Best Attacking Midfielders in the Superliga (Jul 2026)
Ranked by Analytical Strength Index
Market Overview: Superliga Attacking Midfielders 2022-23
Our database tracked 46 Superliga Attacking Midfielders in the 2022-23 season, representing 27 clubs with a combined market value of €28.9M. The average market value for Superliga Attacking Midfielders was €629K, with the average age at 30 years old.
The most valuable attacking midfielder in the Superliga was Oscar Schwartau, worth €3.5M and played for Bröndby IF at 20 years old. The top 5 Attacking Midfielders averaged €2.3M in market value, including Alexandru Cicâldău and Callum McCowatt.
Age distribution showed the youngest tracked attacking midfielder was Oscar Schwartau (20 years, Bröndby IF, €3.5M), while the oldest was Dan Nistor (38 years, FC Universitatea Cluj, €650K). Research shows Attacking Midfielders typically peak at age 26.
Historical analysis showed 14 Attacking Midfielders (30%) increased in market value over the following 12 months based on age-curve trajectories, then-current performance trends, and playing time analysis. The Superliga market for Attacking Midfielders remained actively developing with emerging talent in the 2022-23 season.
Explore Market Size by Position in Superliga
Interactive bubble chart showing predicted 2-year growth vs current age for all Superliga Attacking Midfielders. Identify undervalued assets and track market momentum across 27 clubs with €28.9M 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: Superliga Attacking Midfielders
The Superliga CAM market shows 5 distinct age segments, with the largest cohort in the 30+ bracket (26 players, 57% of market). The 30+ age group holds the most value at €10.5M, averaging €406K per player.
Top Attacking Midfielders by Age Bracket
U21 Years (2 players)
21-23 Years (2 players)
24-26 Years (10 players)
27-29 Years (6 players)
Market Value Distribution
Elite Tier Concentration
The top 5 Attacking Midfielders (11% of players) control €11.7M
Market Tiers
Market structure shows concentrated value with emerging (<€5m) tier representing 100% of the Superliga CAM pool.
Emerging (<€5M)
Club Distribution: Superliga Attacking Midfielders
Among 27 Superliga clubs, Bröndby IF leads with 5 Attacking Midfielders worth €5.0M (averaging €1.0M per player). The top 10 clubs account for 54% of tracked Attacking Midfielders.
Bröndby IF (5 Attacking Midfielders)
Silkeborg IF (3 Attacking Midfielders)
Universitatea Craiova (2 Attacking Midfielders)
FC Nordsjaelland (4 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.
Oscar Schwartau
Bröndby IF • 20 years old
€3.0M
€3.5M
+15.6%
Expected: €4.0M
46.6
Alexandru Cicâldău
Universitatea Craiova • 29 years old
€3.9M
€3.0M
-22.6%
Expected: €2.5M
41.8
Callum McCowatt
Silkeborg IF • 27 years old
€2.1M
€2.0M
-5.4%
Expected: €1.8M
36.6
Younes Bakiz
Silkeborg IF • 27 years old
€1.8M
€1.7M
-5.4%
Expected: €1.5M
34.5
László Kleinheisler
FK Csikszereda Miercurea Ciuc • 32 years old
€1.9M
€1.5M
-22.6%
Expected: €1.3M
33.5
Zidan Sertdemir
FC Nordsjaelland • 21 years old
€1.0M
€1.2M
+15.6%
Expected: €1.3M
30.3
Rami Al Hajj
Silkeborg IF • 24 years old
€865K
€1.0M
+15.6%
Expected: €1.0M
28.8
Paul-José Mpoku
UTA Arad • 34 years old
€1.2M
€900K
-22.6%
Expected: €788K
27.4
Gylfi Sigurdsson
Lyngby Boldklub • 36 years old
€968K
€750K
-22.6%
Expected: €656K
25.3
Dan Nistor
FC Universitatea Cluj • 38 years old
€839K
€650K
-22.6%
Expected: €569K
25.2
Mads Frøkjær
Bröndby IF • 26 years old
€692K
€800K
+15.6%
Expected: €824K
25.0
Mike Themsen
Randers FC • 20 years old
€692K
€800K
+15.6%
Expected: €917K
24.6
Georgi Milanov
FC Dinamo 1948 • 34 years old
€904K
€700K
-22.6%
Expected: €613K
24.3
Xian Emmers
ACSC FC Arges • 26 years old
€605K
€700K
+15.6%
Expected: €721K
23.4
Jasurbek Jaloliddinov
Sogdiana Jizzakh • 24 years old
€519K
€600K
+15.6%
Expected: €614K
22.7
José Gallegos
Sönderjyske Fodbold • 24 years old
€432K
€500K
+15.6%
Expected: €512K
20.1
Desley Ubbink
FC Metaloglobus Bucharest • 33 years old
€646K
€500K
-22.6%
Expected: €438K
20.0
Hervin Ongenda
FC Botosani • 31 years old
€646K
€500K
-22.6%
Expected: €415K
19.7
Fiete Arp
Odense Boldklub • 26 years old
€432K
€500K
+15.6%
Expected: €515K
19.2
João Amaral
ACSM Politehnica Iasi • 34 years old
€581K
€450K
-22.6%
Expected: €394K
18.8
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)
Silkeborg IF's Rami Al Hajj at 24 years old has the highest Pre-Peak Value Efficiency at 1.67×. That means Rami Al Hajj is valued 1.67× higher than the median player in the 24-26 age bracket-representing exceptional value before reaching peak age.
