second-round-{date}.csv	Per-day snapshot for the second round (from 2026-10-05): the two runoff candidates only, with the poll side taken from the Lula × Flávio Bolsonaro head-to-head. See DATA_DICTIONARY.md.

📰 Daily analysis & news

Path	Content
snapshots/analysis-criteriosa/{date}.json	Daily analysis: market × poll × press, per candidate (incl. quadroComparativo).
snapshots/analysis-cards/{date}.json	Thematic cards (sentiment, institutional, macro).
news/news-{date}.json	Public news links (source, title, URL, date) — no article bodies.

🎓 For researchers

• Start with DATA_DICTIONARY.md (every column, type, unit, provenance) and polls/ (the registered-poll universe + published results).
• Reproducibility: every value traces to a public primary source — the TSE registry, a named pollster's release, or a live Polymarket contract. Nothing is imputed or smoothed; where a number is missing it is left blank, not filled.
• Editorial stance: AFOS reports divergence between sources rather than a single blended average — the spread is treated as signal, not noise.
• Demographics: sample-design demographics — the declared composition/weighting of each poll's sample (layer A) — are included (polls/sample-demographics.csv). Vote-by-demographic crosstabs (layer B — e.g. vote share by sex/age/income) are not part of Brazil's TSE open data; institutes publish those separately, so they are intentionally absent here rather than partially scraped.
• Scale caveat (market vs poll): Polymarket prices probability of winning; polls report vote share. The two divergence files keep both raw values side by side and flag the naive gap accordingly — they are not a like-for-like error metric.
• Updates: dated and append-only; each daily commit preserves the full history natively (see CHANGELOG.md). The file for the current date may be regenerated during the day; files for dates already closed are never modified.
• Known errors: see ERRATA.md. When a defect is found in a past date, the file is not rewritten — the correction is published in the errata instead, so the record stays as distributed and the defect stays discoverable. Erros conhecidos em ERRATA.md. · Errores conocidos en ERRATA.md.

Sources / Fontes / Fuentes: Polymarket (live USD markets) · TSE-registered institutes · 400+ press outlets. Method & source code (Apache 2.0): github.com/AFOS-Analytics.