Best Goalkeepers in the Serie A (Jun 2026)
Ranked by Analytical Strength Index
Market Overview: Serie A Goalkeepers 2026-27
Our database tracked 49 Serie A Goalkeepers in the 2026-27 season, representing 20 clubs with a combined market value of €243.9M. The average market value for Serie A Goalkeepers was €5.0M, with the average age at 30 years old.
The most valuable goalkeeper in the Serie A was Mile Svilar, worth €35.0M and played for AS Roma at 26 years old. The top 5 Goalkeepers averaged €25.0M in market value, including Marco Carnesecchi and Mike Maignan.
Age distribution showed the youngest tracked goalkeeper was Lorenzo Torriani (21 years, AC Milan, €500K), while the oldest was Daniele Padelli (40 years, Udinese Calcio, €150K). Research shows Goalkeepers typically peak at age 29.
Historical analysis showed 19 Goalkeepers (39%) increased in market value over the following 12 months based on age-curve trajectories, then-current performance trends, and playing time analysis. The Serie A market for Goalkeepers remained actively developing with emerging talent in the 2026-27 season.
💡 Use the search bar below to find specific players, or apply filters to narrow results by club, age range, or market value. Click the chart icon next to any player to view their historical value trajectory and forecast.
Explore Market Size by Position in Serie A
Interactive bubble chart showing predicted 2-year growth vs current age for all Serie A Goalkeepers. Identify undervalued assets and track market momentum across 20 clubs with €243.9M combined value.
Age Distribution: Serie A Goalkeepers
The Serie A GK market shows 4 distinct age segments, with the largest cohort in the 30+ bracket (24 players, 49% of market). The 27-29 age group holds the most value at €83.6M, averaging €7.0M per player.
Top Goalkeepers by Age Bracket
21-23 Years (5 players)
24-26 Years (8 players)
27-29 Years (12 players)
30+ Years (24 players)
Market Value Distribution
Elite Tier Concentration
The top 5 Goalkeepers (10% of players) control €125.0M
Market Tiers
Market structure shows distributed value with premium (€30-50m) tier representing 2% of the Serie A GK pool.
Premium (€30-50M)
High (€15-30M)
Mid (€5-15M)
Club Distribution: Serie A Goalkeepers
Among 20 Serie A clubs, AS Roma leads with 3 Goalkeepers worth €37.3M (averaging €12.4M per player). The top 10 clubs account for 61% of tracked Goalkeepers.
AS Roma (3 Goalkeepers)
SSC Napoli (3 Goalkeepers)
AC Milan (3 Goalkeepers)
Atalanta BC (2 Goalkeepers)
Player Rankings
Ranked by Analytical Strength Index. Click any player to view full profile, or click the chart icon to see value history.
Mile Svilar
AS Roma • 26 years old
€30.3M
€35.0M
+15.6%
Expected: €39.0M
86.8
Marco Carnesecchi
Atalanta BC • 25 years old
€21.6M
€25.0M
+15.6%
Expected: €26.5M
77.5
Mike Maignan
AC Milan • 30 years old
€26.4M
€25.0M
-5.4%
Expected: €22.5M
76.7
Zion Suzuki
Parma Calcio 1913 • 23 years old
€17.3M
€20.0M
+15.6%
Expected: €22.9M
74.3
Vanja Milinković-Savić
SSC Napoli • 29 years old
€17.3M
€20.0M
+15.6%
Expected: €20.6M
73.4
Michele Di Gregorio
Juventus FC • 28 years old
€15.6M
€18.0M
+15.6%
Expected: €17.6M
72.5
Alex Meret
SSC Napoli • 29 years old
€12.1M
€14.0M
+15.6%
Expected: €14.4M
68.8
Josep Martínez
Inter Milan • 28 years old
€7.8M
€9.0M
+15.6%
Expected: €8.8M
60.2
Maduka Okoye
Udinese Calcio • 26 years old
€6.9M
€8.0M
+15.6%
Expected: €8.6M
59.7
Arijanet Murić
US Sassuolo • 27 years old
€6.5M
€7.5M
+15.6%
Expected: €7.7M
58.3
