Spain beat Argentina in extra time to win the 2026 World Cup
Ferran Torres scored in the 106th minute of a 1–0 final. Spain conceded one goal in eight matches and won its second men’s World Cup.
APGO Football
World Cup analysis and player ranking research
The first ranking will follow a published backtest, data review and consultation with independent analysts.
World Cup 2026
The 48-team World Cup drew record crowds and raised workload questions
FIFA reported 6.8 million spectators and 308 goals across 104 matches. Independent data on travel, player recovery and public cost will determine the fuller case for expansion.
World Player Index · Research proposal v0.2
How the first model will be tested
The proposed index uses a rolling 365-day window, role-specific baselines and confidence estimates. APGO will publish results after licensed data has been backtested across several completed seasons and reviewed outside the project.
Status
APGO is developing this project independently. FIFA and other governing bodies have no role in its design or publication.
| # | Layer | What it measures | Weight |
|---|---|---|---|
| 01 | Match impact | Creation, finishing, progression and prevention | 35% |
| 02 | Role execution | Position-specific responsibilities and error cost | 20% |
| 03 | Opponent strength | Team Elo, competition and match context | 20% |
| 04 | Availability | Minutes, continuity and reliable contribution | 15% |
| 05 | High leverage | Close match states and knockout rounds | 10% |
These weights are provisional and will be revised after backtesting.
Method proposal v0.2
Last reviewed 20 July 2026From event data to a player score
Define coverage
List every competition and data provider, disclose missing leagues and apply a 900-minute eligibility threshold.
Compare roles
Evaluate players against the responsibilities of their own positions before comparing scores across the pitch.
Adjust context
Account for possession, game state, opponent strength, minutes and opportunity.
Weight recency
Test a 120-day half-life, capped match-importance multipliers and a documented team-strength model.
Estimate uncertainty
Pull small samples toward the midpoint and publish confidence and coverage measures.
Archive releases
Publish weights, model versions, changes and corrections. Downloadable outputs will depend on data licences.
Proposed aggregation
Index = 50 + 10 × confidence × weighted role scoreThe confidence term increases with competitive minutes and reduces the influence of small samples.
Release plan
- Data and definitionsSecure lawful coverage, publish the data dictionary and test for league and role bias.
- Backtest and reviewRun completed seasons and invite external analysts to challenge the results.
- Pilot top 25Release scores, uncertainty, minutes, role tables and placement notes.
- Quarterly indexAdd player histories and comparisons after the pipeline is reproducible.
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