Best Attacking Midfielders in the Serie A (Sep 2026)
87 players tracked across 30 clubs. Updated September 2026.
Ranked by Analytical Strength Index
Market Overview: Serie A Attacking Midfielders 2026-27
Our database tracked 87 Serie A Attacking Midfielders in the 2026-27 season, representing 30 clubs with a combined market value of €369.1M. The average market value for Serie A Attacking Midfielders was €4.2M, with the average age at 28 years old.
The most valuable attacking midfielder in the Serie A was Nico Paz, worth €80.0M and played for Como 1907 at 22 years old. The top 5 Attacking Midfielders averaged €34.2M in market value, including Martin Baturina and Charles De Ketelaere.
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 27.
Historical analysis showed 25 Attacking Midfielders (29%) 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 2026-27 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 €369.1M 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.
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 • 22 years old
€69.2M
€80.0M
+15.6%
Expected: €77.8M
93.5
Martin Baturina
Como 1907 • 23 years old
€25.9M
€30.0M
+15.6%
Expected: €28.0M
78.6
Charles De Ketelaere
Atalanta BC • 25 years old
€25.9M
€30.0M
+15.6%
Expected: €29.6M
78.6
Lazar Samardžić
Atalanta BC • 24 years old
€13.8M
€16.0M
+15.6%
Expected: €16.4M
71.2
Antonio Vergara
SSC Napoli • 23 years old
€13.0M
€15.0M
+15.6%
Expected: €14.6M
70.0
Eljif Elmas
SSC Napoli • 26 years old
€11.2M
€13.0M
+15.6%
67.7
Jens Odgaard
Bologna Football Club 1909 • 27 years old
€10.4M
€12.0M
+15.6%
66.3
Luis Alberto
Società Sportiva Lazio S.p.A. • 33 years old
€14.2M
€11.0M
-22.6%
65.8
Giovanni Fabbian
Bologna Football Club 1909 • 23 years old
€8.6M
€10.0M
+15.6%
61.4
Cristian Volpato
US Sassuolo • 22 years old
€8.6M
€10.0M
+15.6%
60.9
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Sign up freeNico Paz
Como 1907 · 22 years old
93.5
ASI
Current Value
€80.0M
% Change
+15.6%
1yr Forecast Range
€67.7M - €88.0M
Martin Baturina
Como 1907 · 23 years old
78.6
ASI
Current Value
€30.0M
% Change
+15.6%
1yr Forecast Range
€24.4M - €31.7M
Charles De Ketelaere
Atalanta BC · 25 years old
78.6
ASI
Current Value
€30.0M
% Change
+15.6%
1yr Forecast Range
€25.8M - €33.5M
Lazar Samardžić
Atalanta BC · 24 years old
71.2
ASI
Current Value
€16.0M
% Change
+15.6%
1yr Forecast Range
€14.3M - €18.5M
Antonio Vergara
SSC Napoli · 23 years old
70.0
ASI
Current Value
€15.0M
% Change
+15.6%
1yr Forecast Range
€12.7M - €16.4M
Eljif Elmas
SSC Napoli · 26 years old
67.7
ASI
Current Value
€13.0M
% Change
+15.6%
1yr Forecast Range
Jens Odgaard
Bologna Football Club 1909 · 27 years old
66.3
ASI
Current Value
€12.0M
% Change
+15.6%
1yr Forecast Range
Luis Alberto
Società Sportiva Lazio S.p.A. · 33 years old
65.8
ASI
Current Value
€11.0M
% Change
-22.6%
1yr Forecast Range
Giovanni Fabbian
Bologna Football Club 1909 · 23 years old
61.4
ASI
Current Value
€10.0M
% Change
+15.6%
1yr Forecast Range
Cristian Volpato
US Sassuolo · 22 years old
60.9
ASI
Current Value
€10.0M
% Change
+15.6%
1yr Forecast Range
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Sign up freeAge Distribution: Serie A Attacking Midfielders
The Serie A CAM market shows 5 distinct age segments, with the largest cohort in the 30+ bracket (33 players, 38% of market). The 21-23 age group holds the most value at €159.4M, averaging €15.9M per player.
Top Attacking Midfielders by Age Bracket
U21 Years (11 players)
21-23 Years (10 players)
24-26 Years (20 players)
27-29 Years (13 players)
Market Value Distribution
Elite Tier Concentration
The top 9 Attacking Midfielders (10% of players) control €217.0M
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 5 Attacking Midfielders worth €112.3M (averaging €22.5M per player). The top 10 clubs account for 47% of tracked Attacking Midfielders.
