Best Attacking Midfielders in the Serie A (Mar 2026)
Ranked by Analytical Strength Score
Market Overview: Serie A Attacking Midfielders 2023-24
Our database tracked 39 Serie A Attacking Midfielders in the 2023-24 season, representing 19 clubs with a combined market value of €347.2M. The average market value for Serie A Attacking Midfielders was €8.9M, with the average age at 25.7 years old.
The most valuable attacking midfielder in the Serie A was Nico Paz, worth €55.0M and played for Como 1907 at 21 years old. The top 5 Attacking Midfielders averaged €31.4M in market value, including Charles De Ketelaere and Teun Koopmeiners.
Age distribution showed the youngest tracked attacking midfielder was Lorran (19 years, Pisa Sporting Club, €9.0M), while the oldest was Franco Vázquez (37 years, US Cremonese, €750K). Research shows Attacking Midfielders typically peak at age 26.
Historical analysis showed 24 Attacking Midfielders (62%) 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 Attacking Midfielders remained actively developing with emerging talent in the 2023-24 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 Attacking Midfielders. Identify undervalued assets and track market momentum across 19 clubs with €347.2M combined value.
Age Distribution: Serie A Attacking Midfielders
The Serie A CAM market shows 5 distinct age segments, with the largest cohort in the 24-26 bracket (13 players, 33% of market). The 24-26 age group holds the most value at €132.2M, averaging €10.2M per player.
Top Attacking Midfielders by Age Bracket
U21 Years (4 players)
21-23 Years (9 players)
24-26 Years (13 players)
27-29 Years (7 players)
Market Value Distribution
Elite Tier Concentration
The top 4 Attacking Midfielders (10% of players) control €140.0M
Market Tiers
Market structure shows distributed value with elite (€50m+) tier representing 3% of the Serie A CAM pool.
Elite (€50M+)
Premium (€30-50M)
High (€15-30M)
Club Distribution: Serie A Attacking Midfielders
Among 19 Serie A clubs, Atalanta BC leads with 3 Attacking Midfielders worth €62.0M (averaging €20.7M per player). The top 10 clubs account for 64% of tracked Attacking Midfielders.
Atalanta BC (3 Attacking Midfielders)
Como 1907 (2 Attacking Midfielders)
Juventus FC (2 Attacking Midfielders)
Genoa CFC (5 Attacking Midfielders)
Player Rankings
Ranked by APE Strength Score. Click any player to view full profile, or click the chart icon to see value history.
Nico Paz
Como 1907 • 21 years old
€47.6M
€55.0M
+15.6%
Expected: €63.1M
88.0
Charles De Ketelaere
Atalanta BC • 24 years old
€30.3M
€35.0M
+15.6%
Expected: €37.3M
83.2
Teun Koopmeiners
Juventus FC • 28 years old
€38.7M
€30.0M
-22.6%
Expected: €27.2M
77.5
Kevin De Bruyne
SSC Napoli • 34 years old
€25.8M
€20.0M
-22.6%
Expected: €18.1M
72.7
Lazar Samardžić
Atalanta BC • 24 years old
€14.7M
€17.0M
+15.6%
Expected: €18.1M
71.4
Giovanni Fabbian
Bologna FC 1909 • 23 years old
€10.4M
€12.0M
+15.6%
Expected: €13.4M
67.6
Nicolò Zaniolo
Udinese Calcio • 26 years old
€10.4M
€12.0M
+15.6%
Expected: €12.9M
66.2
Jens Odgaard
Bologna FC 1909 • 26 years old
€10.4M
€12.0M
+15.6%
Expected: €12.9M
66.2
Valentín Carboni
Genoa CFC • 20 years old
€10.4M
€12.0M
+15.6%
Expected: €14.3M
65.7
Daniel Maldini
Atalanta BC • 24 years old
