Research · Squad cohesion
Which projected XIs walk in already playing together?
Snapshot · 2026-05-22Model 1.0.0For each 2026 World Cup nation we take the model's projected starting XI and quantify how much club-level overlap it carries. Three numbers per team: pairwise shared club-season minutes (normalised to 55 × 3000 = 165,000 maximum), a club-concentration score over the XI's most-recent clubs (Herfindahl-Hirschman index), and the share of the XI playing for the three most common clubs. Methodology in /docs/methodology/.
48 teams · fully-resolved XIs: 3 · lookback window: 2 seasons.
Ranked: pairwise club minutes, descending
15 teams with ≥ 7 resolved XI players.
| # | Team | Pairwise | Concentration | Top-3 | Top clubs |
|---|---|---|---|---|---|
| 1 | France | 5.20% | 0.140 | 50% | AC Milan (2) · Inter (2) · Aston Villa (1) |
| 2 | Portugal | 4.99% | 0.225 | 71% | Manchester United (2) · AC Milan (2) · Barcelona (1) |
| 3 | England | 4.85% | 0.124 | 45% | Manchester City (2) · Arsenal (2) · Everton (1) |
| 4 | Argentina | 4.31% | 0.180 | 60% | Atletico Madrid (3) · Real Betis (2) · Aston Villa (1) |
| 5 | Netherlands | 4.18% | 0.140 | 50% | Liverpool (2) · Inter (2) · Brighton (1) |
| 6 | Germany | 3.06% | 0.124 | 45% | Bayern Munich (2) · VfB Stuttgart (2) · Barcelona (1) |
| 7 | Croatia | 3.00% | 0.161 | 56% | Manchester City (2) · Torino (2) · Fiorentina (1) |
| 8 | Colombia | 2.25% | 0.184 | 57% | Crystal Palace (2) · Cagliari (1) · Tottenham (1) |
| 9 | Belgium | 1.91% | 0.140 | 50% | Eintracht Frankfurt (2) · Manchester City (2) · Real Madrid (1) |
| 10 | Spain | 1.83% | 0.140 | 50% | Manchester City (2) · Barcelona (2) · Athletic Club (1) |
| 11 | Switzerland | 1.23% | 0.107 | 36% | Monaco (2) · Borussia Dortmund (1) · Mainz 05 (1) |
| 12 | Austria | 1.13% | 0.120 | 40% | Freiburg (2) · Real Madrid (1) · Atalanta,Bologna (1) |
| 13 | Brazil | 0.00% | 0.143 | 43% | Chelsea (1) · Paris Saint Germain (1) · Juventus (1) |
| 14 | Norway | 0.00% | 0.143 | 43% | Sevilla (1) · Brentford (1) · Borussia Dortmund (1) |
| 15 | Sweden | 0.00% | 0.111 | 33% | Aston Villa (1) · Manchester United (1) · Atalanta (1) |
Low coverage — read alongside resolved count
33 teams with fewer than 7 resolved XI players.
These teams pull most of their XI from leagues outside our FBref / Understat coverage, so the cohesion numbers below are structurally suppressed — a near-zero pairwise score for an MLS-, Saudi-, or Süper-Lig-heavy XI typically reflects missing data, not genuinely-low club overlap.
