Best Players (All Positions) in the Serie A (Dec 2025)
Ranked by Analytical Strength Score
Market Overview: Serie A Players (All Positions) 2025-26
Our database tracks 531 Serie A Players (All Positions) in the 2025-26 season, representing 22 clubs with a combined market value of €5.3B. The average market value for Serie A Players (All Positions) is €9.9M, with the average age at 26.6 years old.
The most valuable player in the Serie A is Lautaro Martínez, worth €85.0M and playing for Inter Milan at 28 years old. The top 5 Players (All Positions) average €77.0M in market value, including Alessandro Bastoni and Marcus Thuram.
Age distribution shows the youngest tracked player is Buba Sangaré (18 years, AS Roma, €1.0M), while the oldest is Luka Modrić (40 years, AC Milan, €4.0M). Research shows Players (All Positions) typically peak at age 26-27.
Our 1-year forecast model projects 257 Players (All Positions) (48%) will increase in market value over the next 12 months based on age-curve trajectories, current performance trends, and playing time analysis. The Serie A market for Players (All Positions) remains highly competitive with significant transfer activity expected in the 2025-26 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 €2.0B, averaging €13.3M per player.
Top Players (All Positions) by Age Bracket
U21 Years (32 players)
21-23 Years (107 players)
24-26 Years (152 players)
27-29 Years (111 players)
Market Value Distribution
Elite Tier Concentration
The top 54 Players (All Positions) (10% of players) control €2.2B
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.
Lautaro Martínez
Inter Milan • 28 years old
€109.8M
€85.0M
-22.6%
Expected: €77.4M
93.8
Alessandro Bastoni
Inter Milan • 26 years old
€69.2M
€80.0M
+15.6%
Expected: €85.7M
93.2
Marcus Thuram
Inter Milan • 28 years old
€96.8M
€75.0M
-22.6%
Expected: €68.3M
92.9
Kenan Yıldız
Juventus FC • 20 years old
€64.9M
€75.0M
+15.6%
Expected: €89.5M
91.9
Rafael Leão
AC Milan • 26 years old
€60.5M
€70.0M
+15.6%
Expected: €75.0M
91.8
Nicolò Barella
Inter Milan • 28 years old
€83.9M
€65.0M
-22.6%
Expected: €59.2M
91.1
Christian Pulisic
AC Milan • 27 years old
€63.4M
€60.0M
-5.4%
Expected: €54.7M
90.0
Manu Koné
AS Roma • 24 years old
€43.2M
€50.0M
+15.6%
Expected: €53.3M
88.6
Moise Kean
ACF Fiorentina • 25 years old
€43.2M
€50.0M
+15.6%
Expected: €50.9M
88.1
Nico Paz
Como 1907 • 21 years old
€47.6M
€55.0M
+15.6%
Expected: €63.1M
88.0
Scott McTominay
SSC Napoli • 29 years old
€64.6M
€50.0M
-22.6%
Expected: €43.1M
87.9
Bremer
Juventus FC • 28 years old
€64.6M
€50.0M
-22.6%
Expected: €45.5M
87.8
Federico Dimarco
Inter Milan • 28 years old
€64.6M
€50.0M
-22.6%
Expected: €45.5M
87.8
Alessandro Buongiorno
SSC Napoli • 26 years old
€43.2M
€50.0M
+15.6%
Expected: €53.6M
87.6
Rasmus Højlund
SSC Napoli • 22 years old
€38.9M
€45.0M
+15.6%
Expected: €49.6M
87.1
Jonathan David
Juventus FC • 25 years old
€38.9M
€45.0M
+15.6%
Expected: €45.8M
86.8
Loïs Openda
Juventus FC • 25 years old
€38.9M
€45.0M
+15.6%
Expected: €45.8M
86.8
Éderson
Atalanta BC • 26 years old
€38.9M
€45.0M
+15.6%
Expected: €48.2M
86.3
Khéphren Thuram
Juventus FC • 24 years old