€8.6M
€10.0M
+15.6%
Expected: €10.2M
61.1
Tommaso Baldanzi
AS Roma • 22 years old
€8.6M
€10.0M
+15.6%
Expected: €10.6M
61.0
Albert Grønbæk
Genoa CFC • 24 years old
€8.2M
€9.5M
+15.6%
Expected: €9.7M
60.5
Lorenzo Pellegrini
AS Roma • 29 years old
€11.6M
€9.0M
-22.6%
Expected: €7.4M
59.0
Kristian Thorstvedt
US Sassuolo • 26 years old
€7.8M
€9.0M
+15.6%
Expected: €9.3M
58.9
Lorran
Pisa Sporting Club • 19 years old
€7.8M
€9.0M
+15.6%
Expected: €10.7M
57.9
Nikola Vlašić
Torino FC • 28 years old
€10.3M
€8.0M
-22.6%
Expected: €7.0M
57.6
Fisayo Dele-Bashiru
SS Lazio • 25 years old
€6.5M
€7.5M
+15.6%
Expected: €7.3M
57.2
Vasilije Adžić
Juventus FC • 19 years old
€6.9M
€8.0M
+15.6%
Expected: €9.5M
56.4
Calvin Stengs
Pisa Sporting Club • 27 years old
€7.4M
€7.0M
-5.4%
Expected: €6.1M
55.9
Matteo Tramoni
Pisa Sporting Club • 26 years old
€6.1M
€7.0M
+15.6%
Expected: €7.2M
55.9
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)
Como 1907's Nico Paz at 21 years old has the highest Pre-Peak Value Efficiency at 9.17×. That means Nico Paz is valued 9.17× higher than the median player in the 21-23 age bracket—representing exceptional value before reaching peak age.
In second is Atalanta BC's Charles De Ketelaere, who is 24 years old, with a 3.68× PPVE. Third is Giovanni Fabbian of Bologna FC 1909, who is 23 years old with a 2.00× 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 9.17× means the player is worth 817% 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 | Nico Paz Como 1907 | 21 | 21-23 | €55.0M | €6.0M | 9.17× |
| #2 | Charles De Ketelaere Atalanta BC | 24 | 24-26 | €35.0M | €9.5M | 3.68× |
| #3 | Giovanni Fabbian Bologna FC 1909 | 23 | 21-23 | €12.0M | €6.0M | 2.00× |
| #4 | Lazar Samardžić Atalanta BC | 24 | 24-26 | €17.0M | €9.5M | 1.79× |
| #5 | Tommaso Baldanzi AS Roma | 22 | 21-23 | €10.0M | €6.0M | 1.67× |
| #6 | Valentín Carboni Genoa CFC | 20 | U21 | €12.0M | €9.0M | 1.33× |
| #7 | Cristian Volpato US Sassuolo | 22 | 21-23 | €6.5M | €6.0M | 1.08× |
| #8 | Daniel Maldini Atalanta BC | 24 | 24-26 | €10.0M | €9.5M | 1.05× |
| #9 | Lorran Pisa Sporting Club | 19 | U21 | €9.0M | €9.0M | 1.00× |
| #10 | Albert Grønbæk Genoa CFC | 24 | 24-26 | €9.5M | €9.5M | 1.00× |
| #11 | Tomas Suslov Hellas Verona | 23 | 21-23 | €6.0M | €6.0M | 1.00× |
| #12 | Gaetano Oristanio Parma Calcio 1913 | 23 | 21-23 | €6.0M | €6.0M | 1.00× |
| #13 | Vasilije Adžić Juventus FC | 19 | U21 | €8.0M | €9.0M | 0.89× |
| #14 | Fisayo Dele-Bashiru SS Lazio | 25 | 24-26 | €7.5M | €9.5M | 0.79× |
| #15 | Tino Anjorin Torino FC | 24 | 24-26 | €6.0M | €9.5M | 0.63× |
| #16 | Gianluca Gaetano Cagliari Calcio | 25 | 24-26 | €4.0M | €9.5M | 0.42× |
| #17 | Antonio Vergara SSC Napoli | 23 | 21-23 | €2.2M | €6.0M | 0.37× |
| #18 | Filip Marchwinski US Lecce | 24 | 24-26 | €3.0M | €9.5M | 0.32× |
| #19 | Nicolò Cavuoti Cagliari Calcio | 22 | 21-23 | €400K | €6.0M | 0.07× |
| #20 | Hugo Cuenca Genoa CFC | 21 | 21-23 | €300K | €6.0M | 0.05× |
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)
Pisa Sporting Club's Lorran at 19 years old has the highest Return-to-Peak Potential at +40%. That means Lorran is projected to appreciate 40% as they reach their peak age in 7 years—representing significant upside before entering their prime.
