2026 World Cup Goalkeepers: A Complete X-ray of All 48 Starters
Updated on 07/05/2026 — analysis expanded to all 48 starting goalkeepers of all national teams in the 2026 World Cup, based on official "Goal Prevention" FIFA reports (PMSR) from all group stage and Round of 16 matches, cross-referenced with the actual xG of each match.
Raw Save% has always been a deceptive metric: a goalkeeper playing behind a strong defense and only facing long shots has an artificially high SV%; one who faces a bombardment of difficult shots may have a low SV% despite making incredible saves. By using official FIFA reports — which classify every shot conceded as either "required a real save" or "did not require action" — we have built a fairer metric: Quality%, the proportion of genuinely dangerous shots that the goalkeeper handled well.
⚠️ Methodological Note: Sergio Rochet (Uruguay) was excluded from the main analysis — he only came on in the 45th minute of a single match (2nd half vs. Spain, replacing Fernando Muslera, who was criticized after an error). Since FIFA data is for full matches, it was not possible to separate Muslera's numbers from Rochet's. In this expansion, we also identified and treated separately other mid-tournament goalkeeper changes (Norway, Tunisia, USA, Uzbekistan) — in each case, we only used the complete matches of the primary starter, excluding mixed matches or those with a reserve playing limited minutes.
📊 Complete Table — 48 Starting Goalkeepers
| # | Goalkeeper | Nat. | Matches | GS | Raw SV% | Shots Faced (FIFA) | % Easy Shots | Quality% | GS/90 | Team xGA | Perf. vs xGA |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Lionel Mpasi | COD | 4 | 5 | 23% | 49 | 63.3% | 88.9% | 1.25 | 1.00 | -0.25 |
| 2 | Maxime Crepeau | CAN | 5 | 6 | 22% | 22 | 63.6% | 87.5% | 1.20 | 0.70 | -0.50 |
| 3 | Gregor Kobel | SUI | 4 | 3 | 33% | 33 | 54.5% | 86.7% | 0.75 | 0.79 | +0.04 |
| 4 | Mike Maignan | FRA | 5 | 2 | 24% | 28 | 53.6% | 76.9% | 0.40 | 0.81 | +0.41 |
| 5 | Zion Suzuki | JPN | 4 | 5 | 32% | 44 | 45.5% | 75.0% | 1.25 | 0.83 | -0.42 |
| 6 | Alisson | BRA | 4 | 2 | 30% | 40 | 60.0% | 75.0% | 0.50 | 0.64 | +0.14 |
| 7 | Diogo Costa | POR | 4 | 2 | 26% | 54 | 63.0% | 75.0% | 0.50 | 1.00 | +0.50 |
| 8 | Unai Simon | ESP | 4 | 0 | 75% | 21 | 61.9% | 75.0% | 0.00 | 0.18 | +0.18 |
| 9 | Alireza Beiranvand | IRN | 3 | 3 | 24% | 52 | 57.7% | 72.7% | 1.00 | 1.29 | +0.29 |
| 10 | Luca Zidane | ALG | 3 | 6 | 25% | 39 | 53.8% | 72.2% | 2.00 | 1.23 | -0.77 |
| 11 | Vozinha | CPV | 4 | 5 | 27% | 75 | 66.7% | 72.0% | 1.15 | 1.89 | +0.74 |
| 12 | Ronwen Williams | RSA | 4 | 4 | 22% | 51 | 58.8% | 71.4% | 1.00 | 1.30 | +0.30 |
| 13 | Emiliano Martínez | ARG | 4 | 3 | 40% | 34 | 79.4% | 71.4% | 0.75 | 0.63 | -0.12 |
| 14 | Thibaut Courtois | BEL | 4 | 4 | 69% | 48 | 64.6% | 70.6% | 1.00 | 0.90 | -0.10 |
| 15 | Matt Freese | USA | 3 | 1 | 67% | 25 | 60.0% | 70.0% | 0.33 | 0.37 | +0.04 |
| 16 | Yassine Bounou | MAR | 5 | 4 | 24% | 35 | 62.9% | 69.2% | 0.75 | 0.68 | -0.07 |
| 17 | Mohammed Al-Owais | KSA | 3 | 5 | 84% | 65 | 60.0% | 69.2% | 1.67 | 2.02 | +0.35 |
| 18 | Mahmoud Abunada | QAT | 3 | 10 | 62% | 79 | 63.3% | 69.0% | 3.33 | 2.60 | -0.73 |
