Datasets:

AFOS-Analytics1
/

germany-2025-electoral-divergence

@@ -1,105 +1,110 @@
----
-license:
-- cc-by-4.0
-- apache-2.0
-language:
-- en
-- de
-- pt
-- es
-pretty_name: "AFOS · Germany 2025 Electoral Divergence"
-tags:
-- elections
-- germany
-- prediction-markets
-- polls
-- political-risk
-- divergence
-- open-data
-- europe
----
-![AFOS · Germany 2025 Electoral Divergence](banner.png)
-# AFOS · Germany 2025 Electoral Divergence Dataset
-🌐 **[English](#english) · [Português](#português) · [Español](#español)**
-Open dataset cross-referencing **opinion polls × prediction markets** for Germany's **2025 federal election** (Bundestag, 23 February 2025 — a snap election after the November 2024 coalition collapse), in the same spirit as the AFOS Brazil 2026 dataset: sources reported side by side with **explicit divergence**, not blended into one average.
-Maintained by **[AFOS Analytics](https://afos-analytics.com)**. *No personal data — only public electoral information.* **Party-level** dataset: polls measure **party vote share**, the market prices the **probability of winning the most seats** — two different quantities, and the gap is the signal.
----
-## English
-![Polymarket implied probability of winning over the campaign](odds-trajectory.png)
-![Market probability of winning versus poll vote share on the eve of the vote](odds-snapshot.png)
-**Contents (start with the polls):**
-| Path | Rows | Content |
-|------|------|---------|
-| `polls/germany-polls.csv` | 2,505 | Party vote-share polling, **long format** (one row per party × poll), 8 parties, 349 polls, 2024→Feb 2025. |
-| `polls/germany-polls.json` | — | Full structured polls (pollster, fieldwork, sample, per-party results). |
-| `data/germany-market-odds-timeseries.csv` | 420 | Daily Polymarket **"wins the most seats"** probability per party (6 parties, Dec 2024→Feb 2025) from the "Germany Parliamentary Election Winner" market. |
-| `data/germany-divergence-timeseries.csv` | 490 | **Market × poll divergence** per party — each poll's party vote share joined to that party's market odds on its date. |
-| `data/germany-poly-raw.json` | — | Raw Polymarket payload, kept for provenance. |
-<sub>Market data fetched from Polymarket's gamma-api + clob via a US-resolving function. There is no runoff — Germany elects the Bundestag in a single vote.</sub>
-### ⚖️ Notable divergences (why divergence beats the average)
-The market here prices **which party wins the most seats**; the polls measure **party vote share**. In a multi-party system the two come apart sharply — and that gap is the point.
-- **AfD — second in votes, near-zero to win.** In the final polls the AfD held **~21% of the vote**, clearly the **second-largest party** — yet the market gave it only **~3%** of winning the most seats (a −18 pp market−poll gap). High vote share is not the same as a parliamentary plurality, and the market never confused the two. The AfD finished second (20.8%); it did not win the most seats.
-- **CDU/CSU — the mirror image.** ~**29.5%** of the vote but **~97%** to win the most seats (+67 pp): a moderate vote lead translated into near-certain plurality. The CDU/CSU won (28.5%) and Friedrich Merz became Chancellor.
-- **The small-party threshold (5%):** BSW and FDP hovered right at the **5% Bundestag threshold** in vote-share polls while the market priced their probability of *winning* at ~0% — two parties for whom "share" and "win" were never the same question. Both ultimately fell below 5%.
-**The reading:** vote share answers "how many votes," the market answers "who wins" — and in a fragmented parliament those diverge by design. A blended poll average tells you the AfD was second; only the market-versus-poll spread tells you it was second *and* had no path to the plurality.
-**Pollsters covered:** Forsa, INSA, Infratest dimap, Allensbach, YouGov, Ipsos, FGW (Forschungsgruppe Wahlen), GMS, Verian, and others.
