2026 World Cup Goalkeepers: A Complete X-ray of All 48 Starters
Updated on 07/05/2026 — extended analysis for all 48 starting goalkeepers of the 2026 World Cup national teams, based on official FIFA "Goal Prevention" reports (PMSR) from all group stage and Round of 32 matches, cross-referenced with actual xG for each match.
Raw Save% has always been a misleading metric: a goalkeeper playing behind a strong defense who only faces long-range shots has an artificially high SV%; a goalkeeper facing a barrage of difficult shots might have a low SV% even when making incredible saves. Using official FIFA reports — which classify each shot faced as either "required a real save" or "did not require action" — we have developed 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 critically sent off after a mistake). Since FIFA data is per full match, it was not possible to separate Muslera's data from Rochet's. In this expansion, we also identified and separately treated other goalkeeper changes during the World Cup (Norway, Tunisia, USA, Uzbekistan) — in each case, we only used the main starter's complete matches, excluding mixed matches or those of a substitute with few minutes.
📊 Full Table — 48 Starting Goalkeepers
| # | Goalkeeper | Team | Matches | GA | Raw SV% | Shots Faced (FIFA) | % Easy Shots | Quality% | GA/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 |
GA, Raw SV% and Shots Faced cover the complete matches of each team's starting goalkeeper (group stage + Round of 32, 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 game — reminder: this metric usually reaches 100% whenever the team does not concede a goal in that game, so it should not be confused with Quality%, which accounts for the actual difficulty of each shot.
📈 Quality% Ranking — All 48
The chart below ranks the 48 starters by the proportion of genuinely dangerous shots they handled well (green = 75%+, yellow = 60-75%, red = below 60%).
⚖️ Who is outperforming their expected goals conceded? — All 48
By crossing Quality% with the actual xG conceded by their own team, we can see who is truly compensating for a defense exposed to quality chances — and who is being carried by a solid defense. Green bars = the goalkeeper conceded fewer goals than expected given the risk level allowed by the team; red bars = conceded more than expected.
🥅 Shot Maps — Distribution of Outcomes
Important note: FIFA does not provide exact coordinates of where each shot was taken, so these are not maps of the actual shot position — they are a visual representation of how many shots fell into each outcome category (saved and held, deflected, etc.), illustratively distributed within and around the goal to give a sense of volume. Selection: the top 5 in Quality% from the original sample.
Notice how Lionel Mpasi (DR Congo) has a high concentration of "save and clear" shots — he not only holds the ball, but often resolves immediate danger. 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.
🧱 X-Ray of the 3 highest-volume walls — Gill, Mpasi, and Vozinha
The three goalkeepers below handled the highest volume of work in the tournament. Here we look at each player's complete career in the World Cup, including — in Orlando Gill's case — the Round of 16 match against France (M89), which falls outside the standard scope of this article (group stage + Round of 32). This is why Gill's numbers appear in two versions: 85 shots faced in 4 games in the main table above, and 100 shots faced in 5 games in this section, which also includes the Round of 16.
Orlando Gill · Paraguay
100 shots faced
5 games · 6 goals conceded · 85% weighted efficiency
Lionel Mpasi · Congo DR
49 shots faced
4 games · 5 goals conceded · 60% weighted efficiency
Vozinha · Cape Verde
75 shots faced
4 games · 5 goals conceded · 69% weighted efficiency
Accumulated intervention type in the tournament — the same outcome classification used in the graphs above, now summed game by game for each of the three.
Shot map — each goalkeeper's most decisive match. Same methodological warning as the previous section: FIFA does not provide exact coordinates of where each shot was taken, so this is a distribution of outcomes per match, not a real position map.
Gill: 15 shots faced, 80% efficiency. Mpasi: 17 shots faced, 67% efficiency. Vozinha: 23 shots faced, 73% efficiency — by far the busiest game for the three.
✈️ Aerial dominance — who rules the air
Note: this section and the next (Distribution) cover the initial 24 goalkeepers in the analysis — they have not yet been recalculated for all 48.
Using official FIFA "Aerial Control" data (punches, claims, and saves with hands), we calculated the aerial intervention rate: out of all crosses faced, how many did the goalkeeper effectively come off their line to intervene.
Maxime Crepeau (Canada) leads by a wide margin (30.4% of crosses faced resulted in his intervention), followed by Edouard Mendy (Senegal, 25.0%). At the other end, Mike Maignan (France) had zero aerial interventions from 41 crosses faced throughout the World Cup.