In second is Juventus FC's Vasilije Adžić, who is 19 years old, with a +40% RPP (7 years to peak). Third is Naj Razi of Without Club, who is 19 years old with a +40% RPP (7 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 40% RPP means the player is expected to gain 40% 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 | Lorran Pisa Sporting Club | 19 | 7 | €9.0M | €15.0M | +40% |
| #2 | Vasilije Adžić Juventus FC | 19 | 7 | €8.0M | €13.3M | +40% |
| #3 | Naj Razi Without Club | 19 | 7 | €300K | €499K | +40% |
| #4 | Valentín Carboni Genoa CFC | 20 | 6 | €12.0M | €18.5M | +35% |
| #5 | Hugo Cuenca Genoa CFC | 21 | 5 | €300K | €431K | +30% |
| #6 | Nico Paz Como 1907 | 21 | 5 | €55.0M | €79.1M | +30% |
| #7 | Tommaso Baldanzi AS Roma | 22 | 4 | €10.0M | €13.4M | +25% |
| #8 | Nicolò Cavuoti Cagliari Calcio | 22 | 4 | €400K | €535K | +25% |
| #9 | Cristian Volpato US Sassuolo | 22 | 4 | €6.5M | €8.7M | +25% |
| #10 | Tomas Suslov Hellas Verona | 23 | 3 | €6.0M | €7.5M | +20% |
| #11 | Gaetano Oristanio Parma Calcio 1913 | 23 | 3 | €6.0M | €7.5M | +20% |
| #12 | Giovanni Fabbian Bologna FC 1909 | 23 | 3 | €12.0M | €14.9M | +20% |
| #13 | Antonio Vergara SSC Napoli | 23 | 3 | €2.2M | €2.7M | +20% |
| #14 | Lazar Samardžić Atalanta BC | 24 | 2 | €17.0M | €19.7M | +14% |
| #15 | Tino Anjorin Torino FC | 24 | 2 | €6.0M | €6.9M | +14% |
| #16 | Daniel Maldini Atalanta BC | 24 | 2 | €10.0M | €11.6M | +14% |
| #17 | Filip Marchwinski US Lecce | 24 | 2 | €3.0M | €3.5M | +14% |
| #18 | Charles De Ketelaere Atalanta BC | 24 | 2 | €35.0M | €40.5M | +14% |
| #19 | Albert Grønbæk Genoa CFC | 24 | 2 | €9.5M | €11.0M | +14% |
| #20 | Fisayo Dele-Bashiru SS Lazio | 25 | 1 | €7.5M | €8.1M | +7% |
Risk-Adjusted Upside (RAU)
Upside potential weighted against forecast uncertainty. Higher RAU = better risk-reward profile.
Understanding Risk-Adjusted Upside (RAU)
Genoa CFC's Valentín Carboni has the highest Risk-Adjusted Upside at 47.0. That means Valentín Carboni has 19% upside potential with only 0% forecast uncertainty—representing excellent risk-reward for value appreciation.
In second is Without Club's Naj Razi with a 46.4 RAU (19% upside, 0% uncertainty). Third is Vasilije Adžić of Juventus FC with a 46.4 RAU (19% upside, 0% uncertainty).
