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sergiopesch/wc2026-internationals

WC2026 International Match Outcomes A small, clean tabular dataset of 499 historical international football matches between the 48 FIFA World Cup 2026 finalists, labelled by outcome. Built to train a match-outcome classifier (ml-xgboost-v1). Columns column type description home_rank int Home team's FIFA world ranking at match time home_pts float Home team's FIFA ranking points away_rank int Away team's FIFA world ranking away_pts float Away team's… See the full description on the dataset page: https://huggingface.co/datasets/sergiopesch/wc2026-internationals.

sourceHugging Facecc0-1.0updated 4mo agoView on Hugging Face
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Dataset Card

WC2026 International Match Outcomes

A small, clean tabular dataset of 499 historical international football matches between the 48 FIFA World Cup 2026 finalists, labelled by outcome. Built to train a match-outcome classifier (ml-xgboost-v1).

Columns

columntypedescription
home_rankintHome team's FIFA world ranking at match time
home_ptsfloatHome team's FIFA ranking points
away_rankintAway team's FIFA world ranking
away_ptsfloatAway team's FIFA ranking points
home_is_host0/1Whether the home side is a 2026 tournament host (USA / Mexico / Canada)
labelstrOutcome: HOME_WIN, DRAW, or AWAY_WIN

Label distribution

  • —HOME_WIN — 227 (45.5%)
  • —AWAY_WIN — 149 (29.9%)
  • —DRAW — 123 (24.6%)

Provenance & licence

Features are derived: FIFA world rankings/points (published by FIFA) joined to public international match results. The historical results source is martj42's international football results dataset (CC0 / public domain). This dataset contains only abstracted rank/points/outcome rows — no proprietary provider feed is redistributed. Released under CC0-1.0.

Intended use

Educational / demo. Powers a Salesforce + Hugging Face "bring your own model" demo for the FIFA World Cup 2026. Three coarse features mean it captures broad strength gaps, not tactical detail — treat predictions as illustrative.