| 19 | Kim Seung-gyu | KOR | 3 | 3 | 75% | 28 | 42.9% | 68.8% | 1.00 | 0.62 | -0.38 |
| 20 | Eloy Room | CUW | 3 | 9 | 30% | 63 | 50.8% | 67.7% | 3.00 | 2.62 | -0.38 |
| 21 | Orlando Gill | PAR | 5 | 6 | 22% | 85 | 57.6% | 66.7% | 1.12 | 1.49 | +0.37 |
| 22 | Matej Kovar | CZE | 3 | 6 | 61% | 44 | 59.1% | 66.7% | 2.00 | 1.74 | -0.26 |
| 23 | Raul Rangel | MEX | 4 | 0 | 100% | 32 | 71.9% | 66.7% | 0.00 | 0.47 | +0.47 |
| 24 | Bart Verbruggen | NED | 4 | 5 | 31% | 48 | 41.7% | 64.3% | 1.15 | 0.93 | -0.22 |
| 25 | Yazeed Abulaila | JOR | 3 | 8 | 44% | 41 | 65.9% | 64.3% | 2.67 | 2.17 | -0.50 |
| 26 | Orlando Mosquera | PAN | 3 | 4 | 72% | 30 | 53.3% | 64.3% | 1.33 | 1.14 | -0.19 |
| 27 | Lawrence Ati Zigi | GHA | 2 | 1 | 35% | 58 | 56.9% | 64.0% | 0.67 | 1.21 | +0.54 |
| 28 | Manuel Neuer | GER | 4 | 5 | 50% | 31 | 58.1% | 61.5% | 1.25 | 0.89 | -0.36 |
| 29 | Patrick Beach | AUS | 4 | 3 | 24% | 65 | 64.6% | 60.9% | 0.69 | 1.19 | +0.50 |
| 30 | Edouard Mendy | SEN | 2 | 6 | 38% | 50 | 50.0% | 60.0% | 3.53 | 1.27 | -2.26 |
| 31 | Johny Placide | HAI | 3 | 8 | 28% | 41 | 46.3% | 59.1% | 2.67 | 1.48 | -1.19 |
| 32 | Jordan Pickford | ENG | 4 | 3 | 52% | 32 | 56.3% | 57.1% | 0.75 | 0.63 | -0.12 |
| 33 | Ugurcan Cakir | TUR | 3 | 5 | 57% | 34 | 58.8% | 57.1% | 1.67 | 1.04 | -0.63 |
| 34 | Fernando Muslera | URU | 2 | 3 | 58% | 19 | 63.2% | 57.1% | 1.50 | 0.80 | -0.70 |
| 35 | Jacob Widell Zetterstrom | SWE | 2 | 4 | 33% | 51 | 43.1% | 55.2% | 2.00 | 1.68 | -0.32 |
| 36 | Yahia Fofana | CIV | 4 | 4 | 22% | 51 | 60.8% | 55.0% | 1.00 | 1.70 | +0.70 |
| 37 | Dominik Livakovic | CRO | 4 | 7 | 22% | 52 | 57.7% | 54.5% | 1.75 | 1.67 | -0.08 |
| 38 | Aymen Dahmen | TUN | 2 | 7 | 46% | 32 | 65.6% | 54.5% | 3.50 | 1.58 | -1.92 |
| 39 | Mostafa Shoubir | EGY | 4 | 4 | 87% | 58 | 67.2% | 52.6% | 1.00 | 1.19 | +0.19 |
| 40 | Nikola Vasilj | BIH | 4 | 8 | 44% | 43 | 51.2% | 52.4% | 2.00 | 1.33 | -0.67 |
| 41 | Hernan Galindez | ECU | 4 | 4 | 69% | 53 | 56.6% | 52.2% | 1.00 | 1.28 | +0.28 |
| 42 | Jalal Hassan | IRQ | 2 | 8 | 25% | 61 | 63.9% | 50.0% | 5.33 | 2.47 | -2.86 |
| 43 | Angus Gunn | SCO | 3 | 4 | 71% | 48 | 62.5% | 50.0% | 1.33 | 1.76 | +0.43 |
| 44 | Alexander Schlager | AUT | 4 | 9 | 21% | 59 | 47.5% | 48.4% | 2.25 | 1.69 | -0.56 |
| 45 | Max Crocombe | NZL | 3 | 10 | 52% | 71 | 63.4% | 46.2% | 3.33 | 2.65 | -0.68 |
| 46 | Camilo Vargas | COL | 4 | 1 | 62% | 37 | 67.6% | 41.7% | 0.25 | 0.69 | +0.44 |
| 47 | Orjan Nyland | NOR | 3 | 4 | 43% | 41 | 56.1% | 38.9% | 1.33 | 1.56 | +0.23 |
| 48 | Abduvohid Nematov | UZB | 2 | 8 | 38% | 37 | 54.1% | 35.3% | 4.00 | 2.07 | -1.93 |
GS, raw SV%, and Shots Faced cover the complete matches of each national team's starting goalkeeper (group stage + Round of 16, where applicable). Team xGA is the average actual xG conceded per match (source: official FIFA reports). Raw SV% is the simple average of the "Save %" published by FIFA per match — reminder: this metric tends to reach 100% whenever the team does not concede a goal in that match, so it should not be confused with Quality%, which weights based on the actual difficulty of each shot.
