Best Players (All Positions) in the Serie A (Oct 2025)
Ranked by Analytical Strength Score
Market Overview: Serie A Players (All Positions) 2024-25
Our database tracked 531 Serie A Players (All Positions) in the 2024-25 season, representing 22 clubs with a combined market value of €5.3B. The average market value for Serie A Players (All Positions) was €9.9M, with the average age at 26.5 years old.
The most valuable player in the Serie A was Alessandro Bastoni, worth €80.0M and played for Inter Milan at 26 years old. The top 5 Players (All Positions) averaged €75.0M in market value, including Lautaro Martínez and Rafael Leão.
Age distribution showed the youngest tracked player was Jeff Ekhator (18 years, Genoa CFC, €7.0M), while the oldest was Luka Modrić (40 years, AC Milan, €4.0M). Research shows Players (All Positions) typically peak at age 26-27.
Historical analysis showed 311 Players (All Positions) (59%) 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 Players (All Positions) remained highly competitive with significant transfer activity in the 2024-25 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 Players (All Positions). Identify undervalued assets and track market momentum across 22 clubs with €5.3B combined value.
Age Distribution: Serie A Players (All Positions)
The Serie A ALL market shows 5 distinct age segments, with the largest cohort in the 24-26 bracket (152 players, 29% of market). The 24-26 age group holds the most value at €2.1B, averaging €13.6M per player.
Top Players (All Positions) by Age Bracket
U21 Years (34 players)
21-23 Years (111 players)
24-26 Years (152 players)
27-29 Years (108 players)
Market Value Distribution
Elite Tier Concentration
The top 54 Players (All Positions) (10% of players) control €2.1B
Market Tiers
Market structure shows distributed value with elite (€50m+) tier representing 3% of the Serie A ALL pool.
Elite (€50M+)
Premium (€30-50M)
High (€15-30M)
Club Distribution: Serie A Players (All Positions)
Among 22 Serie A clubs, Inter Milan leads with 23 Players (All Positions) worth €643.8M (averaging €28.0M per player). The top 10 clubs account for 48% of tracked Players (All Positions).
Inter Milan (23 Players (All Positions))
Juventus FC (26 Players (All Positions))
SSC Napoli (27 Players (All Positions))
AC Milan (22 Players (All Positions))
Player Rankings
Ranked by APE Strength Score. Click any player to view full profile, or click the chart icon to see value history.
Alessandro Bastoni
Inter Milan • 26 years old
€69.2M
€80.0M
+15.6%
Expected: €85.7M
93.2
Lautaro Martínez
Inter Milan • 28 years old
€85.0M
€85.0M
+0.0%
Expected: €83.9M
92.2
Rafael Leão
AC Milan • 26 years old
€60.5M
€70.0M
+15.6%
Expected: €75.0M
91.8
Marcus Thuram
Inter Milan • 28 years old
€75.0M
€75.0M
+0.0%
Expected: €74.1M
91.2
Nicolò Barella
Inter Milan • 28 years old
€65.0M
€65.0M
+0.0%
Expected: €64.2M
89.4
Kenan Yıldız
Juventus FC • 20 years old
€64.9M
€75.0M
+15.6%
Expected: €102.4M
89.4
Christian Pulisic
AC Milan • 27 years old
€60.0M
€60.0M
+0.0%
Expected: €59.3M
89.2
Moise Kean
ACF Fiorentina • 25 years old
€43.2M
€50.0M
+15.6%
Expected: €55.2M
87.6
Alessandro Buongiorno
SSC Napoli • 26 years old
€43.2M
€50.0M
+15.6%
Expected: €53.6M
87.6
Manu Koné
AS Roma • 24 years old
€43.2M
€50.0M
+15.6%
Expected: €57.8M
87.6
Federico Dimarco
Inter Milan • 27 years old
€50.0M
€50.0M
+0.0%
Expected: €49.4M
86.9
Jonathan David
Juventus FC • 25 years old
€38.9M
€45.0M
+15.6%
Expected: €49.6M
86.3
Éderson
Atalanta BC • 26 years old
€38.9M
€45.0M
+15.6%
Expected: €48.2M
86.3
Loïs Openda
Juventus FC • 25 years old
€38.9M
€45.0M
+15.6%
Expected: €49.6M
86.3
Bremer
Juventus FC • 28 years old
€50.0M
€50.0M
+0.0%
Expected: €49.4M
86.2
Scott McTominay
SSC Napoli • 28 years old
€50.0M
€50.0M
+0.0%
Expected: €49.4M
86.2
Nico Paz
Como 1907 • 21 years old
€47.6M
€55.0M
+15.6%
Expected: €72.2M
85.7
Rasmus Højlund
SSC Napoli • 22 years old
€38.9M
€45.0M
+15.6%
Expected: €56.7M
85.2
Khéphren Thuram
Juventus FC • 24 years old
€34.6M
€40.0M
+15.6%
Expected: €46.2M
84.8
Ademola Lookman
Atalanta BC • 27 years old
€40.0M
€40.0M
+0.0%
Expected: €39.5M
84.1
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)
Juventus FC's Kenan Yıldız at 20 years old has the highest Pre-Peak Value Efficiency at 16.67×. That means Kenan Yıldız is valued 16.67× higher than the median player in the U21 age bracket—representing exceptional value before reaching peak age.