-**Provenance & method:** poll figures compiled deterministically (rowspan/colspan-aware HTML parser) from the public Wikipedia aggregation *"Opinion polling for the 2025 German federal election."* Market odds from the public Polymarket market. Nothing imputed or smoothed; missing values 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. Germany 2025 Electoral Divergence Dataset. Hugging Face, 2026. CC BY 4.0.* (see `CITATION.cff`)
-**Disclaimer:** observational research. Not investment advice, not voting guidance.
----
-## Português
-Dataset aberto cruzando **pesquisas × mercados de previsão** para a **eleição federal alemã de 2025** (Bundestag, 23/fev/2025 — eleição antecipada após o colapso da coalizão em nov/2024). **Nível partido:** as pesquisas medem **voto por partido**; o mercado precifica a **probabilidade de vencer mais cadeiras** — quantidades diferentes, e a diferença é o sinal.
-- `polls/germany-polls.csv` — voto por partido, formato largo, 8 partidos, 349 pesquisas (2024→fev 2025).
-- `data/germany-market-odds-timeseries.csv` / `germany-divergence-timeseries.csv` — probabilidade Polymarket de "vencer mais cadeiras" por partido e divergência mercado × pesquisa.
-### ⚖️ Divergências em destaque (por que a divergência supera a média)
-- **AfD — 2º mais votado, quase zero para vencer.** Nas pesquisas finais a AfD tinha ~**21% do voto** (claramente o 2º maior partido) — mas o mercado lhe dava só **~3%** de vencer mais cadeiras (diferença −18pp). Voto alto não é maioria parlamentar, e o mercado nunca confundiu os dois. A AfD ficou em 2º (20,8%); não venceu.
-- **CDU/CSU — a imagem espelhada.** ~**29,5%** de voto mas **~97%** de vencer mais cadeiras (+67pp): liderança moderada de voto vira maioria quase certa. A CDU/CSU venceu (28,5%) e Friedrich Merz virou chanceler.
-- **O limiar de 5%:** BSW e FDP rondavam os **5% da cláusula de barreira** no voto enquanto o mercado precificava a chance de *vencer* em ~0% — dois partidos para quem "voto" e "vencer" nunca foram a mesma pergunta. Ambos ficaram abaixo de 5%.
-**A leitura:** voto responde "quantos votos", o mercado responde "quem vence" — e num parlamento fragmentado isso diverge por construção. Uma média das pesquisas diz que a AfD era 2ª; só a diferença mercado×pesquisa mostra que era 2ª *e* sem caminho para a maioria.
----
-## Español
-Dataset abierto que cruza **encuestas × mercados de predicción** para la **elección federal alemana de 2025** (Bundestag, 23 feb 2025). **Nivel partido:** las encuestas miden **voto por partido**; el mercado valora la **probabilidad de ganar más escaños**.
-### ⚖️ Divergencias destacadas
-- **AfD — segundo en votos, casi nulo para ganar.** ~**21% del voto** (2º partido) pero el mercado le daba solo **~3%** de ganar más escaños (−18pp). Voto alto no es mayoría parlamentaria. La AfD quedó 2ª (20,8%); no ganó.
-- **CDU/CSU — la imagen espejo.** ~**29,5%** de voto pero **~97%** de ganar más escaños (+67pp). Ganó (28,5%) y Merz fue canciller.
-- **El umbral del 5%:** BSW y FDP rondaban el 5% en voto mientras el mercado valoraba su probabilidad de *ganar* en ~0%. Ambos quedaron bajo el 5%.
-**Fuente:** agregación pública de Wikipedia; Polymarket. **Licencia:** CC BY 4.0 (atribuir a AFOS Analytics y a las encuestadoras). Investigación observacional; no es asesoría de inversión.
----
-**Sources / Fontes / Fuentes:** Pollsters (Forsa, INSA, Infratest dimap, Allensbach, …) · [Wikipedia aggregation](https://en.wikipedia.org/wiki/Opinion_polling_for_the_2025_German_federal_election) · Polymarket. Column definitions in [`DATA_DICTIONARY.md`](DATA_DICTIONARY.md).