Jean Butez
Como 1907 • 31 years old
€5.8M
€4.5M
-22.6%
Expected: €4.0M
51.6
David de Gea
ACF Fiorentina • 35 years old
€4.5M
€3.5M
-22.6%
Expected: €3.1M
50.1
Franco Israel
Torino FC • 26 years old
€3.3M
€3.8M
+15.6%
Expected: €4.1M
50.0
Justin Bijlow
Genoa CFC • 28 years old
€3.5M
€4.0M
+15.6%
Expected: €3.9M
49.7
Wladimiro Falcone
US Lecce • 31 years old
€4.5M
€3.5M
-22.6%
Expected: €3.1M
48.4
Adrian Semper
Pisa Sporting Club • 28 years old
€3.0M
€3.5M
+15.6%
Expected: €3.4M
48.0
Emil Audero
US Cremonese • 29 years old
€2.8M
€3.2M
+15.6%
Expected: €3.3M
46.3
Ivan Provedel
SS Lazio • 32 years old
€3.9M
€3.0M
-22.6%
Expected: €2.6M
43.5
Yann Sommer
Inter Milan • 37 years old
€3.2M
€2.5M
-22.6%
Expected: €2.2M
43.3
Stefano Turati
US Sassuolo • 24 years old
€2.6M
€3.0M
+15.6%
Expected: €3.3M
43.3
Scout Tools
Advanced analytics for scouting and recruitment decisions. Each tool provides unique insights into player value, potential, and market dynamics.
Pre-Peak Value Efficiency (PPVE)
Identifies pre-peak players offering exceptional value relative to their age bracket. Higher PPVE = better value.
Understanding Pre-Peak Value Efficiency (PPVE)
Parma Calcio 1913's Zion Suzuki at 23 years old has the highest Pre-Peak Value Efficiency at 33.33×. That means Zion Suzuki is valued 33.33× higher than the median player in the 21-23 age bracket-representing exceptional value before reaching peak age.
In second is Atalanta BC's Marco Carnesecchi, who is 25 years old, with a 8.33× PPVE. Third is Răzvan Sava of Udinese Calcio, who is 23 years old with a 4.17× PPVE.
How PPVE is calculated: PPVE compares a player's current market value to the median value of all players in their age bracket. A PPVE of 33.33× means the player is worth 3233% more than typical players their age-making them high-value targets before they reach peak value.
PPVE by Age Bracket
| Rank | Player | Age | Bracket | Current Value | Bracket Median | PPVE |
|---|---|---|---|---|---|---|
| #1 | Zion Suzuki Parma Calcio 1913 | 23 | 21-23 | €20.0M | €600K | 33.33× |
| #2 | Marco Carnesecchi Atalanta BC | 25 | 24-26 | €25.0M | €3.0M | 8.33× |
| #3 | Răzvan Sava Udinese Calcio | 23 | 21-23 | €2.5M | €600K | 4.17× |
| #4 | Stefano Turati US Sassuolo | 24 | 24-26 | €3.0M | €3.0M | 1.00× |
| #5 | Gioele Zacchi US Sassuolo | 22 | 21-23 | €600K | €600K | 1.00× |
| #6 | Lorenzo Torriani AC Milan | 21 | 21-23 | €500K | €600K | 0.83× |
| #7 | Filippo Rinaldi Parma Calcio 1913 | 23 | 21-23 | €300K | €600K | 0.50× |
| #8 | Edoardo Corvi Parma Calcio 1913 | 25 | 24-26 | €700K | €3.0M | 0.23× |
Return-to-Peak Potential (RPP)
Recovery potential from current value to forecasted peak. Shows how much upside remains for players approaching their prime.
Understanding Return-to-Peak Potential (RPP)
AC Milan's Lorenzo Torriani at 21 years old has the highest Return-to-Peak Potential at +44%. That means Lorenzo Torriani is projected to appreciate 44% as they reach their peak age in 5 years-representing significant upside before entering their prime.
In second is US Sassuolo's Gioele Zacchi, who is 22 years old, with a +40% RPP (4 years to peak). Third is Zion Suzuki of Parma Calcio 1913, who is 23 years old with a +35% RPP (3 years to peak).
How RPP is calculated: RPP compares a player's current market value to their forecasted peak value, calculating the percentage appreciation potential. A 44% RPP means the player is expected to gain 44% value as they enter their prime-making them excellent growth investments.