€34.6M
€40.0M
+15.6%
Expected: €42.6M
85.8
Ademola Lookman
Atalanta BC • 28 years old
€51.7M
€40.0M
-22.6%
Expected: €36.4M
85.1
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 | 20 | 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 | 22 | 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 | Pietro Comuzzo ACF Fiorentina | 20 | U21 | €25.0M | €4.5M | 5.56× |
| #14 | Ardon Jashari AC Milan | 23 | 21-23 | €32.0M | €6.0M | 5.33× |
| #15 | Khéphren Thuram Juventus FC | 24 | 24-26 | €40.0M | €8.0M | 5.00× |
| #16 | Francisco Conceição Juventus FC | 22 | 21-23 | €30.0M | €6.0M | 5.00× |
| #17 | Dušan Vlahović Juventus FC | 25 | 24-26 | €35.0M | €8.0M | 4.38× |
| #18 | Charles De Ketelaere Atalanta BC | 24 | 24-26 | €35.0M | €8.0M | 4.38× |
| #19 | Yann Bisseck Inter Milan | 25 | 24-26 | €35.0M | €8.0M | 4.38× |
| #20 | Andrea Cambiaso Juventus FC | 25 | 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.
Understanding Return-to-Peak Potential (RPP)
ACF Fiorentina's Tommaso Martinelli at 19 years old has the highest Return-to-Peak Potential at +52%. That means Tommaso Martinelli is projected to appreciate 52% as they reach their peak age in 7 years—representing significant upside before entering their prime.
In second is AC Milan's Lorenzo Torriani, who is 20 years old, with a +48% RPP (6 years to peak). Third is Buba Sangaré of AS Roma, who is 18 years old with a +44% RPP (8 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 52% RPP means the player is expected to gain 52% 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 | Tommaso Martinelli ACF Fiorentina | 19 | 7 | €1.8M | €3.7M | +52% |
| #2 | Lorenzo Torriani AC Milan | 20 | 6 | €500K | €961K | +48% |
| #3 | Buba Sangaré AS Roma | 18 | 8 | €1.0M | €1.8M | +44% |
| #4 | Lorran Pisa Sporting Club | 19 | 7 | €9.0M | €15.0M | +40% |
| #5 | Tobias Slotsager Hellas Verona | 19 | 7 | €2.0M | €3.3M | +40% |
| #6 | Seydou Fini Genoa CFC | 19 | 7 | €1.3M | €2.2M | +40% |
| #7 | Lennon Miller Udinese Calcio | 19 | 7 | €8.0M | €13.3M | +40% |
| #8 | Jeff Ekhator Genoa CFC | 19 | 7 | €7.0M | €11.6M | +40% |
| #9 | Vasilije Adžić Juventus FC | 19 | 7 | €8.0M | €13.3M | +40% |
| #10 | Naj Razi Without Club | 19 | 7 | €300K | €499K | +40% |
| #11 | Niccolò Fortini ACF Fiorentina | 19 | 7 | €8.5M | €14.1M | +40% |
| #12 | İsak Vural Pisa Sporting Club | 19 | 7 | €4.5M | €7.5M | +40% |
| #13 | Luca Lipani US Sassuolo | 20 | 6 | €4.5M | €7.5M | +40% |
| #14 | Gioele Zacchi US Sassuolo | 22 | 4 | €600K | €997K | +40% |
| #15 | Davide Bartesaghi AC Milan | 19 | 7 | €3.0M | €5.0M | +40% |
| #16 | David Odogu AC Milan | 19 | 7 | €5.0M | €8.3M | +40% |
| #17 | Tiago Gabriel US Lecce | 20 | 6 | €3.0M | €4.6M | +35% |
| #18 | Juan Rodríguez Cagliari Calcio | 20 | 6 | €3.0M | €4.6M | +35% |
| #19 | Iker Bravo Udinese Calcio | 20 | 6 | €3.0M | €4.6M | +35% |
| #20 | Valentín Carboni Genoa CFC | 20 | 6 | €12.0M | €18.5M | +35% |
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 154.3. That means Tommaso Martinelli has 40% upside potential with only 0% forecast uncertainty—representing excellent risk-reward for value appreciation.
