AFOS-Analytics1/peru-2026-electoral-divergence

AFOS · Peru 2026 Electoral Divergence Dataset

🌐 English · Español · Português

Open dataset cross-referencing opinion polls × prediction markets for Peru's 2026 general election (first round 12 April 2026; runoff 7 June 2026, Keiko Fujimori vs Roberto Sánchez), built in the same spirit as the AFOS Brazil 2026 dataset: sources are reported side by side with explicit divergence, not blended into a single average.

Maintained by AFOS Analytics. This is part of AFOS's expansion of its electoral-divergence method beyond Brazil. No personal data, only public electoral information.

Outcome (validated). The runoff was one of the closest in Peruvian history. Final publishable polls showed a statistical tie (Ipsos valid-vote simulacro about 51.4 / 48.6) while the market gave Fujimori about 68% to win. After Roberto Sánchez contested the count (seeking to void the overseas vote and petitioning the Inter-American Commission on Human Rights), the JNE rejected the appeals and on 3 July 2026 proclaimed Keiko Fujimori president-elect with 50.135% to Sánchez's 49.865% (about 49,000 votes); inauguration 28 July. Two opposite divergences in one election: in the first round the market misread the frontrunner (López Aliaga, favorite → 3rd); in the runoff it was right on direction but overstated the margin, while the polls' tie matched the result.

Resultado (validado). El balotaje fue uno de los más ajustados de la historia peruana. Las encuestas finales publicables mostraban un empate técnico (simulacro de votos válidos de Ipsos cerca de 51,4 / 48,6), mientras el mercado daba a Fujimori cerca de 68% de ganar. Tras la impugnación del conteo por Roberto Sánchez (pidiendo anular el voto en el exterior y recurriendo a la CIDH), el JNE rechazó los recursos y, el 3 de julio de 2026, proclamó a Keiko Fujimori presidenta electa con 50,135% frente al 49,865% de Sánchez (cerca de 49 mil votos); investidura el 28 de julio. Dos divergencias opuestas en una elección: en la primera vuelta el mercado erró al favorito (López Aliaga, favorito → 3º); en el balotaje acertó la dirección pero sobreestimó el margen, mientras el empate de las encuestas coincidió con el resultado.

Desfecho (validado). O 2º turno foi um dos mais apertados da história peruana. As pesquisas finais publicáveis davam empate técnico (simulacro de votos válidos da Ipsos cerca de 51,4 / 48,6), enquanto o mercado dava Fujimori a cerca de 68% de chance de vencer. Depois de Roberto Sánchez contestar a apuração (pedindo a nulidade do voto no exterior e recorrendo à CIDH), a JNE rejeitou os recursos e, em 3 de julho de 2026, proclamou Keiko Fujimori presidente eleita com 50,135% contra 49,865% de Sánchez (cerca de 49 mil votos); posse em 28 de julho. Duas divergências opostas na mesma eleição: no 1º turno o mercado errou o favorito (López Aliaga, favorito → 3º); no 2º turno acertou a direção mas superestimou a margem, enquanto o empate das pesquisas bateu com o resultado.

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Press coverage layer

The qualitative third axis of the AFOS cross (market x polls x press) is now a structured file: news/peru-2026-press-coverage.csv, 8 dated headlines from 6 national outlets across the cycle (polls, election, result, analysis), in ES. Headlines and links only (outlets retain copyright); dates are publication/coverage dates, best-effort. It complements the quantitative market-vs-poll divergence; it is not sentiment-scored.

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English

Contents (start with the polls):

Path	Rows	Content
polls/peru-first-round-polls.csv	327	First-round voting intention, long format (one row per candidate × poll), all 14 candidates, 36 polls, Jan→Apr 2026.
polls/peru-runoff-polls.csv	16	Runoff head-to-head (Fujimori vs Sánchez), Apr→Jun 2026.
polls/peru-polls.json	n/a	Full structured polls (first round + runoff) with methodology.
data/peru-market-odds-timeseries.csv	2,490	Daily Polymarket win-probability per candidate (16 candidates, Dec 2025→Jun 2026) from the "Peru Presidential Election Winner" market.
data/peru-divergence-timeseries.csv	324	Market × poll divergence per candidate, each first-round poll joined to the candidate's market odds on its date.
data/peru-poly-raw.json	n/a	Raw Polymarket payload (event + per-candidate price histories), kept for provenance.