| # | Team | Pairwise | Concentration | Top-3 | Top clubs | Resolved |
|---|---|---|---|---|---|---|
| 1 | Scotland | 0.00% | 0.167 | 50% | Arsenal (1) · Everton (1) · Napoli (1) | 6/11 |
| 2 | Uruguay | 0.00% | 0.167 | 50% | Sassuolo (1) · Barcelona (1) · Cagliari (1) | 6/11 |
| 3 | Algeria | 0.19% | 0.280 | 80% | Lille (2) · Nice (1) · Wolverhampton Wanderers (1) | 5/11 |
| 4 | DR Congo | 0.00% | 0.200 | 60% | Marseille (1) · West Ham (1) · Nantes (1) | 5/11 |
| 5 | Czech Republic | 2.65% | 0.280 | 80% | West Ham (2) · Torino (1) · Bayer Leverkusen (1) | 5/11 |
| 6 | Ghana | 0.00% | 0.200 | 60% | Auxerre (1) · Rennes (1) · Arsenal (1) | 5/11 |
| 7 | Japan | 0.00% | 0.200 | 60% | Parma Calcio 1913 (1) · Borussia M.Gladbach (1) · Freiburg (1) | 5/11 |
| 8 | Senegal | 0.27% | 0.280 | 80% | Monaco (2) · Lyon (1) · Everton (1) | 5/11 |
| 9 | United States | 0.92% | 0.280 | 80% | Fulham (2) · Juventus (1) · AC Milan (1) | 5/11 |
| 10 | Ivory Coast | 0.00% | 0.250 | 75% | Angers (1) · Roma (1) · Nottingham Forest (1) | 4/11 |
| 11 | Egypt | 0.00% | 0.250 | 75% | Nice (1) · Arsenal (1) · Eintracht Frankfurt (1) | 4/11 |
| 12 | Morocco | 0.00% | 0.250 | 75% | Manchester United (1) · Paris Saint Germain (1) · Fiorentina (1) | 4/11 |
| 13 | Mexico | 0.00% | 0.250 | 75% | Salernitana (1) · Genoa (1) · Fulham (1) | 4/11 |
| 14 | Bosnia and Herzegovina | 0.00% | 0.333 | 100% | St. Pauli (1) · Atalanta (1) · VfB Stuttgart (1) | 3/11 |
| 15 | South Korea | 0.00% | 0.333 | 100% | Bayern Munich (1) · Paris Saint Germain (1) · Tottenham (1) | 3/11 |
| 16 | Tunisia | 0.00% | 0.333 | 100% | Lorient (1) · Union Berlin (1) · Eintracht Frankfurt (1) | 3/11 |
| 17 | Australia | 0.21% | 1.000 | 100% | St. Pauli (2) | 2/11 |
| 18 | Ecuador | 0.00% | 0.500 | 100% | Bayer Leverkusen (1) · Chelsea (1) | 2/11 |
| 19 | Haiti | 0.00% | 0.500 | 100% | Nantes (1) · Wolverhampton Wanderers (1) | 2/11 |
| 20 | New Zealand | 0.00% | 0.500 | 100% | Empoli (1) · Nottingham Forest (1) | 2/11 |
| 21 | Paraguay | 0.00% | 0.500 | 100% | Getafe (1) · Torino (1) | 2/11 |
| 22 | Turkey | 0.00% | 0.500 | 100% | Atletico Madrid (1) · Inter (1) | 2/11 |
| 23 | Canada | 0.00% | 1.000 | 100% | Villarreal (1) | 1/11 |
| 24 | Cape Verde | 0.00% | 1.000 | 100% | Villarreal (1) | 1/11 |
| 25 | Iran | 0.00% | 1.000 | 100% | Brentford (1) | 1/11 |
| 26 | South Africa | 0.00% | 1.000 | 100% | Burnley (1) | 1/11 |
| 27 | Uzbekistan | 0.00% | 1.000 | 100% | Roma (1) | 1/11 |
| 28 | Curaçao | 0.00% | 0.000 | 0% | — | 0/11 |
| 29 | Iraq | 0.00% | 0.000 | 0% | — | 0/11 |
| 30 | Jordan | 0.00% | 0.000 | 0% | — | 0/11 |
| 31 | Saudi Arabia | 0.00% | 0.000 | 0% | — | 0/11 |
| 32 | Panama | 0.00% | 0.000 | 0% | — | 0/11 |
| 33 | Qatar | 0.00% | 0.000 | 0% | — | 0/11 |
What this is — and isn't
Squad cohesion is a descriptive surface. It captures how much of the projected XI plays together at club level — summed shared minutes for each of the C(11, 2) = 55 pairs, with a join key of (season_end_year, club). Two players who shared a club in different seasons do not count.
This is not a model probability. It does not feed the published tournament-winner numbers. A high cohesion score does not predict a better team — Spain 2022 had an XI heavy in FC Barcelona players and exited early; the descriptive number doesn't close the gap with national-team familiarity, set-piece routines, or manager continuity (which would need lineup-history data we don't have). The number is published for editorial / research use.
The metric inherits the FBref / Understat coverage tilt documented across the rest of the data pipeline: Big-5 leagues are well-covered, while small-league players appear in the ratings table only when they hit Wikipedia top-scorer thresholds. The “low coverage” section above isolates teams where the headline pairwise number is suppressed by missing data rather than by genuine fragmentation.