Big Five league employment and FIFA World Cup knockout progression conditional on qualification, 2014-2026 a format-harmonised analysis

This repository contains the harmonised data and reproducible analysis code supporting the article “Big Five league employment and FIFA World Cup knockout progression conditional on qualification, 2014-2026: a format-harmonised analysis”. The dataset comprises a census of the 80 team-tournament observations that reached the knockout stage of the 2014, 2018, 2022 and 2026 FIFA World Cups. The player-level file contains 880 starting-eleven records, corresponding to each team’s first knockout match. Big Five exposure was defined as the proportion of starters employed, at the tournament date, in the top divisions of England, France, Germany, Italy or Spain. Knockout progression was harmonised across tournament formats as first-round exit, second-round exit, or advancement beyond the second knockout round. Archived World Football Elo ratings measured pre-tournament team strength using snapshots dated before the opening match of each tournament. The repository includes player- and team-level datasets, archived Elo snapshots, source and verification documentation, a data dictionary, reconstruction and analysis scripts, machine-readable results and publication-quality figures. The code reproduces the ordinal and threshold-specific logistic models, 5,000 cluster-bootstrap samples grouped by national team, leave-one-edition and leave-one-team influence analyses, and a penalised 2026 squad-value sensitivity analysis. The estimand is knockout progression conditional on having reached the knockout stage, not overall FIFA World Cup success. These observational data do not identify a causal effect of employment in a Big Five league.