_{Market data fetched from Polymarket's gamma-api + clob (US-resolving function). Divergence covers the first round; no clean head-to-head runoff win-probability market exists to join the runoff polls.}

⚖️ Notable divergences (why divergence beats the average)

The point of this dataset is the gap between what the market prices (probability of winning) and what polls measure (first-round vote share), read across the full daily series, not a single snapshot.

• Rafael López Aliaga, the market's sustained favorite that the polls never matched. For months the market priced his win probability at 40-55% while his first-round vote-share polling stayed in the low-to-mid teens (7-17%). He placed third and missed the runoff, the market's conviction ran well ahead of his actual support. A real, sustained divergence.
• Keiko Fujimori, polls about 16% × market about 22%: steadier in both; she led the first round and advanced. The 7 June runoff against Roberto Sánchez ended in a virtual tie and, after Sánchez's challenges, the JNE proclaimed Keiko Fujimori president-elect on 3 July 2026 (50.135% × 49.865%, about 49,000 votes).
• Ricardo Belmont, poll 9% × market 5.1%: the market priced him below his vote share, never a contender in its eyes.
• A caution on noise: outsider Carlos Álvarez briefly spiked to 31.6% in the market on a single day (5 Apr) against about 8% in polls, then fell to low single digits within days. Thin-market prints can diverge sharply without being a sustained signal, which is exactly why the full daily series matters, not one snapshot.

The reading: the spread is the signal, but reading it means telling the sustained gap (López Aliaga) from transient noise (Álvarez). A blended average hides both.

Pollsters covered: Ipsos Perú, Datum Internacional, CPI, IEP, CIT, Imasolu, CELAG, IDICE, CB Global Data (with publishing client where applicable).

Provenance & method: poll figures are compiled deterministically (rowspan/colspan-aware HTML parser) from the public Wikipedia aggregation "Opinion polling for the 2026 Peruvian general election" and cross-checked against the AS/COA poll tracker; every figure traces to a named pollster's release. Market odds come from the public Polymarket markets. Nothing is imputed or smoothed; missing values are left blank.

License (dual): data → CC BY 4.0 (LICENSE-CC-BY-4.0); code/scripts → Apache 2.0 (LICENSE-APACHE-2.0), matching the repo root and the Hugging Face mirror. Underlying poll numbers are facts released by the named pollsters; the Wikipedia aggregation is CC BY-SA. Please attribute AFOS Analytics and the original pollsters.

Cite: AFOS Analytics. Peru 2026 Electoral Divergence Dataset. Hugging Face, 2026. CC BY 4.0. (see CITATION.cff)

Disclaimer: observational research. Not investment advice, not voting guidance.

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Español

Dataset abierto que cruza encuestas × mercados de predicción para la elección general del Perú 2026 (primera vuelta 12 abr 2026; segunda vuelta 7 jun 2026, Keiko Fujimori vs Roberto Sánchez), con divergencia explícita entre fuentes en lugar de un promedio único.

• polls/peru-first-round-polls.csv, intención de voto en primera vuelta, formato largo, los 14 candidatos, 36 encuestas (ene→abr 2026).
• polls/peru-runoff-polls.csv, segunda vuelta cara a cara (Fujimori vs Sánchez), 16 encuestas.
• data/peru-market-odds-timeseries.csv / data/peru-divergence-timeseries.csv, probabilidad de Polymarket por candidato y divergencia mercado × encuesta.

⚖️ Divergencias destacadas (por qué la divergencia supera al promedio)

Lo importante es la brecha entre lo que valora el mercado (probabilidad de ganar) y lo que miden las encuestas (voto de primera vuelta), leída en toda la serie diaria, no en una foto.

