Best Attacking Midfielders in the Serie A (Jul 2026)
Ranked by Analytical Strength Index
Market Overview: Serie A Attacking Midfielders 2024-25
Our database tracked 82 Serie A Attacking Midfielders in the 2024-25 season, representing 30 clubs with a combined market value of €330.5M. The average market value for Serie A Attacking Midfielders was €4.0M, with the average age at 28 years old.
The most valuable attacking midfielder in the Serie A was Nico Paz, worth €65.0M and played for Como 1907 at 21 years old. The top 5 Attacking Midfielders averaged €29.8M in market value, including Charles De Ketelaere and Eljif Elmas.
Age distribution showed the youngest tracked attacking midfielder was Alphadjo Cissè (19 years, Hellas Verona, €6.0M), while the oldest was Ederson (40 years, Società Sportiva Lazio S.p.A., €700K). Research shows Attacking Midfielders typically peak at age 26.
Historical analysis showed 33 Attacking Midfielders (40%) 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 2024-25 season.
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 30 clubs with €330.5M combined value.
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.
Age Distribution: Serie A Attacking Midfielders
The Serie A CAM market shows 5 distinct age segments, with the largest cohort in the 30+ bracket (30 players, 37% of market). The 21-23 age group holds the most value at €94.3M, averaging €10.5M per player.
Top Attacking Midfielders by Age Bracket
U21 Years (10 players)
21-23 Years (9 players)
24-26 Years (19 players)
27-29 Years (14 players)
Market Value Distribution
Elite Tier Concentration
The top 9 Attacking Midfielders (11% of players) control €200.0M
Market Tiers
Market structure shows distributed value with elite (€50m+) tier representing 1% of the Serie A CAM pool.
Elite (€50M+)
Premium (€30-50M)
High (€15-30M)
Club Distribution: Serie A Attacking Midfielders
Among 30 Serie A clubs, Como 1907 leads with 4 Attacking Midfielders worth €67.3M (averaging €16.8M per player). The top 10 clubs account for 46% of tracked Attacking Midfielders.
Como 1907 (4 Attacking Midfielders)
Atalanta BC (4 Attacking Midfielders)
SSC Napoli (3 Attacking Midfielders)
Bologna Football Club 1909 (5 Attacking Midfielders)
Player Rankings
Ranked by Analytical Strength Index. Click any player to view full profile, or click the chart icon to see value history.
Nico Paz
Como 1907 • 21 years old
€56.2M
€65.0M
+15.6%
Expected: €74.6M
91.1
Charles De Ketelaere
Atalanta BC • 25 years old
€29.4M
€34.0M
+15.6%
Expected: €34.6M
83.3
Eljif Elmas
SSC Napoli • 26 years old
€17.3M
€20.0M
+15.6%
Expected: €20.6M
72.6
Kevin De Bruyne
SSC Napoli • 35 years old
€19.4M
€15.0M
-22.6%
Expected: €13.1M
70.0
Lazar Samardžić
Atalanta BC • 24 years old
€13.0M
€15.0M
+15.6%
Expected: €15.4M
70.0
Calvin Stengs
Pisa Sporting Club • 27 years old
€15.9M
€15.0M
-5.4%
Expected: €13.1M
69.1
Jens Odgaard
Bologna Football Club 1909 • 27 years old
€15.9M
€15.0M
-5.4%
Expected: €13.1M
69.1
Luis Alberto
Società Sportiva Lazio S.p.A. • 33 years old
€14.2M
€11.0M
-22.6%
Expected: €9.6M
65.9
Giovanni Fabbian
Bologna Football Club 1909 • 23 years old
€8.6M
€10.0M
+15.6%
Expected: €10.7M
61.8
Tommaso Baldanzi
Associazione Sportiva Roma • 23 years old
€8.6M
€10.0M
+15.6%
Expected: €10.7M
61.8
Nikola Vlašić
Torino FC • 28 years old
€12.9M
€10.0M
-22.6%
Expected: €8.8M
60.6
Lorenzo Pellegrini
Associazione Sportiva Roma • 30 years old
€11.6M
€9.0M
-22.6%
Expected: €7.5M
59.5
Vasilije Adžić
Juventus FC • 20 years old
€6.9M
€8.0M
+15.6%
Expected: €9.2M
57.2
Tomas Suslov
Hellas Verona • 24 years old
€6.1M
€7.0M
+15.6%
Expected: €7.2M
56.9
Andrea Colpani
ACF Fiorentina • 27 years old
€6.3M
€6.0M
-5.4%
Expected: €5.3M
54.1
Alphadjo Cissè
Hellas Verona • 19 years old
€5.2M
€6.0M
+15.6%
Expected: €7.1M
53.0
Nicolae Stanciu
Genoa CFC • 33 years old
€6.5M
€5.0M
-22.6%
Expected: €4.4M
52.5
Omri Gandelman
US Lecce • 26 years old
€4.3M
€5.0M
+15.6%
Expected: €5.1M
51.8
Daniel Maldini
Società Sportiva Lazio S.p.A. • 24 years old
€3.9M
€4.5M
+15.6%
Expected: €4.6M
51.4
Simone Pafundi
Udinese Calcio • 20 years old
€4.3M
€5.0M
+15.6%
Expected: €5.7M
51.3
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)
Atalanta BC's Charles De Ketelaere at 25 years old has the highest Pre-Peak Value Efficiency at 56.67×. That means Charles De Ketelaere is valued 56.67× higher than the median player in the 24-26 age bracket-representing exceptional value before reaching peak age.
