What shapes a match
Resumen + muestra · documento completo de 820 palabras
How many club minutes has each nation's likely starting XI played this season? This dataset captures the workload each team's players carry into the tournament.
Two CSVs:
data/wc2026/squad_minutes_loaded.csv — one row per team. - data/wc2026/squad_minutes_loaded_detail.csv — one row per (team, player) slot, matched or not.The team-level CSV is the consumer surface. Columns:
| Column | Definition |
|---|---|
team_id, team_name, season_label, data_as_of | Team identity and the season the figures refer to. |
xi_total_minutes, xi_mean_minutes_per_player, xi_median_minutes | Aggregate club minutes for the 11 predicted starters. |
squad_total_minutes, squad_mean_minutes_per_player | Aggregate club minutes for the full 26-man predicted squad. |
n_xi_matched, n_squad_matched | Number of slots we could match to a player-season row. The remaining slots have no minutes recorded. |
match_rate | n_squad_matched / 26. Used by downstream consumers to weight the signal. |
gk_minutes | Goalkeeper-only minutes carve-out. |
The detail CSV preserves the per-player slot, including unmatched ones, so the per-team aggregates are auditable. The spec column club_minutes_last_90_days exists on the detail CSV but is intentionally blank — ratings_player.csv is season-aggregated, not per-match, so a true rolling-90-day window is not derivable from what is on disk.
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