| cff-version: 1.2.0 | |
| message: "If you use this dataset, please cite it as below." | |
| title: "AFOS · Mexico 2024 Electoral Divergence Dataset" | |
| abstract: >- | |
| Open dataset cross-referencing opinion polls and prediction markets for Mexico's | |
| 2024 presidential election (single round, 2 June 2024), with explicit poll-versus-market | |
| divergence rather than a blended average. Polls measure candidate vote share; the market | |
| prices the probability of winning the presidency. From January the market gave Claudia | |
| Sheinbaum about 90% to win while polls measured her vote share around 50%; Sheinbaum won | |
| with about 59.8% of the vote, the largest vote count in Mexican history, ahead of Xóchitl | |
| Gálvez (27.5%) and Jorge Álvarez Máynez (10.3%). Poll figures compiled deterministically | |
| from public pollster releases (via the Wikipedia aggregation), excluding poll-of-poll | |
| aggregators; market odds from Polymarket. | |
| type: dataset | |
| authors: | |
| - name: "AFOS Analytics" | |
| website: "https://afos-analytics.com" | |
| keywords: | |
| - elections | |
| - Mexico | |
| - opinion polls | |
| - prediction markets | |
| - divergence | |
| - open data | |
| license: CC-BY-4.0 | |
| repository: "https://huggingface.co/datasets/AFOS-Analytics1/mexico-2024-electoral-divergence" | |
| url: "https://afos-analytics.com" | |
| version: "2026.06" | |
| date-released: "2026-06-13" | |