⚽ 2026 FIFA World Cup Analytics · Swaab et al. (2014) Modeling

Soccer Team Dynamics & Synergy Model

Empirical research evaluating international squad cohesion, domestic club co-playing density (C_d), tactical integration (T_i), age cohort alignment (A_t), and squad quality concentration (Q_c) across all 48 national squads qualified for the 2026 FIFA World Cup.

#1 SPAIN
Top Synergy Score (95.0) · Domestic Blocks
#2 FRANCE
Synergy Score (94.3) · High Integration
#3 GERMANY
Synergy Score (93.9) · Bundesliga Core
#4 ENGLAND
Synergy Score (90.9) · Premier League Depth
🔬 Scientific Foundation & Mathematical Synergy Model worldfootballR · Transfermarkt

Grounded in behavioral sports economics research (Swaab et al., Psychological Science 2014: The Too-Much-Talent Effect), this index captures how shared domestic familiarity and club tactical partnerships compound international tournament performance:

S = (T_i × 0.25 + C_d × 0.40 + A_t × 0.20 + Q_c × 0.15), normalised [40 – 95]
C_d (Club Co-Playing Density, 40%): HHI concentration of players sharing domestic clubs (e.g., Real Madrid/Barcelona, Bayern Munich).
T_i (Tactical Integration, 25%): Domestic league minutes and tactical familiarity across starting 26.
A_t (Age Cohort Alignment, 20%): Core squad age curve matching peak athletic tournament efficiency (25–29 yrs).
Q_c (Quality Concentration, 15%): Top-5 European league player depth vs reliance on single stars.

📊 Head-to-Head Squad Dynamics Comparison

Quick Matchups:

🏆 Full 48-Nation World Cup Synergy Leaderboard

Click any team row to inspect head-to-head dynamics against the tournament favorite.

Rank Nation Group Synergy Score (S) Squad Cohesion Profile Club Density (C_d) Tactical Integration (T_i) Age Alignment (A_t) Quality Conc (Q_c) Tournament Tier