+---
+license:
+- cc-by-4.0
+- apache-2.0
+language:
+- en
+- de
+- pt
+- es
+pretty_name: "AFOS · Germany 2025 Electoral Divergence"
+tags:
+- elections
+- germany
+- prediction-markets
+- polls
+- political-risk
+- divergence
+- open-data
+- europe
+---
+![AFOS · Germany 2025 Electoral Divergence](banner.png)
+# AFOS · Germany 2025 Electoral Divergence Dataset
+🌐 **[English](#english) · [Português](#português) · [Español](#español)**
+Open dataset cross-referencing **opinion polls × prediction markets** for Germany's **2025 federal election** (Bundestag, 23 February 2025 — a snap election after the November 2024 coalition collapse), in the same spirit as the AFOS Brazil 2026 dataset: sources reported side by side with **explicit divergence**, not blended into one average.
+Maintained by **[AFOS Analytics](https://afos-analytics.com)**. *No personal data — only public electoral information.* **Party-level** dataset: polls measure **party vote share**, the market prices the **probability of winning the most seats** — two different quantities, and the gap is the signal.
+---
+## English
+![Polymarket implied probability of winning over the campaign](odds-trajectory.png)
+![Market probability of winning versus poll vote share on the eve of the vote](odds-snapshot.png)
+**Contents (start with the polls):**
+| Path | Rows | Content |
+|------|------|---------|
+| `polls/germany-polls.csv` | 2,505 | Party vote-share polling, **long format** (one row per party × poll), 8 parties, 349 polls, 2024→Feb 2025. |
+| `polls/germany-polls.json` | — | Full structured polls (pollster, fieldwork, sample, per-party results). |
+| `data/germany-market-odds-timeseries.csv` | 420 | Daily Polymarket **"wins the most seats"** probability per party (6 parties, Dec 2024→Feb 2025) from the "Germany Parliamentary Election Winner" market. |
+| `data/germany-divergence-timeseries.csv` | 490 | **Market × poll divergence** per party — each poll's party vote share joined to that party's market odds on its date. |
+| `data/germany-poly-raw.json` | — | Raw Polymarket payload, kept for provenance. |
+<sub>Market data fetched from Polymarket's gamma-api + clob via a US-resolving function. There is no runoff — Germany elects the Bundestag in a single vote.</sub>
+### ⚖️ Notable divergences (why divergence beats the average)
+The market here prices **which party wins the most seats**; the polls measure **party vote share**. In a multi-party system the two come apart sharply — and that gap is the point.
+- **AfD — second in votes, near-zero to win.** In the final polls the AfD held **~21% of the vote**, clearly the **second-largest party** — yet the market gave it only **~3%** of winning the most seats (a −18 pp market−poll gap). High vote share is not the same as a parliamentary plurality, and the market never confused the two. The AfD finished second (20.8%); it did not win the most seats.
+- **CDU/CSU — the mirror image.** ~**29.5%** of the vote but **~97%** to win the most seats (+67 pp): a moderate vote lead translated into near-certain plurality. The CDU/CSU won (28.5%) and Friedrich Merz became Chancellor.
+- **The small-party threshold (5%):** BSW and FDP hovered right at the **5% Bundestag threshold** in vote-share polls while the market priced their probability of *winning* at ~0% — two parties for whom "share" and "win" were never the same question. Both ultimately fell below 5%.
+**The reading:** vote share answers "how many votes," the market answers "who wins" — and in a fragmented parliament those diverge by design. A blended poll average tells you the AfD was second; only the market-versus-poll spread tells you it was second *and* had no path to the plurality.
+**Pollsters covered:** Forsa, INSA, Infratest dimap, Allensbach, YouGov, Ipsos, FGW (Forschungsgruppe Wahlen), GMS, Verian, and others.