Como 1907 (5 Attacking Midfielders)
Atalanta BC (5 Attacking Midfielders)
SSC Napoli (3 Attacking Midfielders)
Società Sportiva Lazio S.p.A. (6 Attacking Midfielders)
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 50.00×. That means Charles De Ketelaere is valued 50.00× 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 26.67× PPVE. Third is Daniel Maldini of Società Sportiva Lazio S.p.A., who is 24 years old with a 15.00× 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 50.00× means the player is worth 4900% 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 | €30.0M | €600K | 50.00x |
| #2 | Lazar Samardžić Atalanta BC | 24 | 24-26 | €16.0M | €600K | 26.67x |
| #3 | Daniel Maldini Società Sportiva Lazio S.p.A. | 24 | 24-26 | €9.0M | €600K | 15.00x |
| #4 | Nico Paz Como 1907 | 22 | 21-23 | €80.0M | €10.0M | 8.00x |
| #5 | Tomas Suslov Hellas Verona | 24 | 24-26 | €4.0M | €600K | 6.67x |
| #6 | Vasilije Adžić Juventus FC | 20 | U21 | €8.0M | €1.2M | 6.67x |
| #7 | Adrian Przyborek Società Sportiva Lazio S.p.A. | 19 | U21 | €6.0M | €1.2M | 5.00x |
| #8 | Alphadjo Cissè Hellas Verona | 19 | U21 | €6.0M | €1.2M | 5.00x |
| #9 | Simone Pafundi Udinese Calcio | 20 | U21 | €5.0M | €1.2M | 4.17x |
| #10 | Martin Baturina Como 1907 | 23 | 21-23 | €30.0M | €10.0M | 3.00x |
| #11 | Filip Marchwinski US Lecce | 24 | 24-26 | €1.5M | €600K | 2.50x |
| #12 | Antonio Vergara SSC Napoli | 23 | 21-23 | €15.0M | €10.0M | 1.50x |
| #13 | Sergiu Perciun Torino FC | 20 | U21 | €1.5M | €1.2M | 1.25x |
| #14 | Giacomo Olzer AC Milan | 25 | 24-26 | €600K | €600K | 1.00x |
| #15 | Krisztofer Horváth Torino FC | 24 | 24-26 | €600K | €600K | 1.00x |
| #16 | Giovanni Fabbian Bologna Football Club 1909 | 23 | 21-23 | €10.0M | €10.0M | 1.00x |
| #17 | Cristian Volpato US Sassuolo | 22 | 21-23 | €10.0M | €10.0M | 1.00x |
| #18 | Tommaso Rubino ACF Fiorentina | 19 | U21 | €1.2M | €1.2M | 1.00x |
| #19 | Tommaso Baldanzi Associazione Sportiva Roma | 23 | 21-23 | €8.5M | €10.0M | 0.85x |
| #20 | David Pejičić Udinese Calcio | 19 | U21 | €1.0M | €1.2M | 0.83x |
Return-to-Peak Potential (RPP)
Recovery potential from current value to forecasted peak. Shows how much upside remains for players approaching their prime.
Unlock Return-to-Peak analysis for Serie A Attacking Midfielders.
Upgrade to FanRisk-Adjusted Upside (RAU)
Upside potential weighted against forecast uncertainty. Higher RAU = better risk-reward profile.
Unlock Risk-Adjusted Upside for Serie A Attacking Midfielders.
Upgrade to FanRoster Pressure Index (RPI)
Squad depth pressure based on Z-score distribution. Negative RPI = thin depth, positive = deep roster.
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Upgrade to FanAge-Share Concentration (ASC)
Identifies players capturing disproportionate value relative to age group representation. Positive ASC = value concentration.
Unlock Age-Share Concentration for Serie A Attacking Midfielders.
Upgrade to FanBuy-Now vs Wait-List Map
Categorizes players by age position and upside potential to guide timing of acquisition.
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Upgrade to FanPrice vs Peer Z-Score
IQR-based pricing analysis relative to position peers. Identifies over/undervalued players vs market.
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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 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: 27 years (technical skill and tactical awareness)
Decline Rate: Widening steps, not a flat rate: about -5% at 28, -10% at 29, steeper from 30 (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: Compounding and banded around a peak of 27: +25%/year through age 21, +15% at 22-23, +10% up to the year before peak, then -5%, -10% and steeper with each later band. Growth is damped above €30M.
• 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 2026-27 season
Who are the most valuable Attacking Midfielders in the Serie A in 2026-27?
The most valuable attacking midfielder in the Serie A in 2026-27 is Nico Paz, who is worth €80.0M and plays for Como 1907. The second most valuable is Martin Baturina (€30.0M, Como 1907), followed by Charles De Ketelaere (€30.0M, Atalanta BC). Our database tracks 87 Serie A Attacking Midfielders with comprehensive market valuations updated for the 2026-27 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 27, in line with other midfielders. In our valuation model, value then falls in widening steps rather than at a flat annual rate: around -5% at 28, -10% at 29, and steeper from 30. This position demands high technical ability, creativity, and burst acceleration. 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: €80.0M), estimated transfer fees would range from €64.0M to €112.0M 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 compound gains toward their position's peak age, up to +25% a year through age 21 and easing as they approach it, while post-peak players fall in widening steps), 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 2026-27 season to ensure accuracy for recruitment and investment decisions.