In second is Como 1907's Nico Paz, who is 21 years old, with a 9.17× PPVE. Third is Rasmus Højlund of SSC Napoli, who is 22 years old with a 7.50× 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 16.67× means the player is worth 1567% 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 | Kenan Yıldız Juventus FC | 20 | U21 | €75.0M | €4.5M | 16.67× |
| #2 | Nico Paz Como 1907 | 21 | 21-23 | €55.0M | €6.0M | 9.17× |
| #3 | Rasmus Højlund SSC Napoli | 22 | 21-23 | €45.0M | €6.0M | 7.50× |
| #4 | Assane Diao Como 1907 | 20 | U21 | €30.0M | €4.5M | 6.67× |
| #5 | Jesús Rodríguez Como 1907 | 19 | U21 | €30.0M | €4.5M | 6.67× |
| #6 | Moise Kean ACF Fiorentina | 25 | 24-26 | €50.0M | €8.0M | 6.25× |
| #7 | Manu Koné AS Roma | 24 | 24-26 | €50.0M | €8.0M | 6.25× |
| #8 | Giorgio Scalvini Atalanta BC | 21 | 21-23 | €35.0M | €6.0M | 5.83× |
| #9 | Matías Soulé AS Roma | 22 | 21-23 | €35.0M | €6.0M | 5.83× |
| #10 | Santiago Castro Bologna FC 1909 | 21 | 21-23 | €35.0M | €6.0M | 5.83× |
| #11 | Loïs Openda Juventus FC | 25 | 24-26 | €45.0M | €8.0M | 5.63× |
| #12 | Jonathan David Juventus FC | 25 | 24-26 | €45.0M | €8.0M | 5.63× |
| #13 | Evan Ferguson AS Roma | 20 | U21 | €25.0M | €4.5M | 5.56× |
| #14 | Pietro Comuzzo ACF Fiorentina | 20 | U21 | €25.0M | €4.5M | 5.56× |
| #15 | Ardon Jashari AC Milan | 23 | 21-23 | €32.0M | €6.0M | 5.33× |
| #16 | Khéphren Thuram Juventus FC | 24 | 24-26 | €40.0M | €8.0M | 5.00× |
| #17 | Francisco Conceição Juventus FC | 22 | 21-23 | €30.0M | €6.0M | 5.00× |
| #18 | Nicolò Rovella SS Lazio | 23 | 21-23 | €30.0M | €6.0M | 5.00× |
| #19 | Dušan Vlahović Juventus FC | 25 | 24-26 | €35.0M | €8.0M | 4.38× |
| #20 | Charles De Ketelaere Atalanta BC | 24 | 24-26 | €35.0M | €8.0M | 4.38× |
Return-to-Peak Potential (RPP)
Recovery potential from current value to forecasted peak. Shows how much upside remains for players approaching their prime.
No RPP data available (requires forecast values in database)
Risk-Adjusted Upside (RAU)
Upside potential weighted against forecast uncertainty. Higher RAU = better risk-reward profile.