• Rafael López Aliaga, el favorito sostenido del mercado que las encuestas nunca confirmaron. Durante meses el mercado valoró su probabilidad de ganar en 40-55% mientras su voto de primera vuelta se quedaba en la franja baja-media de la decena (7-17%). Quedó tercero y no llegó al balotaje, la convicción del mercado iba muy por delante de su apoyo real. Una divergencia real y sostenida.
• Keiko Fujimori, encuestas cerca de 16% × mercado cerca de 22%: más estable en ambos; lideró la primera vuelta y avanzó. El balotaje del 7 jun frente a Roberto Sánchez terminó en empate técnico y, tras las impugnaciones de Sánchez, el JNE proclamó a Keiko Fujimori presidenta electa el 3 jul 2026 (50,135% × 49,865%, cerca de 49 mil votos).
• Ricardo Belmont, encuesta 9% × mercado 5,1%: el mercado lo valoró por debajo de su voto.
• Una advertencia sobre el ruido: el outsider Carlos Álvarez subió brevemente a 31,6% en el mercado en un solo día (5 abr) frente a cerca de 8% en encuestas, y cayó a un dígito en pocos días. Los precios de mercados poco líquidos pueden divergir con fuerza sin ser una señal sostenida, por eso importa la serie diaria completa.

La lectura: la brecha es la señal, pero leerla implica distinguir la divergencia sostenida (López Aliaga) del ruido transitorio (Álvarez). Un promedio oculta ambas.

Encuestadoras: Ipsos Perú, Datum Internacional, CPI, IEP, CIT, Imasolu, CELAG, IDICE, CB Global Data. Fuente: agregación pública de Wikipedia + tracker AS/COA; cada cifra remite a la publicación de una encuestadora con nombre. Licencia: CC BY 4.0 (atribuir a AFOS Analytics y a las encuestadoras originales). Investigación observacional; no es asesoría de inversión ni orientación de voto.

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Português

Dataset aberto cruzando pesquisas × mercados de previsão para a eleição geral do Peru 2026 (1º turno 12/abr; 2º turno 07/jun, Keiko Fujimori × Roberto Sánchez), com divergência explícita entre fontes. Pesquisas (14 candidatos, 36 do 1º turno + 16 do 2º turno) compiladas deterministicamente da agregação pública da Wikipedia + tracker AS/COA; odds do Polymarket. Licença CC BY 4.0 (atribuir AFOS Analytics + institutos originais). Pesquisa observacional; não é recomendação de investimento nem orientação de voto.

⚖️ Divergências em destaque (por que a divergência supera a média)

O ponto é a diferença entre o que o mercado precifica (probabilidade de vencer) e o que as pesquisas medem (voto de 1º turno), lida na série diária inteira, não numa foto.

• Rafael López Aliaga, o favorito sustentado do mercado que as pesquisas nunca confirmaram. Por meses o mercado precificou a chance de vencer dele em 40-55% enquanto o voto de 1º turno ficava na casa baixa-média da dezena (7-17%). Ficou em 3º e não foi ao 2º turno, a convicção do mercado ia bem à frente do apoio real. Divergência real e sustentada.
• Keiko Fujimori, pesquisas cerca de 16% × mercado cerca de 22%: mais estável nos dois; liderou o 1º turno e avançou. O 2º turno de 07/jun contra Roberto Sánchez terminou em empate técnico e, após as contestações de Sánchez, a JNE proclamou Keiko Fujimori presidente eleita em 03/jul 2026 (50,135% × 49,865%, cerca de 49 mil votos).
• Ricardo Belmont, pesquisa 9% × mercado 5,1%: o mercado o precificou abaixo do voto.
• Um alerta sobre ruído: o azarão Carlos Álvarez deu um spike breve de 31,6% no mercado num único dia (5/abr) contra cerca de 8% nas pesquisas, e caiu pra um dígito em poucos dias. Preços de mercados pouco líquidos podem divergir forte sem ser sinal sustentado, por isso a série diária completa importa.

A leitura: a diferença é o sinal, mas lê-la é distinguir a divergência sustentada (López Aliaga) do ruído passageiro (Álvarez). A média esconde as duas.

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Sources / Fuentes: Pollsters (Ipsos Perú, Datum, CPI, IEP, CIT, …) · Wikipedia aggregation · AS/COA poll tracker · Polymarket. Column definitions in DATA_DICTIONARY.md.

Structural context (World Bank)

Beyond the divergence data, this dataset ships data/peru-structural-context.csv: official, open World Bank indicators that frame the country, governance (Worldwide Governance Indicators, 0-100 scale) plus economy & education (World Development Indicators: population, GDP, GDP per capita, inflation, public education spending, expected years of schooling). These are annual structural indicators that contextualize the country; they do not predict the electoral outcome. Columns are documented in DATA_DICTIONARY.md.