In second is AC Milan's Lorenzo Torriani with a 118.5 RAU (28% upside, 0% uncertainty). Third is Gioele Zacchi of US Sassuolo with a 100.1 RAU (19% upside, 0% uncertainty).
How RAU is calculated: RAU divides upside potential by forecast uncertainty (RAU = Upside % ÷ Uncertainty %). A RAU of 154.3 means the upside is 154.3× 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 | Tommaso Martinelli ACF Fiorentina | €2.5M | €2.3M-2.7M | +40% | 154.3 |
| #2 | Lorenzo Torriani AC Milan | €639K | €581K-698K | +28% | 118.5 |
| #3 | Gioele Zacchi US Sassuolo | €714K | €657K-772K | +19% | 100.1 |
| #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 | Filippo Rinaldi Parma Calcio 1913 | €373K | €343K-402K | +15% | 79.9 |
| #7 | Buba Sangaré AS Roma | €1.2M | €1.1M-1.4M | +23% | 68.9 |
| #8 | Kenan Yıldız Juventus FC | €89.5M | €77.2M-101.9M | +19% | 58.7 |
| #9 | Edoardo Corvi Parma Calcio 1913 | €386K | €355K-417K | +10% | 58.1 |
| #10 | Christos Mandas SS Lazio | €7.7M | €7.1M-8.3M | +10% | 58.1 |
| #11 | Stefano Turati US Sassuolo | €5.0M | €4.6M-5.4M | +10% | 58.1 |
| #12 | Elia Caprile Cagliari Calcio | €12.1M | €11.2M-13.1M | +10% | 58.1 |
| #13 | Niccolò Fortini ACF Fiorentina | €10.1M | €8.7M-11.5M | +19% | 58.0 |
| #14 | Tobias Slotsager Hellas Verona | €2.4M | €2.1M-2.7M | +19% | 58.0 |
| #15 | Lennon Miller Udinese Calcio | €9.5M | €8.2M-10.8M | +19% | 58.0 |
| #16 | David Odogu AC Milan | €6.0M | €5.1M-6.8M | +19% | 58.0 |
| #17 | Luca Lipani US Sassuolo | €5.4M | €4.6M-6.1M | +19% | 58.0 |
| #18 | İsak Vural Pisa Sporting Club | €5.4M | €4.6M-6.1M | +19% | 58.0 |
| #19 | Davide Bartesaghi AC Milan | €3.6M | €3.1M-4.1M | +19% | 58.0 |
| #20 | Jeff Ekhator Genoa CFC | €8.3M | €7.2M-9.5M | +19% | 58.0 |
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 Stanislav Lobotka captures 10.2% of total market value while representing only 24.3% of players in their age group—showing dominant elite status.