Recovery Potential by Player
| Rank | Player | Age | Years to Peak | Current | Peak Forecast | RPP % |
|---|---|---|---|---|---|---|
| #1 | Lorenzo Torriani AC Milan | 21 | 5 | €500K | €894K | +44% |
| #2 | Gioele Zacchi US Sassuolo | 22 | 4 | €600K | €997K | +40% |
| #3 | Zion Suzuki Parma Calcio 1913 | 23 | 3 | €20.0M | €30.9M | +35% |
| #4 | Răzvan Sava Udinese Calcio | 23 | 3 | €2.5M | €3.9M | +35% |
| #5 | Filippo Rinaldi Parma Calcio 1913 | 23 | 3 | €300K | €464K | +35% |
| #6 | Stefano Turati US Sassuolo | 24 | 2 | €3.0M | €4.3M | +30% |
| #7 | Edoardo Corvi Parma Calcio 1913 | 25 | 1 | €700K | €936K | +25% |
| #8 | Marco Carnesecchi Atalanta BC | 25 | 1 | €25.0M | €33.4M | +25% |
Risk-Adjusted Upside (RAU)
Upside potential weighted against forecast uncertainty. Higher RAU = better risk-reward profile.
Understanding Risk-Adjusted Upside (RAU)
AC Milan's Lorenzo Torriani has the highest Risk-Adjusted Upside at 103.3. That means Lorenzo Torriani has 23% upside potential with only 0% forecast uncertainty-representing excellent risk-reward for value appreciation.
In second is US Sassuolo's Gioele Zacchi with a 100.1 RAU (19% upside, 0% uncertainty). Third is Filippo Rinaldi of Parma Calcio 1913 with a 79.9 RAU (15% upside, 0% uncertainty).
How RAU is calculated: RAU divides upside potential by forecast uncertainty (RAU = Upside % ÷ Uncertainty %). A RAU of 103.3 means the upside is 103.3× greater than the uncertainty-making it a high-confidence growth opportunity. Target RAU ≥2.0 for balanced risk-reward.
Risk-Adjusted Upside by Player
| Rank | Player | Expected | Range | Upside % | RAU |
|---|---|---|---|---|---|
| #1 | Lorenzo Torriani AC Milan | €617K | €561K-674K | +23% | 103.3 |
| #2 | Gioele Zacchi US Sassuolo | €714K | €657K-772K | +19% | 100.1 |
| #3 | Filippo Rinaldi Parma Calcio 1913 | €344K | €316K-371K | +15% | 79.9 |
| #4 | Zion Suzuki Parma Calcio 1913 | €22.9M | €21.1M-24.8M | +15% | 79.9 |
| #5 | Răzvan Sava Udinese Calcio | €2.9M | €2.6M-3.1M | +15% | 79.9 |
| #6 | Mile Svilar AS Roma | €39.0M | €35.9M-42.1M | +11% | 64.1 |
| #7 | Stefano Turati US Sassuolo | €3.3M | €3.0M-3.6M | +10% | 58.1 |
| #8 | Christian Früchtl US Lecce | €1.1M | €985K-1.2M | +7% | 41.2 |
| #9 | Maduka Okoye Udinese Calcio | €8.6M | €7.9M-9.3M | +7% | 41.2 |
| #10 | Federico Ravaglia Bologna FC 1909 | €2.1M | €2.0M-2.3M | +7% | 41.2 |
| #11 | Franco Israel Torino FC | €4.1M | €3.7M-4.4M | +7% | 41.2 |
| #12 | Marco Carnesecchi Atalanta BC | €26.5M | €24.3M-28.6M | +6% | 34.5 |
| #13 | Edoardo Corvi Parma Calcio 1913 | €741K | €682K-800K | +6% | 34.5 |
| #14 | Vanja Milinković-Savić SSC Napoli | €20.6M | €18.9M-22.2M | +3% | 18.0 |
| #15 | Alex Meret SSC Napoli | €14.4M | €13.3M-15.6M | +3% | 18.0 |
| #16 | Emil Audero US Cremonese | €3.3M | €3.0M-3.6M | +3% | 18.0 |
| #17 | Giacomo Satalino US Sassuolo | €410K | €377K-442K | +2% | 14.7 |
| #18 | Arijanet Murić US Sassuolo | €7.7M | €7.1M-8.3M | +2% | 14.7 |
| #19 | Oliver Christensen ACF Fiorentina | €1.5M | €1.4M-1.7M | +2% | 14.7 |
Roster Pressure Index (RPI)
Squad depth pressure based on Z-score distribution. Negative RPI = thin depth, positive = deep roster.