Understanding Risk-Adjusted Upside (RAU)
ACF Fiorentina's Tommaso Martinelli has the highest Risk-Adjusted Upside at 184.5. That means Tommaso Martinelli has 51% upside potential with only 0% forecast uncertainty—representing excellent risk-reward for value appreciation.
In second is AC Milan's Lorenzo Torriani with a 172.2 RAU (46% upside, 0% uncertainty). Third is Filippo Rinaldi of Parma Calcio 1913 with a 166.3 RAU (36% upside, 0% uncertainty).
How RAU is calculated: RAU divides upside potential by forecast uncertainty (RAU = Upside % ÷ Uncertainty %). A RAU of 184.5 means the upside is 184.5× 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 | Tommaso Martinelli ACF Fiorentina | €2.7M | €2.5M-3.0M | +51% | 184.5 |
| #2 | Lorenzo Torriani AC Milan | €732K | €664K-799K | +46% | 172.2 |
| #3 | Filippo Rinaldi Parma Calcio 1913 | €443K | €407K-478K | +36% | 166.3 |
| #4 | Gioele Zacchi US Sassuolo | €818K | €752K-883K | +36% | 166.3 |
| #5 | Zion Suzuki Parma Calcio 1913 | €26.2M | €24.1M-28.3M | +31% | 148.7 |
| #6 | Răzvan Sava Udinese Calcio | €3.3M | €3.0M-3.5M | +31% | 148.7 |
| #7 | Stefano Turati US Sassuolo | €5.7M | €5.2M-6.1M | +26% | 129.7 |
| #8 | Edoardo Corvi Parma Calcio 1913 | €442K | €406K-477K | +26% | 129.7 |
| #9 | Elia Caprile Cagliari Calcio | €13.9M | €12.8M-15.0M | +26% | 129.7 |
| #10 | Christos Mandas SS Lazio | €8.8M | €8.1M-9.5M | +26% | 129.7 |
| #11 | Franco Israel Torino FC | €6.1M | €5.6M-6.5M | +21% | 109.0 |
| #12 | Federico Ravaglia Bologna FC 1909 | €1.8M | €1.7M-2.0M | +21% | 109.0 |
| #13 | Marco Carnesecchi Atalanta BC | €30.3M | €27.9M-32.7M | +21% | 109.0 |
| #14 | Christian Früchtl US Lecce | €1.6M | €1.4M-1.7M | +21% | 109.0 |
| #15 | Mihai Popa Torino FC | €787K | €724K-850K | +21% | 109.0 |
| #16 | Jeff Ekhator Genoa CFC | €9.9M | €8.5M-11.3M | +41% | 105.9 |
| #17 | Buba Sangaré AS Roma | €1.4M | €1.2M-1.6M | +41% | 105.9 |
| #18 | Kenan Yıldız Juventus FC | €102.4M | €88.3M-116.6M | +37% | 97.0 |
| #19 | Luca Lipani US Sassuolo | €6.1M | €5.3M-7.0M | +36% | 96.4 |
| #20 | Davide Bartesaghi AC Milan | €4.1M | €3.5M-4.7M | +36% | 96.4 |
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: player 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)
Bologna FC 1909's Ciro Immobile in the 30+ age bracket has the highest Age-Share Concentration at +-14.1%. That means Mike Maignan captures 9.6% of total market value while representing only 23.7% of players in their age group—showing dominant elite status.
In second is Juventus FC's Mattia Perin with a +-14.1% ASC (9.6% value share vs 23.7% player share in 30+ bracket). Third is Stefan de Vrij of Inter Milan with a +-14.1% ASC (9.6% value vs 23.7% players in 30+ bracket).