📈 Ranking by Quality% — All 48 Goalkeepers
The chart below ranks the 48 starters based on the percentage of genuinely dangerous shots handled well (green = 75%+, yellow = 60-75%, red = below 60%).
⚖️ Who Is Outperforming Expectations? — All 48 Goalkeepers
By cross-referencing Quality% with the actual xG conceded by their national team, we can see who is truly compensating for a defense exposed to quality chances — and who is being supported by a solid defense. Green bars = the goalkeeper conceded fewer goals than expected based on the risk level allowed by the team; red bars = they conceded more than expected.
Vozinha (Cape Verde) remains at the top (+0.74) even with the sample expanded to 48 teams — he faces the 2nd highest actual xGA in the entire World Cup (1.89/game) and yet concedes few goals. Immediately behind are Yahia Fofana (Ivory Coast, +0.70) and the surprises of the expansion: Camilo Vargas (Colombia, +0.44) and Orjan Nyland (Norway, +0.23) — despite having an average Quality%, they play behind more exposed defenses than average and still maintain the result. At the bottom of the ranking, Abduvohid Nematov (Uzbekistan, -1.93) and Aymen Dahmen (Tunisia, -1.92) join Jalal Hassan (Iraq, -2.86) and Edouard Mendy (Senegal, -2.26) as the most deficit cases.
🥅 Shot Maps — Outcome Distribution
Important note: FIFA does not provide exact coordinates of where each shot was taken, so these are not actual shot placement maps — they are a visual representation of how many shots fell into each outcome category (save and hold, parry, etc.), illustratively distributed in and around the goal to give an idea of volume. Selection: the top 5 by Quality% from the original sample.
Note how Lionel Mpasi (DR Congo) has a high concentration of "save and clear danger" shots — he doesn't just hold the ball, he often resolves immediate danger too. Diogo Costa, on the other hand, has the highest total volume of shots faced (54) among the five, which makes his 75% Quality% even more respectable.
✈️ Aerial Dominance — Who Commands the Air
Note: this section and the next (Distribution) still cover the 24 goalkeepers from the first round of analysis — they have not yet been recalculated for all 48.
Using official FIFA "Aerial Control" data (punches, claims, and catches), we calculated the aerial intervention rate: of all crosses faced, how many did the goalkeeper actually come off their line to intervene.
Maxime Crepeau (Canada) leads by a large margin (30.4% of crosses faced resulted in an intervention), followed by Edouard Mendy (Senegal, 25.0%). At the opposite end, Mike Maignan (France) recorded zero aerial interventions from 41 crosses faced throughout the World Cup.
🎯 Distribution: Short Passes and Vertical Lines
The modern goalkeeper doesn't just save shots — they also initiate attacks. Using the "In Possession — Individual Data" section of the official reports (tabular data, not radial graph), we checked the passing accuracy and vertical line rate of three specific goalkeepers game by game.