In second is Atalanta BC's Lazar Samardžić, who is 24 years old, with a 25.00× PPVE. Third is Nico Paz of Como 1907, who is 21 years old with a 16.25× 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 56.67× means the player is worth 5567% 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 | Charles De Ketelaere Atalanta BC | 25 | 24-26 | €34.0M | €600K | 56.67× |
| #2 | Lazar Samardžić Atalanta BC | 24 | 24-26 | €15.0M | €600K | 25.00× |
| #3 | Nico Paz Como 1907 | 21 | 21-23 | €65.0M | €4.0M | 16.25× |
| #4 | Tomas Suslov Hellas Verona | 24 | 24-26 | €7.0M | €600K | 11.67× |
| #5 | Vasilije Adžić Juventus FC | 20 | U21 | €8.0M | €1.0M | 8.00× |
| #6 | Daniel Maldini Società Sportiva Lazio S.p.A. | 24 | 24-26 | €4.5M | €600K | 7.50× |
| #7 | Alphadjo Cissè Hellas Verona | 19 | U21 | €6.0M | €1.0M | 6.00× |
| #8 | Simone Pafundi Udinese Calcio | 20 | U21 | €5.0M | €1.0M | 5.00× |
| #9 | Filip Marchwinski US Lecce | 24 | 24-26 | €2.5M | €600K | 4.17× |
| #10 | Giovanni Fabbian Bologna Football Club 1909 | 23 | 21-23 | €10.0M | €4.0M | 2.50× |
| #11 | Tommaso Baldanzi Associazione Sportiva Roma | 23 | 21-23 | €10.0M | €4.0M | 2.50× |
| #12 | Tommaso Rubino ACF Fiorentina | 19 | U21 | €1.2M | €1.0M | 1.20× |
| #13 | Cristian Volpato US Sassuolo | 22 | 21-23 | €4.5M | €4.0M | 1.13× |
| #14 | David Pejičić Udinese Calcio | 19 | U21 | €1.0M | €1.0M | 1.00× |
| #15 | Giacomo Olzer AC Milan | 25 | 24-26 | €600K | €600K | 1.00× |
| #16 | Krisztofer Horváth Torino FC | 24 | 24-26 | €600K | €600K | 1.00× |
| #17 | Gaetano Oristanio Parma Calcio 1913 | 23 | 21-23 | €4.0M | €4.0M | 1.00× |
| #18 | Luis Rojas Bologna Football Club 1909 | 24 | 24-26 | €500K | €600K | 0.83× |
| #19 | Federico Cassa Atalanta BC | 20 | U21 | €700K | €1.0M | 0.70× |
| #20 | Alessandro Cortinovis Atalanta BC | 25 | 24-26 | €400K | €600K | 0.67× |
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)
Udinese Calcio's David Pejičić at 19 years old has the highest Return-to-Peak Potential at +40%. That means Tommaso Rubino is projected to appreciate 40% as they reach their peak age in 7 years-representing significant upside before entering their prime.