How RAU is calculated: RAU divides upside potential by forecast uncertainty (RAU = Upside % ÷ Uncertainty %). A RAU of 47.0 means the upside is 47.0× 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 | Valentín Carboni Genoa CFC | €14.3M | €11.9M-16.8M | +19% | 47.0 |
| #2 | Naj Razi Without Club | €357K | €296K-419K | +19% | 46.4 |
| #3 | Vasilije Adžić Juventus FC | €9.5M | €7.9M-11.2M | +19% | 46.4 |
| #4 | Lorran Pisa Sporting Club | €10.7M | €8.9M-12.6M | +19% | 46.4 |
| #5 | Nico Paz Como 1907 | €63.1M | €52.2M-74.0M | +15% | 37.3 |
| #6 | Giovanni Fabbian Bologna FC 1909 | €13.4M | €11.4M-15.4M | +11% | 34.2 |
| #7 | Hugo Cuenca Genoa CFC | €331K | €274K-388K | +10% | 26.9 |
| #8 | Jens Odgaard Bologna FC 1909 | €12.9M | €10.9M-14.8M | +7% | 22.3 |
| #9 | Nicolò Zaniolo Udinese Calcio | €12.9M | €10.9M-14.8M | +7% | 22.3 |
| #10 | Antonio Vergara SSC Napoli | €2.4M | €2.0M-2.7M | +7% | 22.0 |
| #11 | Tomas Suslov Hellas Verona | €6.4M | €5.5M-7.4M | +7% | 22.0 |
| #12 | Gaetano Oristanio Parma Calcio 1913 | €6.4M | €5.5M-7.4M | +7% | 22.0 |
| #13 | Lazar Samardžić Atalanta BC | €18.1M | €15.4M-20.8M | +7% | 20.6 |
| #14 | Charles De Ketelaere Atalanta BC | €37.3M | €31.7M-42.9M | +7% | 20.6 |
| #15 | Cristian Volpato US Sassuolo | €6.9M | €5.8M-7.9M | +6% | 18.4 |
| #16 | Nicolò Cavuoti Cagliari Calcio | €423K | €360K-487K | +6% | 18.4 |
| #17 | Tommaso Baldanzi AS Roma | €10.6M | €9.0M-12.2M | +6% | 18.4 |
| #18 | André Anderson Without Club | €154K | €131K-178K | +3% | 9.6 |
| #19 | Matteo Tramoni Pisa Sporting Club | €7.2M | €6.1M-8.3M | +3% | 9.6 |
| #20 | Kristian Thorstvedt US Sassuolo | €9.3M | €7.9M-10.7M | +3% | 9.6 |
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: attacking midfielder position shows strong 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)
Como 1907's Simone Verdi in the 30+ age bracket has the highest Age-Share Concentration at +-7.3%. That means Kevin De Bruyne captures 8.1% of total market value while representing only 15.4% of players in their age group—showing dominant elite status.
In second is Genoa CFC's Nicolae Stanciu with a +-7.3% ASC (8.1% value share vs 15.4% player share in 30+ bracket). Third is Ruslan Malinovskyi of Genoa CFC with a +-7.3% ASC (8.1% value vs 15.4% players in 30+ bracket).