| Goalkeeper | Match | Completed Passes % | Vertical Lines % |
|---|---|---|---|
| Alisson | vs Haiti (M29) | 28/34 (82%) | 3/8 (38%) |
| Alisson | vs Scotland (M49) | 21/23 (91%) | 3/5 (60%) |
| Alisson | vs Japan (M76) | 18/25 (72%) | 2/8 (25%) |
| Diogo Costa | vs DR Congo (M23) | 28/34 (82%) | 5/9 (56%) |
| Diogo Costa | vs Colombia (M71) | 19/23 (83%) | 3/6 (50%) |
| Gregor Kobel | vs Algeria (M85) | 32/45 (71%) | 7/19 (37%) |
Alisson was excellent with the ball at his feet against Haiti (82% passes, 38% vertical lines) and even better against Scotland (91% passes, 60% vertical lines) — but he dropped significantly in the round of 16 against Japan: passes remained solid (72%), but the vertical line rate plummeted to 25% (be careful not to confuse: the drop was in vertical lines, not the pass itself). Diogo Costa maintained similar numbers in the two analyzed matches, being the most consistent of the three. Gregor Kobel stands out for volume: against Algeria, he attempted 19 vertical lines, completing 7 (37%) — a more proactive style in build-up play.
😬 The Worst World Cup Mistakes — When an Error Becomes a Goal
Not everything in a World Cup is about spectacular saves. The 2026 edition is seeing an unusual number of individual errors leading to goals — according to BBC Sport, there were 52 errors leading to a shot in the first matchday of the group stage alone, surpassing the 42 errors in the entire 2022 World Cup (64 games). The BBC offers some hypotheses: physical wear and tear due to long European seasons, heat in several stadiums, and even a theory from former goalkeeper Joe Hart that the official ball "arrives faster than expected." Some specific, verified cases:
- Fernando Muslera (Uruguay): the worst individual case of the tournament. He made mistakes in all three group stage matches and was substituted at halftime against Spain (the first non-forced goalkeeper substitution in a World Cup since 2014) — the first goalkeeper since 1966 to commit 3 errors leading to goals in a single edition.
- Ronwen Williams (South Africa): in the opening match against Mexico, his short pass to midfielder Sithole was intercepted near his own area, paving the way for Julián Quiñones' goal.
- Kim Seung-gyu (South Korea): he came out to claim a cross against Mexico, collided with his own defender, and left the ball at Luis Romo's feet — an incident officially classified in the FIFA report as "Loose Ball."
- Aymen Dahmen / Mouhib Chamakh (Tunisia): the national team made 6 errors in total against Sweden, 4 of which directly led to goals in the 5-1 defeat.
- Yazeed Abulaila (Jordan): he tried to "guess" the side of a Messi free-kick and watched the ball go in almost straight down the middle of the goal — instantly becoming a meme.
The BBC also cites Edouard Mendy (Senegal) and Luca Zidane (Algeria) among goalkeepers with slow reactions to goals conceded early in the tournament — two names that already appear among the lowest positions in our Perf. vs xGA ranking, a good cross-confirmation of our numbers.
And the heroic counterpart: Eloy Room (Curaçao) did the opposite of a mistake — 15 saves in a single game (0-0 against Ecuador), a record in regular time of a World Cup, helping Curaçao become the smallest country by population to earn a point in tournament history.
📋 Main Conclusions
- Top 3 by pure Quality% (among the 48): Lionel Mpasi (88.9%), Maxime Crepeau (87.5%), and Gregor Kobel (86.7%).
- Best balance vs. actual xG, with expanded sample: Vozinha (Cape Verde, +0.74) remains at the top, followed by Yahia Fofana (Ivory Coast, +0.70) and Lawrence Ati Zigi (Ghana, +0.54).
- Major collective disappointments: Iraq (-2.86), Senegal (-2.26), Uzbekistan (-1.93), and Tunisia (-1.92) — the defense around the goalkeeper suffers much more than it should.
- The "big teams" in the middle of the ranking: Spain (Unai Simón, 75.0% Quality%) is the best among the traditional favorites; Germany (Manuel Neuer) and Argentina (Emiliano Martínez) remain in the middle third; Colombia (Camilo Vargas, 41.7%) and Norway (Orjan Nyland, 38.9%) are surprisingly negative in pure Quality%, although they partially compensate in the balance vs xG.
- The other side of the coin: Muslera (Uruguay) has been the worst individual case of the World Cup so far, with 3 errors leading to goals — a negative record since 1966.
Great Performances and Decisive Moments
Beyond aggregated numbers, some isolated matches deserve special attention — portraits of goalkeepers carrying their team on their shoulders in specific 90 minutes.