🎯 Distribution: short pass and line-breaking pass
A modern goalkeeper is not only someone who makes saves — they also initiate plays. Using the "In Possession — Individual Data" section of official reports (tabulated data, not a radial chart), we checked the pass accuracy and line-breaking pass rate of three specific goalkeepers game by game.
| Goalkeeper | Match | Completed Passes % | Line-Breaking Passes % |
|---|---|---|---|
| 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% line breaks) and even better against Scotland (91% passes, 60% line breaks) — but dropped significantly in the Round of 32 against Japan: his passes remained solid (72%), but his line-breaking pass rate plummeted to 25% (not to be confused: it was the line-breaking pass rate that dropped, not the pass itself). Diogo Costa maintains similar numbers in the two analyzed games, the most consistent of the three. Gregor Kobel stands out for volume: against Algeria, he attempted 19 line-breaking passes, completing 7 (37%) — a more proactive style in build-up play.
😬 The biggest blunders of the World Cup — when error turns into goal
Not everything in a World Cup is about spectacular saves. The 2026 edition is recording an unusual number of individual errors leading to goals — according to BBC Sport, there were 52 errors leading to shots in just the first round of the group stage, surpassing the 42 errors of the entire 2022 World Cup (64 games). The BBC points to hypotheses: physical fatigue from 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. Failed 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 make 3 errors leading to goals in a single edition.
- Ronwen Williams (South Africa): in the opening match against Mexico, a short pass from him to midfielder Sithole was intercepted near his own box, paving the way for Julián Quiñones' goal.
- Kim Seung-gyu (South Korea): came out to claim a cross against Mexico, collided with his own defender, and dropped the ball at Luis Romo's feet — officially classified in the FIFA report as a "Loose Ball."
- Aymen Dahmen / Mouhib Chamakh (Tunisia): the team made 6 errors in total against Sweden, 4 directly leading to goals in the 5-1 rout.
- Yazeed Abulaila (Jordan): tried to "guess" the corner of a Messi free-kick and saw the ball go in practically down the middle — becoming an instant meme.
The BBC also mentions Edouard Mendy (Senegal) and Luca Zidane (Algeria) among goalkeepers with slow reactions to goals conceded early in the tournament — two names that already appear in the worst positions of our Perf. vs xGA ranking, a good cross-validation of our own numbers.
And the heroic counterpoint: Eloy Room (Curaçao) did the opposite of a blunder — 15 saves in a single match (0-0 against Ecuador), a record in regular time for a World Cup, helping Curaçao become the smallest country by population to score points in tournament history.
📋 Key takeaways
- Top 3 in pure Quality% (among the 48): Lionel Mpasi (88.9%), Maxime Crepeau (87.5%), and Gregor Kobel (86.7%).
- Best balance vs. real xG, with expanded sample: Vozinha (Cape Verde, +0.74) remains ahead, followed by Yahia Fofana (Ivory Coast, +0.70) and Lawrence Ati Zigi (Ghana, +0.54).
- Biggest 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.
- "Big" teams in the middle of the table: Spain (Unai Simon, 75.0% Quality%) is the best of the traditional favorites; Germany (Manuel Neuer) and Argentina (Emiliano Martínez) are in the middle third; Colombia (Camilo Vargas, 41.7%) and Norway (Orjan Nyland, 38.9%) surprisingly perform poorly in pure Quality%, although they partially compensate in their balance vs. xG.
- The other side of the coin: Muslera (Uruguay) was 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 aggregate numbers, some individual games deserve special mention — they are a portrait of goalkeepers carrying their team on their shoulders in 90 specific minutes.
The technical verdict: Diogo Costa and Mostafa Shoubir
The "Goal Prevention" analysis shows that technical consistency appears not only in highly-touted national teams, but also in individual high-level performances:
- Diogo Costa (Portugal) faced 26 shots against Colombia (0-0, group stage) and finished with 100% success rate — one of the highest-volume and most efficient combined performances of the entire tournament.
- Mostafa Shoubir (Egypt), in the draw against Belgium, stopped 17 shots with 100% effectiveness, neutralizing the Belgian attack without conceding dangerous rebounds.
The real fluctuation of Alisson (Brazil)
Against Japan, Alisson faced only 2 shots on target and conceded 1 goal, finishing the match with a 50% success rate — his worst individual mark in the competition. An important correction here: the drop was not in the general pass distribution (he finished that game with 72% overall accuracy, 18 of 25), but specifically in the riskier line-breaking passes, where he only completed 2 out of 8 attempts (25%) — quite different from the 82% overall accuracy against Haiti. In other words: Alisson did not "break" on simple passes, he just had a bad night attempting difficult passes. Even so, he remained active in defensive sweeping: 6 possession recoveries against Scotland show that he remains a security component even outside the goal.
Area dominance: Qatar's aerial differential
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 aggression uncommon in goal-line clearances. In pure volume, Qatar also leads: 35 shots faced against Canada, albeit with a low success rate (44%) given the lopsided score.
