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"