+**Provenance & method:** poll figures compiled deterministically (rowspan/colspan-aware HTML parser) from the public Wikipedia aggregation *"Opinion polling for the 2025 German federal election."* Market odds from the public Polymarket market. Nothing imputed or smoothed; missing values 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. Germany 2025 Electoral Divergence Dataset. Hugging Face, 2026. CC BY 4.0.* (see `CITATION.cff`)
+**Disclaimer:** observational research. Not investment advice, not voting guidance.
+---
+## Português
+Dataset aberto cruzando **pesquisas × mercados de previsão** para a **eleição federal alemã de 2025** (Bundestag, 23/fev/2025 — eleição antecipada após o colapso da coalizão em nov/2024). **Nível partido:** as pesquisas medem **voto por partido**; o mercado precifica a **probabilidade de vencer mais cadeiras** — quantidades diferentes, e a diferença é o sinal.
+- `polls/germany-polls.csv` — voto por partido, formato largo, 8 partidos, 349 pesquisas (2024→fev 2025).
+- `data/germany-market-odds-timeseries.csv` / `germany-divergence-timeseries.csv` — probabilidade Polymarket de "vencer mais cadeiras" por partido e divergência mercado × pesquisa.
+### ⚖️ Divergências em destaque (por que a divergência supera a média)
+- **AfD — 2º mais votado, quase zero para vencer.** Nas pesquisas finais a AfD tinha ~**21% do voto** (claramente o 2º maior partido) — mas o mercado lhe dava só **~3%** de vencer mais cadeiras (diferença −18pp). Voto alto não é maioria parlamentar, e o mercado nunca confundiu os dois. A AfD ficou em 2º (20,8%); não venceu.
+- **CDU/CSU — a imagem espelhada.** ~**29,5%** de voto mas **~97%** de vencer mais cadeiras (+67pp): liderança moderada de voto vira maioria quase certa. A CDU/CSU venceu (28,5%) e Friedrich Merz virou chanceler.
+- **O limiar de 5%:** BSW e FDP rondavam os **5% da cláusula de barreira** no voto enquanto o mercado precificava a chance de *vencer* em ~0% — dois partidos para quem "voto" e "vencer" nunca foram a mesma pergunta. Ambos ficaram abaixo de 5%.
+**A leitura:** voto responde "quantos votos", o mercado responde "quem vence" — e num parlamento fragmentado isso diverge por construção. Uma média das pesquisas diz que a AfD era 2ª; só a diferença mercado×pesquisa mostra que era 2ª *e* sem caminho para a maioria.
+---
+## Español
+Dataset abierto que cruza **encuestas × mercados de predicción** para la **elección federal alemana de 2025** (Bundestag, 23 feb 2025). **Nivel partido:** las encuestas miden **voto por partido**; el mercado valora la **probabilidad de ganar más escaños**.
+### ⚖️ Divergencias destacadas
+- **AfD — segundo en votos, casi nulo para ganar.** ~**21% del voto** (2º partido) pero el mercado le daba solo **~3%** de ganar más escaños (−18pp). Voto alto no es mayoría parlamentaria. La AfD quedó 2ª (20,8%); no ganó.
+- **CDU/CSU — la imagen espejo.** ~**29,5%** de voto pero **~97%** de ganar más escaños (+67pp). Ganó (28,5%) y Merz fue canciller.
+- **El umbral del 5%:** BSW y FDP rondaban el 5% en voto mientras el mercado valoraba su probabilidad de *ganar* en ~0%. Ambos quedaron bajo el 5%.
+**Fuente:** agregación pública de Wikipedia; Polymarket. **Licencia:** CC BY 4.0 (atribuir a AFOS Analytics y a las encuestadoras). Investigación observacional; no es asesoría de inversión.
+---
+**Sources / Fontes / Fuentes:** Pollsters (Forsa, INSA, Infratest dimap, Allensbach, …) · [Wikipedia aggregation](https://en.wikipedia.org/wiki/Opinion_polling_for_the_2025_German_federal_election) · Polymarket. Column definitions in [`DATA_DICTIONARY.md`](DATA_DICTIONARY.md).
+## Structural context (World Bank)
+Beyond the divergence data, this dataset ships `data/germany-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`.