In second is Parma Calcio 1913's Elia Plicco, who is 19 years old, with a +40% RPP (7 years to peak). Third is Tommaso Rubino of ACF Fiorentina, 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 | David Pejičić Udinese Calcio | 19 | 7 | €1.0M | €1.7M | +40% |
| #2 | Elia Plicco Parma Calcio 1913 | 19 | 7 | €500K | €831K | +40% |
| #3 | Tommaso Rubino ACF Fiorentina | 19 | 7 | €1.2M | €2.0M | +40% |
| #4 | Alphadjo Cissè Hellas Verona | 19 | 7 | €6.0M | €10.0M | +40% |
| #5 | Naj Razi Como 1907 | 19 | 7 | €275K | €457K | +40% |
| #6 | Federico Cassa Atalanta BC | 20 | 6 | €700K | €1.1M | +35% |
| #7 | Daniele Quieto Inter Milan | 20 | 6 | €250K | €386K | +35% |
| #8 | Simone Pafundi Udinese Calcio | 20 | 6 | €5.0M | €7.7M | +35% |
| #9 | Vasilije Adžić Juventus FC | 20 | 6 | €8.0M | €12.4M | +35% |
| #10 | Saad El Haddad Venezia FC | 20 | 6 | €400K | €618K | +35% |
| #11 | Andrea Sodero FC Empoli | 21 | 5 | €300K | €431K | +30% |
| #12 | Nico Paz Como 1907 | 21 | 5 | €65.0M | €93.4M | +30% |
| #13 | Cristian Volpato US Sassuolo | 22 | 4 | €4.5M | €6.0M | +25% |
| #14 | Antonio Vergara SSC Napoli | 23 | 3 | €175K | €218K | +20% |
| #15 | Dennis Stojkovic Torino FC | 23 | 3 | €150K | €186K | +20% |
| #16 | Giovanni Fabbian Bologna Football Club 1909 | 23 | 3 | €10.0M | €12.4M | +20% |
| #17 | Tommaso Baldanzi Associazione Sportiva Roma | 23 | 3 | €10.0M | €12.4M | +20% |
| #18 | Gaetano Oristanio Parma Calcio 1913 | 23 | 3 | €4.0M | €5.0M | +20% |
| #19 | Nicolò Cavuoti Cagliari Calcio | 23 | 3 | €200K | €249K | +20% |
| #20 | Daniel Maldini Società Sportiva Lazio S.p.A. | 24 | 2 | €4.5M | €5.2M | +14% |
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 Rubino has the highest Risk-Adjusted Upside at 53.6. That means Tommaso Rubino has 19% upside potential with only 0% forecast uncertainty-representing excellent risk-reward for value appreciation.
In second is Udinese Calcio's David Pejičić with a 53.6 RAU (19% upside, 0% uncertainty). Third is Elia Plicco of Parma Calcio 1913 with a 53.6 RAU (19% upside, 0% uncertainty).
How RAU is calculated: RAU divides upside potential by forecast uncertainty (RAU = Upside % ÷ Uncertainty %). A RAU of 53.6 means the upside is 53.6× 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 Rubino ACF Fiorentina | €1.4M | €1.2M-1.6M | +19% | 53.6 |
| #2 | David Pejičić Udinese Calcio | €1.2M | €1.0M-1.4M | +19% | 53.6 |
| #3 | Elia Plicco Parma Calcio 1913 | €595K | €506K-684K | +19% | 53.6 |
| #4 | Alphadjo Cissè Hellas Verona | €7.1M | €6.1M-8.2M | +19% | 53.6 |
| #5 | Naj Razi Como 1907 | €327K | €278K-376K | +19% | 53.6 |
| #6 | Nico Paz Como 1907 | €74.6M | €63.4M-85.7M | +15% | 43.0 |
| #7 | Federico Cassa Atalanta BC | €803K | €683K-923K | +15% | 42.8 |
| #8 | Daniele Quieto Inter Milan | €287K | €244K-330K | +15% | 42.8 |
| #9 | Vasilije Adžić Juventus FC | €9.2M | €7.8M-10.5M | +15% | 42.8 |
| #10 | Saad El Haddad Venezia FC | €459K | €390K-527K | +15% | 42.8 |
| #11 | Simone Pafundi Udinese Calcio | €5.7M | €4.9M-6.6M | +15% | 42.8 |
| #12 | Andrea Sodero FC Empoli | €331K | €281K-380K | +10% | 31.1 |
| #13 | Dennis Stojkovic Torino FC | €161K | €140K-181K | +7% | 25.4 |
| #14 | Gaetano Oristanio Parma Calcio 1913 | €4.3M | €3.7M-4.8M | +7% | 25.4 |
| #15 | Giovanni Fabbian Bologna Football Club 1909 | €10.7M | €9.3M-12.1M | +7% | 25.4 |
| #16 | Tommaso Baldanzi Associazione Sportiva Roma | €10.7M | €9.3M-12.1M | +7% | 25.4 |
| #17 | Antonio Vergara SSC Napoli | €187K | €163K-212K | +7% | 25.4 |
| #18 | Nicolò Cavuoti Cagliari Calcio | €214K | €186K-242K | +7% | 25.4 |
| #19 | Cristian Volpato US Sassuolo | €4.8M | €4.1M-5.4M | +6% | 21.2 |
| #20 | Luka Markovic FC Crotone | €309K | €269K-349K | +3% | 11.1 |
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)
Chievo Verona's Nicola Bellomo in the 30+ age bracket has the highest Age-Share Concentration at +-18.3%. That means Kevin De Bruyne captures 18.2% of total market value while representing only 36.6% of players in their age group-showing dominant elite status.