The Technical Verdict: Diogo Costa and Mostafa Shoubir
The "Goal Prevention" analysis shows that technical consistency is not only about the most famous national teams, but also about specific high-level performances:
- Diogo Costa (Portugal) faced 26 shots against Colombia (0-0, group stage) ending with 100% saves — one of the performances with the highest combined volume and effectiveness in the entire tournament.
- Mostafa Shoubir (Egypt), in the draw against Belgium, saved 17 shots with 100% effectiveness, neutralizing the Belgian attack without conceding dangerous rebounds.
Alisson's Real Fluctuation (Brazil)
Against Japan, Alisson faced only 2 shots on target and conceded 1 goal, ending the match with 50% saves — his worst isolated figure of the competition. An important correction here: the drop was not in the general pass distribution (he finished that match with 72% overall accuracy, 18 out of 25), but specifically in the riskier vertical lines, where he only completed 2 out of 8 attempts (25%) — quite different from the 82% overall accuracy against Haiti. In other words: Alisson didn't "break" on simple passes, he just had an off night attempting difficult ones. He still remained active in defensive coverage: 6 possession recoveries against Scotland show that he remains a safe element even away from goal.
Area Dominance: Qatar's Aerial Advantage
Qatar's goalkeeper is the most proactive in the tournament in aerial play: against Switzerland, he made 8 aerial interventions, including 6 punches to clear danger — an unusual aggressiveness in coming off his line. In terms of pure volume, Qatar also leads: 35 shots faced against Canada, albeit with a low save percentage (44%) due to the large scoreline.
Resilience Ranking (Volume of Shots Faced)
| Goalkeeper (Nation) | Match | Shots Faced | Save Percentage |
|---|---|---|---|
| Orlando Gill (PAR) | vs Turkey | 34 | 100% |
| Vozinha (CPV) | vs Spain | 28 | 100% |
| Diogo Costa (POR) | vs Colombia | 26 | 100% |
| Mostafa Shoubir (EGY) | vs Belgium | 17 | 100% |
| Alisson (BRA) | vs Haiti | 7 | 100% |
Costly Mistakes
Not all are impenetrable walls: Uruguay (vs Saudi Arabia) finished with only 67% save percentage, and Sweden (vs Netherlands) recorded one of the worst figures of the tournament, with just 29% effectiveness in decisive interventions.
The Finale: Volume Walls vs. Game Architects
If we had to choose two archetypes to symbolize the goalkeeping styles of this World Cup, they would be these:
The Volume Walls — Vozinha (Cape Verde) and Orlando Gill (Paraguay) — play under constant pressure and try to break lines throughout the match: 20+ attempts every 90 minutes, almost double the tournament average. Vozinha still manages a 54.3% success rate in these risky plays; Gill sacrifices precision (37.1%) for volume, a sign of a team that pushes the ball forward out of necessity, even knowing they will often lose possession.
The Game Architects — and here the data gave us an interesting twist. Diogo Costa is, in fact, a model of efficiency: few vertical lines (6.5/90), but with 80.2% overall passing accuracy — he simply doesn't need to force it, because Portugal dominates possession. But the one who truly earns the title of "Architect" by the numbers is Unai Simón: the lowest volume of risk among goalkeepers with 3+ complete matches (8.0 vertical lines/90) combined with the best overall passing accuracy percentage of the entire World Cup (92.5%). Simón is not the most flamboyant goalkeeper, but he is the one who makes the fewest mistakes — the perfect definition of an architect who builds without fanfare.
The lesson the numbers leave us with: a high volume of distribution is not synonymous with quality, and a low volume is not synonymous with fear. It's a style of play — and each of these goalkeepers carries their team on their shoulders in their own way.
Data extracted and validated from the 88 official FIFA Post Match Summary Reports for the 2026 World Cup.
Methodology: data extracted from official FIFA PMSR (Post-Match Statistical Review) reports for the 2026 World Cup, covering the group stage and round of 16, for the 48 starting goalkeepers of the 48 national teams. Quality% = (Save and Hold + Parry and Hold + Save and Clear) ÷ (Total shots faced − shots that did not require action). The xGA per national team is the actual xG of each match summed only in the complete matches of the identified starter via official lineup. Aerial dominance and distribution (specific sections) still cover only the 24 goalkeepers from the first round of analysis. Data on errors/mistakes cross-referenced with BBC Sport reports and other news outlets. Data subject to updates as more matches are played.
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