How ASC is calculated: ASC = (% of total value) - (% of total players) in age bracket. A +-7.3% ASC means the player captures -7.3% 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 | Simone Verdi Como 1907 | 30+ | 8.1% | 15.4% | -7.3% |
| #2 | Nicolae Stanciu Genoa CFC | 30+ | 8.1% | 15.4% | -7.3% |
| #3 | Ruslan Malinovskyi Genoa CFC | 30+ | 8.1% | 15.4% | -7.3% |
| #4 | Franco Vázquez US Cremonese | 30+ | 8.1% | 15.4% | -7.3% |
| #5 | Nicolas Viola Without Club | 30+ | 8.1% | 15.4% | -7.3% |
| #6 | Kevin De Bruyne SSC Napoli | 30+ | 8.1% | 15.4% | -7.3% |
| #7 | Tomas Suslov Hellas Verona | 21-23 | 28.3% | 23.1% | +5.3% |
| #8 | Gaetano Oristanio Parma Calcio 1913 | 21-23 | 28.3% | 23.1% | +5.3% |
| #9 | Giovanni Fabbian Bologna FC 1909 | 21-23 | 28.3% | 23.1% | +5.3% |
| #10 | Tommaso Baldanzi AS Roma | 21-23 | 28.3% | 23.1% | +5.3% |
| #11 | Nicolò Cavuoti Cagliari Calcio | 21-23 | 28.3% | 23.1% | +5.3% |
| #12 | Antonio Vergara SSC Napoli | 21-23 | 28.3% | 23.1% | +5.3% |
| #13 | Cristian Volpato US Sassuolo | 21-23 | 28.3% | 23.1% | +5.3% |
| #14 | Hugo Cuenca Genoa CFC | 21-23 | 28.3% | 23.1% | +5.3% |
| #15 | Nico Paz Como 1907 | 21-23 | 28.3% | 23.1% | +5.3% |
| #16 | Jens Odgaard Bologna FC 1909 | 24-26 | 38.1% | 33.3% | +4.7% |
| #17 | Gianluca Gaetano Cagliari Calcio | 24-26 | 38.1% | 33.3% | +4.7% |
| #18 | Nicolò Zaniolo Udinese Calcio | 24-26 | 38.1% | 33.3% | +4.7% |
| #19 | Tino Anjorin Torino FC | 24-26 | 38.1% | 33.3% | +4.7% |
| #20 | Charles De Ketelaere Atalanta BC | 24-26 | 38.1% | 33.3% | +4.7% |
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: 4 immediate targets, 11 standard acquisitions, 0 watch-list prospects, 15 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 €900K. 0 undervalued, 0 premium.
Value Positioning vs Peers
| Player | Market Value | Position Median | Z-Score | Assessment |
|---|---|---|---|---|
Tino Anjorin Torino FC | €6.0M | €7.0M | -0.78 | Good Value |
André Anderson Without Club | €150K | €7.0M | -0.74 | Good Value |
Matteo Tramoni Pisa Sporting Club | €7.0M | €7.0M | -0.56 | Good Value |
Calvin Stengs Pisa Sporting Club | €7.0M | €7.0M | -0.50 | Fair Value |
Fisayo Dele-Bashiru SS Lazio | €7.5M | €7.0M | -0.44 | Fair Value |
Grigoris Kastanos Hellas Verona | €1.5M | €7.0M | -0.40 | Fair Value |
Vasilije Adžić Juventus FC | €8.0M | €7.0M | -0.25 | Fair Value |
Franco Vázquez US Cremonese | €750K | €7.0M | -0.16 | Fair Value |
Tomas Suslov Hellas Verona | €6.0M | €7.0M | -0.13 | Fair Value |
Gaetano Oristanio Parma Calcio 1913 | €6.0M | €7.0M | -0.13 | Fair Value |
Kristian Thorstvedt US Sassuolo | €9.0M | €7.0M | -0.11 | Fair Value |
Simone Verdi Como 1907 | €900K | €7.0M | -0.06 | Fair Value |
Hugo Cuenca Genoa CFC | €300K | €7.0M | -0.05 | Fair Value |
Lorran Pisa Sporting Club | €9.0M | €7.0M | 0.00 | Fair Value |
Nikola Vlašić Torino FC | €8.0M | €7.0M | 0.00 | Fair Value |
Abdelhamid Sabiri ACF Fiorentina | €1.7M | €7.0M | 0.00 | Fair Value |
Teun Koopmeiners Juventus FC | €30.0M | €7.0M | 0.00 | Fair Value |
Charles De Ketelaere Atalanta BC | €35.0M | €7.0M | 0.00 | Fair Value |
Albert Grønbæk Genoa CFC | €9.5M | €7.0M | 0.00 | Fair Value |
Lazar Samardžić Atalanta BC | €17.0M | €7.0M | 0.00 | Fair Value |