What This Shows
Z-Score explained: Measures how many standard deviations a player's strength is from the position average. Z-Score = 0 means average, +1.0 is one standard deviation above average, -1.0 is below average.
How to use: RPI < -1.0 indicates critical depth shortage. These positions need immediate reinforcement. RPI > +1.0 suggests strong depth, allowing selective, high-value additions only.
Current market: goalkeeper position shows weak depth (avg Z-score: -0.00). RPI: -0.00.
Position Depth Analysis
Highest Z-Scores
Lowest Z-Scores
Age-Share Concentration (ASC)
Identifies players capturing disproportionate value relative to age group representation. Positive ASC = value concentration.
Understanding Age-Share Concentration (ASC)
Juventus FC's Mattia Perin in the 30+ age bracket has the highest Age-Share Concentration at +-25.3%. That means Mike Maignan captures 23.7% of total market value while representing only 49.0% of players in their age group-showing dominant elite status.
In second is Genoa CFC's Benjamin Siegrist with a +-25.3% ASC (23.7% value share vs 49.0% player share in 30+ bracket). Third is Luca Lezzerini of ACF Fiorentina with a +-25.3% ASC (23.7% value vs 49.0% players in 30+ bracket).
How ASC is calculated: ASC = (% of total value) - (% of total players) in age bracket. A +-25.3% ASC means the player captures -25.3% more market value than their numerical representation-indicating marquee status. ASC > +15% = elite dominance, ASC < -15% = potential value targets.
Value Concentration by Player
| Rank | Player | Age Bracket | Value Share | Player Share | ASC |
|---|---|---|---|---|---|
| #1 | Mattia Perin Juventus FC | 30+ | 23.7% | 49.0% | -25.3% |
| #2 | Benjamin Siegrist Genoa CFC | 30+ | 23.7% | 49.0% | -25.3% |
| #3 | Luca Lezzerini ACF Fiorentina | 30+ | 23.7% | 49.0% | -25.3% |
| #4 | Nicola Leali Genoa CFC | 30+ | 23.7% | 49.0% | -25.3% |
| #5 | Alberto Paleari Torino FC | 30+ | 23.7% | 49.0% | -25.3% |
| #6 | Mike Maignan AC Milan | 30+ | 23.7% | 49.0% | -25.3% |
| #7 | Ivan Provedel SS Lazio | 30+ | 23.7% | 49.0% | -25.3% |
| #8 | Marco Sportiello Atalanta BC | 30+ | 23.7% | 49.0% | -25.3% |
| #9 | Wladimiro Falcone US Lecce | 30+ | 23.7% | 49.0% | -25.3% |
| #10 | Simone Scuffet Pisa Sporting Club | 30+ | 23.7% | 49.0% | -25.3% |
| #11 | Simone Perilli Hellas Verona | 30+ | 23.7% | 49.0% | -25.3% |
| #12 | Lorenzo Montipò Hellas Verona | 30+ | 23.7% | 49.0% | -25.3% |
| #13 | Pierluigi Gollini AS Roma | 30+ | 23.7% | 49.0% | -25.3% |
| #14 | Nikita Contini SSC Napoli | 30+ | 23.7% | 49.0% | -25.3% |
| #15 | Daniele Padelli Udinese Calcio | 30+ | 23.7% | 49.0% | -25.3% |
| #16 | Jean Butez Como 1907 | 30+ | 23.7% | 49.0% | -25.3% |
| #17 | Yann Sommer Inter Milan | 30+ | 23.7% | 49.0% | -25.3% |
| #18 | David de Gea ACF Fiorentina | 30+ | 23.7% | 49.0% | -25.3% |
| #19 | Raffaele Di Gennaro Inter Milan | 30+ | 23.7% | 49.0% | -25.3% |
| #20 | Carlo Pinsoglio Juventus FC | 30+ | 23.7% | 49.0% | -25.3% |
Buy-Now vs Wait-List Map
Categorizes players by age position and upside potential to guide timing of acquisition.