In second is Juventus FC's Mattia Perin with a +-14.1% ASC (10.2% value share vs 24.3% player share in 30+ bracket). Third is Stefan de Vrij of Inter Milan with a +-14.1% ASC (10.2% value vs 24.3% 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+ | 10.2% | 24.3% | -14.1% |
| #2 | Mattia Perin Juventus FC | 30+ | 10.2% | 24.3% | -14.1% |
| #3 | Stefan de Vrij Inter Milan | 30+ | 10.2% | 24.3% | -14.1% |
| #4 | Benjamin Siegrist Genoa CFC | 30+ | 10.2% | 24.3% | -14.1% |
| #5 | Leonardo Spinazzola SSC Napoli | 30+ | 10.2% | 24.3% | -14.1% |
| #6 | Juan Jesus SSC Napoli | 30+ | 10.2% | 24.3% | -14.1% |
| #7 | Cristiano Biraghi Torino FC | 30+ | 10.2% | 24.3% | -14.1% |
| #8 | Hakan Çalhanoğlu Inter Milan | 30+ | 10.2% | 24.3% | -14.1% |
| #9 | Patric SS Lazio | 30+ | 10.2% | 24.3% | -14.1% |
| #10 | Álvaro Morata Como 1907 | 30+ | 10.2% | 24.3% | -14.1% |
| #11 | Simone Verdi Como 1907 | 30+ | 10.2% | 24.3% | -14.1% |
| #12 | Alessandro Florenzi AC Milan | 30+ | 10.2% | 24.3% | -14.1% |
| #13 | Francesco Acerbi Inter Milan | 30+ | 10.2% | 24.3% | -14.1% |
| #14 | Marten de Roon Atalanta BC | 30+ | 10.2% | 24.3% | -14.1% |
| #15 | Luca Lezzerini ACF Fiorentina | 30+ | 10.2% | 24.3% | -14.1% |
| #16 | Nicola Leali Genoa CFC | 30+ | 10.2% | 24.3% | -14.1% |
| #17 | Charalampos Lykogiannis Bologna FC 1909 | 30+ | 10.2% | 24.3% | -14.1% |
| #18 | Matías Vecino SS Lazio | 30+ | 10.2% | 24.3% | -14.1% |
| #19 | Remo Freuler Bologna FC 1909 | 30+ | 10.2% | 24.3% | -14.1% |
| #20 | Nicolae Stanciu Genoa CFC | 30+ | 10.2% | 24.3% | -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: 18 immediate targets, 136 standard acquisitions, 0 watch-list prospects, 214 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 €2.0M. 1 undervalued, 8 premium.
Value Positioning vs Peers
| Player | Market Value | Position Median | Z-Score | Assessment |
|---|---|---|---|---|
Francisco Conceição Juventus FC | €30.0M | €5.0M | -1.67 | Undervalued |
Romelu Lukaku SSC Napoli | €15.0M | €5.0M | -1.40 | Good Value |
André Anderson Without Club | €150K | €5.0M | -1.23 | Good Value |
David Odogu AC Milan | €5.0M | €5.0M | -1.17 | Good Value |
Dimitrije Kamenovic SS Lazio | €300K | €5.0M | -1.13 | Good Value |
Kevin Bonifazi Bologna FC 1909 | €300K | €5.0M | -1.10 | Good Value |
Edoardo Corvi Parma Calcio 1913 | €350K | €5.0M | -1.10 | Good Value |
Giacomo Satalino US Sassuolo | €400K | €5.0M | -1.07 | Good Value |
Nikita Contini SSC Napoli | €400K | €5.0M | -1.05 | Good Value |
Manuel Locatelli Juventus FC | €30.0M | €5.0M | -1.00 | Good Value |
Teun Koopmeiners Juventus FC | €30.0M | €5.0M | -1.00 | Good Value |
Marco Sala Como 1907 | €500K | €5.0M | -1.00 | Good Value |
Ardon Jashari AC Milan | €32.0M | €5.0M | -1.00 | Good Value |
Junior Ajayi Hellas Verona | €300K | €5.0M | -0.90 | Good Value |
Alberto Cerri Como 1907 | €700K | €5.0M | -0.90 | Good Value |
Arturo Calabresi Pisa Sporting Club | €700K | €5.0M | -0.90 | Good Value |
Mihai Popa Torino FC | €650K | €5.0M | -0.90 | Good Value |
Filippo Rinaldi Parma Calcio 1913 | €325K | €5.0M | -0.89 | Good Value |
Nicolò Cavuoti Cagliari Calcio | €400K | €5.0M | -0.86 | Good Value |
Mitchel Bakker Atalanta BC | €5.0M | €5.0M | -0.86 | Good Value |