Resilience ranking (shot volume)
| Goalkeeper (Team) | Match | Shots Faced | Save Rate |
|---|---|---|---|
| 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% |
Errors that cost dearly
It wasn't all walls: Uruguay (vs Saudi Arabia) finished with only a 67% save rate, and Sweden (vs Netherlands) recorded one of the worst marks in the tournament, with only 29% efficiency in goal interventions.
📐 Real Impact Index — when work volume is considered
Gross Save% and even Quality% favor those who defend little and well. To try to capture who supported their national team under more pressure, we created a weighted index combining work volume, efficiency, and participation in playmaking:
- Save efficiency, weighted by the volume of shots faced35%
- Volume of shots faced per 90 minutes15%
- Goalkeeper interventions per 90 minutes15%
- Line breaks / distribution per 90 minutes15%
- Total involvements per 90 minutes10%
- Minutes played / availability10%
Minimum filter: 270 minutes, 3 games, 15+ attempts faced. Base: 90 games, 4,822 player-match rows, 1,250 unique players.
| # | Goalkeeper | Team | Score | Games | Min. | Attempts | Weighted Save % |
|---|---|---|---|---|---|---|---|
| 1 | Orlando Gill | Paraguay | 86.2 | 4 | 370 | 78 | 85.3% |
| 2 | Mohammed Alowais | Saudi Arabia | 77.4 | 3 | 273 | 65 | 82.0% |
| 3 | Patrick Beach | Australia | 75.5 | 4 | 392 | 65 | 85.4% |
| 4 | Vozinha | Cape Verde | 73.9 | 4 | 394 | 75 | 69.1% |
| 5 | Ronwen Williams | South Africa | 71.7 | 4 | 362 | 51 | 70.3% |
| 6 | Gregor Kobel | Switzerland | 65.5 | 4 | 360 | 33 | 89.5% |
| 7 | Mahmoud Abunada | Qatar | 64.9 | 3 | 270 | 79 | 61.1% |
| 8 | Bart Verbruggen | Netherlands | 62.9 | 4 | 384 | 48 | 75.4% |
| 9 | Raul Rangel | Mexico | 61.5 | 4 | 371 | 32 | 100.0% |
| 10 | Diogo Costa | Portugal | 61.4 | 4 | 370 | 54 | 88.5% |
⚠️ Data reconciliation note: Gill's attempts faced appear in three different numbers in this survey: 78 in the index above, 85 in the main table of the article (4 games, group stage + round of 32), and 100 if we add his 5 full matches in the World Cup, including the round of 16 against France. The difference is in the cut, not in a counting error — but since the index lists "4 games" and not "5", it is worth making this reconciliation explicit so that it does not seem that the cut was hand-picked.
⚠️ About the index itself: more than half of the final weight rewards work volume (volume + interventions + involvements per 90 = 40%, in addition to part of the 35% for "weighted efficiency"). This tends to favor goalkeepers behind more exposed defenses — which can reflect the team's playing style as much as individual quality. It does not invalidate the index, but it means that "real impact" is one lens among many, not a neutral metric superior to Quality% or the balance vs xG already calculated above.
The Conclusion: Volume Walls vs. Game Architects
If we were to choose two archetypes to symbolize the goalkeeping styles in 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 all the time: 20+ attempts per 90 minutes, almost double the tournament average. Vozinha still manages 54.3% accuracy in these risky plays; Gill sacrifices precision (37.1%) for volume, a sign of a team that pushes the ball forward forcefully, even knowing that they will lose possession frequently.
The Game Architects — and here the data gave us an interesting twist. Diogo Costa is, in fact, an example of efficiency: few line breaks (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" with the numbers in hand is Unai Simon: the lowest volume of risk among goalkeepers with 3+ full games (8.0 line breaks/90) combined with the best overall passing accuracy rate of the entire World Cup (92.5%). Simon is not the flashiest 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: high distribution volume is not synonymous with quality, and low volume is not synonymous with fear. It's a playing style — and each of these goalkeepers carries the team on their back 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 the official FIFA PMSR (Post-Match Statistical Review) reports for the 2026 World Cup, covering the group stage and round of 32, for the 48 starting goalkeepers of the 48 national teams. Quality% = (Saved and Held + Deflected and Held + Saved and Cleared) ÷ (Total shots faced − shots that did not require action). xGA per team is the actual xG for each match summed only in the full games of the starter identified via official lineup. Aerial dominance and distribution (specific sections) still only cover the 24 goalkeepers from the first batch of analysis. Data on errors/failures cross-referenced with reports from BBC Sport and Brazilian outlets (CNN Brasil, Band, Lance, Gazeta Esportiva). Data subject to updates as more matches are played.
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