What This Shows
How to use:"Buy Now - High Upside" = immediate priority targets."Watch List" = monitor for 6-12 months."Peak" = pay premium for proven performers."Aging" = short-term depth only.
Current market: 2 immediate targets, 6 standard acquisitions, 0 watch-list prospects, 14 at peak.
BUY NOW - High Upside
WATCH LIST - High Upside
No players in this category
BUY NOW - Medium Upside
PEAK Players
Price vs Peer Z-Score
IQR-based pricing analysis relative to position peers. Identifies over/undervalued players vs market.
What This Shows
How to use: Z-score < -1.5 = significantly undervalued (potential bargain). Z-score > +1.5 = premium pricing (requires strong justification). Within ±1.0 = fair market value.
Current market: Position median is €800K. 0 undervalued, 1 premium.
Value Positioning vs Peers
| Player | Market Value | Position Median | Z-Score | Assessment |
|---|---|---|---|---|
Michele Di Gregorio Juventus FC | €18.0M | €2.0M | -1.00 | Good Value |
Edoardo Corvi Parma Calcio 1913 | €700K | €2.0M | -0.65 | Good Value |
Christian Früchtl US Lecce | €1.0M | €2.0M | -0.50 | Fair Value |
Giacomo Satalino US Sassuolo | €400K | €2.0M | -0.44 | Fair Value |
Daniele Padelli Udinese Calcio | €150K | €2.0M | -0.40 | Fair Value |
Mauro Vigorito Como 1907 | €150K | €2.0M | -0.40 | Fair Value |
Carlo Pinsoglio Juventus FC | €200K | €2.0M | -0.38 | Fair Value |
Raffaele Di Gennaro Inter Milan | €300K | €2.0M | -0.33 | Fair Value |
Luca Lezzerini ACF Fiorentina | €350K | €2.0M | -0.31 | Fair Value |
Simone Perilli Hellas Verona | €400K | €2.0M | -0.29 | Fair Value |
Nikita Contini SSC Napoli | €400K | €2.0M | -0.29 | Fair Value |
Marco Silvestri US Cremonese | €500K | €2.0M | -0.24 | Fair Value |
Arijanet Murić US Sassuolo | €7.5M | €2.0M | -0.23 | Fair Value |
Alen Sherri Cagliari Calcio | €1.0M | €2.0M | -0.20 | Fair Value |
Benjamin Siegrist Genoa CFC | €600K | €2.0M | -0.19 | Fair Value |
Filippo Rinaldi Parma Calcio 1913 | €300K | €2.0M | -0.15 | Fair Value |
Pierluigi Gollini AS Roma | €800K | €2.0M | -0.10 | Fair Value |
Lorenzo Torriani AC Milan | €500K | €2.0M | -0.05 | Fair Value |
Alberto Paleari Torino FC | €1.0M | €2.0M | 0.00 | Fair Value |
Mike Maignan AC Milan | €25.0M | €2.0M | 0.00 | Fair Value |
How We Rank Serie A Goalkeepers
Our Analytical Strength Index is calibrated specifically for goalkeepers, using position-specific age curves and playing time benchmarks. The model draws from academic research on player valuation (Franck & Nüesch, 2012) and age-performance curves (Dendir, 2016).
Scoring Components for GK
Historical Achievement Index (35%)
Peak career market value for Serie A goalkeepers, reflecting proven track record and reputation. Uses log-scale to account for exponential value distribution at elite level.
Current Performance Proxy (30%)
Present market value for Serie A goalkeepers, capturing recent form, injuries, and current performance level. Weighted to reflect age-related depreciation patterns.
Playing Time Utilization (18%)
Goalkeepers with 2,700+ minutes score highest, indicating regular starting role and sustained performance.
Age-Adjusted Performance Curve (12%)
Goalkeepers peak at 29 with gradual 3.5%/year decline. Pre-peak players score higher on development trajectory.
Competition Level Adjustment (3%)
Serie A receives Top 5 European league premium for competitive intensity and quality of opposition.
Performance Expectations Multiplier (2%)
Players at clubs with Champions League pedigree face higher performance standards and tactical complexity, contributing to development and market validation.