How ASC is calculated: ASC = (% of total value) - (% of total players) in age bracket. A +-14.1% ASC means the player captures -14.1% 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 | Ciro Immobile Bologna FC 1909 | 30+ | 9.6% | 23.7% | -14.1% |
| #2 | Mattia Perin Juventus FC | 30+ | 9.6% | 23.7% | -14.1% |
| #3 | Stefan de Vrij Inter Milan | 30+ | 9.6% | 23.7% | -14.1% |
| #4 | Benjamin Siegrist Genoa CFC | 30+ | 9.6% | 23.7% | -14.1% |
| #5 | Leonardo Spinazzola SSC Napoli | 30+ | 9.6% | 23.7% | -14.1% |
| #6 | Juan Jesus SSC Napoli | 30+ | 9.6% | 23.7% | -14.1% |
| #7 | Cristiano Biraghi Torino FC | 30+ | 9.6% | 23.7% | -14.1% |
| #8 | Hakan Çalhanoğlu Inter Milan | 30+ | 9.6% | 23.7% | -14.1% |
| #9 | Patric SS Lazio | 30+ | 9.6% | 23.7% | -14.1% |
| #10 | Álvaro Morata Como 1907 | 30+ | 9.6% | 23.7% | -14.1% |
| #11 | Simone Verdi Como 1907 | 30+ | 9.6% | 23.7% | -14.1% |
| #12 | Alessandro Florenzi AC Milan | 30+ | 9.6% | 23.7% | -14.1% |
| #13 | Francesco Acerbi Inter Milan | 30+ | 9.6% | 23.7% | -14.1% |
| #14 | Marten de Roon Atalanta BC | 30+ | 9.6% | 23.7% | -14.1% |
| #15 | Luca Lezzerini ACF Fiorentina | 30+ | 9.6% | 23.7% | -14.1% |
| #16 | Nicola Leali Genoa CFC | 30+ | 9.6% | 23.7% | -14.1% |
| #17 | Charalampos Lykogiannis Bologna FC 1909 | 30+ | 9.6% | 23.7% | -14.1% |
| #18 | Matías Vecino SS Lazio | 30+ | 9.6% | 23.7% | -14.1% |
| #19 | Remo Freuler Bologna FC 1909 | 30+ | 9.6% | 23.7% | -14.1% |
| #20 | Nicolae Stanciu Genoa CFC | 30+ | 9.6% | 23.7% | -14.1% |
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: 161 immediate targets, 85 standard acquisitions, 0 watch-list prospects, 127 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 €1.3M. 0 undervalued, 8 premium.
Value Positioning vs Peers
| Player | Market Value | Position Median | Z-Score | Assessment |
|---|---|---|---|---|
Romelu Lukaku SSC Napoli | €15.0M | €5.0M | -1.40 | Good Value |
André Anderson Without Club | €150K | €5.0M | -1.37 | Good Value |
Dimitrije Kamenovic SS Lazio | €300K | €5.0M | -1.27 | Good Value |
Edoardo Corvi Parma Calcio 1913 | €350K | €5.0M | -1.23 | Good Value |
Giacomo Satalino US Sassuolo | €400K | €5.0M | -1.20 | Good Value |
David Odogu AC Milan | €5.0M | €5.0M | -1.17 | Good Value |
Marco Sala Como 1907 | €500K | €5.0M | -1.13 | Good Value |
Kevin Bonifazi Bologna FC 1909 | €300K | €5.0M | -1.12 | Good Value |
Nikita Contini SSC Napoli | €400K | €5.0M | -1.06 | Good Value |
Mihai Popa Torino FC | €650K | €5.0M | -1.03 | Good Value |
Manuel Locatelli Juventus FC | €30.0M | €5.0M | -1.00 | Good Value |
Adam Buksa Udinese Calcio | €5.0M | €5.0M | -1.00 | Good Value |
Teun Koopmeiners Juventus FC | €30.0M | €5.0M | -1.00 | Good Value |
Mitchel Bakker Atalanta BC | €5.0M | €5.0M | -1.00 | Good Value |
Alessandro Zanoli Udinese Calcio | €5.0M | €5.0M | -1.00 | Good Value |
Francisco Conceição Juventus FC | €30.0M | €5.0M | -1.00 | Good Value |
Franco Israel Torino FC | €5.0M | €5.0M | -1.00 | Good Value |
Nicolò Rovella SS Lazio | €30.0M | €5.0M | -1.00 | Good Value |
Fabiano Parisi ACF Fiorentina | €5.0M | €5.0M | -1.00 | Good Value |
Nikola Stulic US Lecce | €5.0M | €5.0M | -1.00 | Good Value |