In second is Chievo Verona's Alessandro Sbaffo with a +-18.3% ASC (18.2% value share vs 36.6% player share in 30+ bracket). Third is Gastón Ramírez of UC Sampdoria with a +-18.3% ASC (18.2% value vs 36.6% players in 30+ bracket).
How ASC is calculated: ASC = (% of total value) - (% of total players) in age bracket. A +-18.3% ASC means the player captures -18.3% 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 | Nicola Bellomo Chievo Verona | 30+ | 18.2% | 36.6% | -18.3% |
| #2 | Alessandro Sbaffo Chievo Verona | 30+ | 18.2% | 36.6% | -18.3% |
| #3 | Gastón Ramírez UC Sampdoria | 30+ | 18.2% | 36.6% | -18.3% |
| #4 | Luis Alberto Società Sportiva Lazio S.p.A. | 30+ | 18.2% | 36.6% | -18.3% |
| #5 | Simone Verdi Como 1907 | 30+ | 18.2% | 36.6% | -18.3% |
| #6 | Carlos Carbonero UC Sampdoria | 30+ | 18.2% | 36.6% | -18.3% |
| #7 | Lucas Chiaretti Delfino Pescara 1936 | 30+ | 18.2% | 36.6% | -18.3% |
| #8 | Nicolae Stanciu Genoa CFC | 30+ | 18.2% | 36.6% | -18.3% |
| #9 | Pablo Ceppelini Cagliari Calcio | 30+ | 18.2% | 36.6% | -18.3% |
| #10 | Valerio Verre UC Sampdoria | 30+ | 18.2% | 36.6% | -18.3% |
| #11 | Victor Chievo Verona | 30+ | 18.2% | 36.6% | -18.3% |
| #12 | Mattia Aramu Genoa CFC | 30+ | 18.2% | 36.6% | -18.3% |
| #13 | Luca Garritano Frosinone Calcio | 30+ | 18.2% | 36.6% | -18.3% |
| #14 | Dele Alli Como 1907 | 30+ | 18.2% | 36.6% | -18.3% |
| #15 | César Falletti Bologna Football Club 1909 | 30+ | 18.2% | 36.6% | -18.3% |
| #16 | Antonio Vutov Udinese Calcio | 30+ | 18.2% | 36.6% | -18.3% |
| #17 | Valter Birsa Cagliari Calcio | 30+ | 18.2% | 36.6% | -18.3% |
| #18 | Gastón Pereiro Genoa CFC | 30+ | 18.2% | 36.6% | -18.3% |
| #19 | Octávio ACF Fiorentina | 30+ | 18.2% | 36.6% | -18.3% |
| #20 | Antonín Barák ACF Fiorentina | 30+ | 18.2% | 36.6% | -18.3% |
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: 5 immediate targets, 14 standard acquisitions, 0 watch-list prospects, 27 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 €450K. 0 undervalued, 6 premium.