GK Performance Benchmarks
Peak Age: 29 years (latest of all positions due to experience premium)
Decline Rate: 3.5% per year (slowest decline, experience compensates for reflexes)
Optimal Minutes: 2,700 per season (near-complete games for #1 goalkeeper)
1-Year Market Value Forecast
Probabilistic model combining age-curve depreciation, value momentum, and playing time factors:
• Age Factor: GK-specific -3.5%/year post-peak, +5%/year pre-peak
• Value Trajectory: Near career peak (>95% of peak value): +3% momentum | Moderate decline: -5%
• Playing Time Factor: Regular starters (+2%), Squad rotation (-2%)
• Forecast Range: ±8% confidence interval (most stable)
Research Foundation
• Dendir (2016): Age-performance curves for goalkeepers
• Carmichael et al. (2011): Player depreciation in top leagues
• Franck & Nüesch (2012): Hedonic pricing models for talent valuation
• Szymanski, S. (2015). Money and Soccer: A Soccernomics Guide
Frequently Asked Questions
Common questions about Serie A Goalkeepers in the 2026-27 season
Who are the most valuable Goalkeepers in the Serie A in 2026-27?
The most valuable goalkeeper in the Serie A in 2026-27 is Mile Svilar, who is worth €35.0M and plays for AS Roma. The second most valuable is Marco Carnesecchi (€25.0M, Atalanta BC), followed by Mike Maignan (€25.0M, AC Milan). Our database tracks 49 Serie A Goalkeepers with comprehensive market valuations updated for the 2026-27 season.
How are Serie A Goalkeepers ranked?
Serie A Goalkeepers are ranked by our proprietary Analytical Strength Index, which is specifically calibrated for Goalkeepers. The score combines six factors: Historical Achievement Index (35%) measuring peak career value, Current Performance Proxy (30%) reflecting recent market signals, Playing Time Utilization (18%) tracking minutes played, Age-Adjusted Performance Curve (12%) using position-specific peak ages, League Quality Coefficient (3%) for Serie A competition level, and Club Tier Multiplier (2%) accounting for club prestige. This methodology is grounded in academic research including work by Dendir (2016) on age-performance curves and Franck & Nüesch (2012) on hedonic pricing models.
What age do Goalkeepers peak?
Goalkeepers typically peak at age 29, later than outfield players, with a slower decline rate of 3.5% per year after peak. This is supported by research from Dendir (2016) showing that goalkeepers maintain elite performance longer due to the position's reliance on positioning, decision-making, and experience rather than pure athleticism. The optimal playing time for peak performance is around 2,700 minutes per season.
How much does it cost to sign a top goalkeeper from the Serie A?
Transfer fees for Serie A Goalkeepers vary significantly based on market value, contract length, and club bargaining position. For the top-ranked goalkeeper Mile Svilar (market value: €35.0M), estimated transfer fees would range from €28.0M to €49.0M depending on contract situation. Players with longer contracts (3+ years) command premium fees (1.2-1.4× market value), while those in the final year may be available for 0.8-1.1× market value. Our fee estimates are derived from historical transfer patterns and contract-clock modifiers validated against actual Serie A transactions.
What is the value forecast for Serie A Goalkeepers?
Our 1-year forecast model projects market value changes for Serie A Goalkeepers based on age-curve depreciation, historical trajectory, and playing time adjustments. The forecast combines three factors: age-based appreciation/depreciation (pre-peak players gain ~5% per year toward peak age, post-peak players decline at position-specific rates), market trajectory momentum (comparing current to peak value), and playing time confidence (regular starters receive +2% boost). Forecast confidence intervals account for position-specific volatility-goalkeepers have ±8% volatility (most stable). Young players (under 22) and older players (over 32) receive 1.15× uncertainty multipliers due to unpredictable development or decline patterns.
Where does the Serie A goalkeeper data come from?
Our Serie A goalkeeper data is sourced from Football Analytics AI's proprietary Transfer Intelligence Database, which aggregates market valuations, player statistics, contract information, and transfer histories from multiple industry sources. Market values are updated regularly based on player performance, injuries, contract negotiations, and transfer market activity. We enhance this data with our proprietary analytics including position-specific scoring algorithms, age-performance curves calibrated to academic research, and statistical forecast models. All data is validated against official Serie A sources and updated monthly for the 2026-27 season to ensure accuracy for recruitment and investment decisions.