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World Cup 2026: what the data reveals so far

World Cup 2026: what the data reveals so far

Analysis based on ELO ratings adjusted with Dixon-Coles, official FIFA EFI (Enhanced Football Intelligence) data, and real results from the 83 matches played so far — group stage + round of 32.

We've reached the knockout stage, and the data is starting to tell a clearer story than the pre-tournament predictions suggested. Here are the numbers that actually matter: who tops the real strength ranking, who's over- (or under-) performing the model's expectations, how each qualified team likes to play, and what FIFA's own physical data reveals about the tournament's wear and tear.


1. The real strength ranking (post-groups + round of 32 ELO)

Forget the pre-tournament FIFA ranking. After 83 matches, the ELO system — recalculated match by match, with home-advantage and margin-of-victory multipliers — shows a clearly defined order at the top:

# Team ELO
1 🇫🇷 France 2065
2 🇪🇸 Spain 2024
3 🏴 England 2007
4 🇦🇷 Argentina 2003
5 🇧🇷 Brazil 1980
6 🇵🇹 Portugal 1940
7 🇳🇱 Netherlands 1924
8 🇩🇪 Germany 1906
9 🇨🇴 Colombia 1901
10 🇳🇴 Norway 1898

France has taken a clear lead — not just winning, but doing it dominantly (see section 2). What stands out is Norway in the top 10: no recent tradition of standing out, but an attack that's among the most productive in the tournament (see below), led by the Haaland-Odegaard duo.

2. Who's leading the attack

The tournament's goal average sits at 2.94 goals per game — a high number for a World Cup, driven by a handful of teams that are systematically routing opponents:

Team Goals scored Games
🇫🇷 France 13 4
🇳🇱 Netherlands 11 4
🇩🇪 Germany 11 4
🇳🇴 Norway 10 4
🇺🇸 USA 10 4
🇸🇳 Senegal 10 4

And at the other end, the tournament's most solid defense (by xG against, not just goals conceded — a more reliable metric since it doesn't depend on the goalkeeper's luck):

Team xGA/game
🇪🇸 Spain 0.50
🇦🇷 Argentina 0.54
🇨🇦 Canada 0.67
🇲🇽 Mexico 0.75
🇬🇭 Ghana 0.79
🇧🇷 Brazil 0.80

Interestingly, Spain and Argentina show up as the toughest defenses to break down according to the model, even without necessarily being remembered for that.

3. Who's over- and under-performing

This is where the data gets genuinely interesting. We calculated delta_pts — the difference between the points each team actually earned and the points the model (ELO + Dixon-Coles) expected them to earn given the level of opponents faced. It's not pure luck, but it's the most honest picture of who's "playing above their level" versus who's underdelivering.

Overperforming:

Team delta_pts
🇲🇽 Mexico +2.67
🇫🇷 France +2.67
🇳🇴 Norway +2.17
🇵🇾 Paraguay +1.95
🇬🇭 Ghana +1.50

Mexico's case is a double surprise: not only outperforming expectations, but also enjoying home advantage (like co-hosts USA and Canada) — but that's already priced into the model, so the +2.67 is purely about performance.

Underdelivering (for now):

Team delta_pts
🇺🇾 Uruguay -2.93
🇸🇳 Senegal -2.25
🇩🇪 Germany -2.19
🇹🇳 Tunisia -1.99
🇺🇿 Uzbekistan -1.85

Germany's case is telling: they have the tournament's 3rd-highest goal tally (11) but still disappoint on delta_pts — a sign the defense (involved in that fateful 4-5 penalty shootout loss to Paraguay, which was actually 1-1 in regular time) is costing them dearly. Teams that score a lot but also concede a lot tend to show up here, because the model weighs both sides.

4. How each qualified team likes to play

Using official FIFA EFI data (Enhanced Football Intelligence — tracking over 4,000 rows of player/match data), we mapped each team's goal-creation style: where their shots come from — combination passing, crosses, set pieces, individual carrying, etc.

The most common tactical tags across teams (all calculated by real percentile within the tournament, not opinion):

Tag # of teams
Mid block 30
Set-piece threat 14
Miserly defense 13
Direct style 13
Possession-based 12
Carries the ball a lot 12
Wide/crossing-heavy 12
Leaky defense 12
Low block 10
High-intensity running 9
High press 8

The tournament is clearly dominated by mid-block teams (30 of 48) — the most common posture is to stay organized without fully committing to either high pressing or a deep low block. Only 8 teams press genuinely aggressively throughout.

One concrete example: Spain creates 50% of their shots through combination passing, and carries both "set-piece threat" and "miserly defense" tags — an almost complete profile. Egypt, meanwhile, is curiously the lowest-intensity team in the entire tournament (dead last in sprints/game and defensive pressures applied) and still sits unbeaten, relying on efficiency and set pieces.

5. The penalty-shootout drama

Two round-of-32 matches were decided on penalties — worth flagging a technical detail: public datasets (including football-data.org itself) frequently fold the penalty-shootout score into the actual match score. We corrected this in our modeling because it directly affects ELO, goal difference, and every derived metric:

  • Germany 1-1 Paraguay (regular time) — Paraguay won on penalties 4-3. In the raw data, this incorrectly showed as "4-5".
  • Netherlands 1-1 Morocco (regular time) — Morocco won on penalties 3-2. It showed as "3-4".

Without this fix, Germany would show 14 goals scored and 9 conceded in the stats — in reality, it's 11 and 5. It matters.

6. What's coming

With 10 teams already through to the round of 16 (Belgium, Brazil, Canada, USA, France, England, Morocco, Mexico, Norway, and Paraguay) and the rest of the round of 32 still underway, the tournament's next chapters will test exactly the patterns the data already points to:

  • France and Spain remain the clear ELO favorites, but the model also shows nobody is free from instability — delta_pts deviations show recent results don't always reflect real playing level.
  • Teams tagged with "leaky defense" — 12 in total — are natural candidates to be caught out against quality attacking sides.
  • Penalty-shootout drama has already appeared twice in the round of 32; statistically, it's reasonable to expect more as the balance of quality tightens in the knockout rounds.

Methodology: ELO calculated sequentially (pre-match ratings, not retroactive) with a margin-of-victory multiplier and home-advantage bonus for co-hosts (Mexico, USA, Canada). Probabilities via a bivariate Poisson model with Dixon-Coles adjustment (ρ = -0.18). Physical and chance-creation data via FIFA EFI (source: Bustami/efi-fifa-data-wc-2026). Results data via football-data.org, with manual correction for penalty-shootout matches.

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