Value Positioning vs Peers
| Player | Market Value | Position Median | Z-Score | Assessment |
|---|---|---|---|---|
Andrea Colpani ACF Fiorentina | €6.0M | €700K | -1.00 | Good Value |
Lazar Samardžić Atalanta BC | €15.0M | €700K | -1.00 | Good Value |
Omri Gandelman US Lecce | €5.0M | €700K | -1.00 | Good Value |
André Anderson Società Sportiva Lazio S.p.A. | €125K | €700K | -0.69 | Good Value |
Nicolae Stanciu Genoa CFC | €5.0M | €700K | -0.67 | Good Value |
Felice D'Amico UC Sampdoria | €175K | €700K | -0.56 | Good Value |
Hamza Haoudi Frosinone Calcio | €175K | €700K | -0.56 | Good Value |
Roberto Biancu Cagliari Calcio | €200K | €700K | -0.50 | Good Value |
Mohamed Bahlouli UC Sampdoria | €200K | €700K | -0.50 | Good Value |
Matías Fernández ACF Fiorentina | €125K | €700K | -0.47 | Fair Value |
Andrea Mazzarani FC Crotone | €125K | €700K | -0.47 | Fair Value |
Davide Di Gennaro Società Sportiva Lazio S.p.A. | €150K | €700K | -0.44 | Fair Value |
Lauri Ala-Myllymäki Venezia FC | €200K | €700K | -0.41 | Fair Value |
Lorenzo Di Livio Associazione Sportiva Roma | €225K | €700K | -0.40 | Fair Value |
Nicola Mosti Juventus FC | €250K | €700K | -0.38 | Fair Value |
Gastón Ramírez UC Sampdoria | €200K | €700K | -0.37 | Fair Value |
Lucas Chiaretti Delfino Pescara 1936 | €200K | €700K | -0.37 | Fair Value |
Daniele Quieto Inter Milan | €250K | €700K | -0.34 | Fair Value |
Simone Pafundi Udinese Calcio | €5.0M | €700K | -0.33 | Fair Value |
Gastón Pereiro Genoa CFC | €250K | €700K | -0.31 | Fair Value |
How We Rank Serie A Attacking Midfielders
Our Analytical Strength Index is calibrated specifically for attacking midfielders, 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 CAM
Historical Achievement Index (35%)
Peak career market value for Serie A attacking midfielders, 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 attacking midfielders, capturing recent form, injuries, and current performance level. Weighted to reflect age-related depreciation patterns.
Playing Time Utilization (18%)
Midfielders with 2,400+ minutes score highest, indicating regular starting role and sustained performance.
Age-Adjusted Performance Curve (12%)
Midfielders peak at 26-27 with 6.0%/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.
CAM Performance Benchmarks
Peak Age: 26-27 years (technical skill and tactical awareness)
Decline Rate: 6.0% per year (technical skills age better than physical attributes)
Optimal Minutes: 2,400-2,500 per season (balance of involvement and recovery)
1-Year Market Value Forecast
Probabilistic model combining age-curve depreciation, value momentum, and playing time factors:
• Age Factor: Midfielder -6.0%/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: ±12-15% confidence interval
Research Foundation
• Dendir (2016): Age-performance curves for attacking midfielders
• 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 Attacking Midfielders in the 2024-25 season
Who are the most valuable Attacking Midfielders in the Serie A in 2024-25?
The most valuable attacking midfielder in the Serie A in 2024-25 is Nico Paz, who is worth €65.0M and plays for Como 1907. The second most valuable is Charles De Ketelaere (€34.0M, Atalanta BC), followed by Eljif Elmas (€20.0M, SSC Napoli). Our database tracks 82 Serie A Attacking Midfielders with comprehensive market valuations updated for the 2024-25 season.
How are Serie A Attacking Midfielders ranked?
Serie A Attacking Midfielders are ranked by our proprietary Analytical Strength Index, which is specifically calibrated for Attacking Midfielders. 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 Attacking Midfielders peak?
Attacking midfielders typically peak at age 26, with a decline rate of 6.5% per year after peak. This position demands high technical ability, creativity, and burst acceleration, which tend to decline faster than other midfielder attributes. The optimal playing time is around 2,400 minutes per season.
How much does it cost to sign a top attacking midfielder from the Serie A?
Transfer fees for Serie A Attacking Midfielders vary significantly based on market value, contract length, and club bargaining position. For the top-ranked attacking midfielder Nico Paz (market value: €65.0M), estimated transfer fees would range from €52.0M to €91.0M 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 Attacking Midfielders?
Our 1-year forecast model projects market value changes for Serie A Attacking Midfielders 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-midfielders have ±12-15% volatility. 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 attacking midfielder data come from?
Our Serie A attacking midfielder 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 2024-25 season to ensure accuracy for recruitment and investment decisions.