In second is Sogdiana Jizzakh's Jasurbek Jaloliddinov, who is 24 years old, with a 1.00× PPVE. Third is Zidan Sertdemir of FC Nordsjaelland, who is 21 years old with a 1.00× 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 1.67× means the player is worth 67% 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 | Rami Al Hajj Silkeborg IF | 24 | 24-26 | €1.0M | €600K | 1.67× |
| #2 | Jasurbek Jaloliddinov Sogdiana Jizzakh | 24 | 24-26 | €600K | €600K | 1.00× |
| #3 | Zidan Sertdemir FC Nordsjaelland | 21 | 21-23 | €1.2M | €1.2M | 1.00× |
| #4 | Oscar Schwartau Bröndby IF | 20 | U21 | €3.5M | €3.5M | 1.00× |
| #5 | José Gallegos Sönderjyske Fodbold | 24 | 24-26 | €500K | €600K | 0.83× |
| #6 | Mike Themsen Randers FC | 20 | U21 | €800K | €3.5M | 0.23× |
| #7 | Bertram Kvist Bröndby IF | 21 | 21-23 | €200K | €1.2M | 0.17× |
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)
Bröndby IF's Oscar Schwartau at 20 years old has the highest Return-to-Peak Potential at +35%. That means Oscar Schwartau is projected to appreciate 35% as they reach their peak age in 6 years-representing significant upside before entering their prime.
In second is Randers FC's Mike Themsen, who is 20 years old, with a +35% RPP (6 years to peak). Third is Zidan Sertdemir of FC Nordsjaelland, who is 21 years old with a +30% RPP (5 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 35% RPP means the player is expected to gain 35% 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 | Oscar Schwartau Bröndby IF | 20 | 6 | €3.5M | €5.4M | +35% |
| #2 | Mike Themsen Randers FC | 20 | 6 | €800K | €1.2M | +35% |
| #3 | Zidan Sertdemir FC Nordsjaelland | 21 | 5 | €1.2M | €1.7M | +30% |
| #4 | Bertram Kvist Bröndby IF | 21 | 5 | €200K | €287K | +30% |
| #5 | Jasurbek Jaloliddinov Sogdiana Jizzakh | 24 | 2 | €600K | €694K | +14% |
| #6 | Rami Al Hajj Silkeborg IF | 24 | 2 | €1.0M | €1.2M | +14% |
| #7 | José Gallegos Sönderjyske Fodbold | 24 | 2 | €500K | €578K | +14% |
Risk-Adjusted Upside (RAU)
Upside potential weighted against forecast uncertainty. Higher RAU = better risk-reward profile.
Understanding Risk-Adjusted Upside (RAU)
Randers FC's Mike Themsen has the highest Risk-Adjusted Upside at 42.8. That means Mike Themsen has 15% upside potential with only 0% forecast uncertainty-representing excellent risk-reward for value appreciation.
In second is Bröndby IF's Oscar Schwartau with a 42.8 RAU (15% upside, 0% uncertainty). Third is Zidan Sertdemir of FC Nordsjaelland with a 31.1 RAU (10% upside, 0% uncertainty).
How RAU is calculated: RAU divides upside potential by forecast uncertainty (RAU = Upside % ÷ Uncertainty %). A RAU of 42.8 means the upside is 42.8× 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 | Mike Themsen Randers FC | €917K | €780K-1.1M | +15% | 42.8 |
| #2 | Oscar Schwartau Bröndby IF | €4.0M | €3.4M-4.6M | +15% | 42.8 |
| #3 | Zidan Sertdemir FC Nordsjaelland | €1.3M | €1.1M-1.5M | +10% | 31.1 |
| #4 | Bertram Kvist Bröndby IF | €221K | €188K-253K | +10% | 31.1 |
| #5 | Ágúst Hlynsson AC Horsens | €154K | €134K-175K | +3% | 11.1 |
| #6 | Christian Tue Jensen FC Midtjylland | €154K | €134K-175K | +3% | 11.1 |
| #7 | Emilio Simonsen FC Fredericia | €154K | €134K-175K | +3% | 11.1 |
| #8 | Xian Emmers ACSC FC Arges | €721K | €627K-814K | +3% | 11.1 |
| #9 | Mads Frøkjær Bröndby IF | €824K | €717K-931K | +3% | 11.1 |
| #10 | Masaki Murata Vejle Boldklub | €412K | €358K-465K | +3% | 11.1 |
| #11 | Fiete Arp Odense Boldklub | €515K | €448K-582K | +3% | 11.1 |
| #12 | Rami Al Hajj Silkeborg IF | €1.0M | €891K-1.2M | +2% | 9.1 |
| #13 | José Gallegos Sönderjyske Fodbold | €512K | €445K-579K | +2% | 9.1 |
| #14 | Jasurbek Jaloliddinov Sogdiana Jizzakh | €614K | €522K-707K | +2% | 7.8 |
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)
FC Dinamo 1948's Georgi Milanov in the 30+ age bracket has the highest Age-Share Concentration at +-20.1%. That means László Kleinheisler captures 36.4% of total market value while representing only 56.5% of players in their age group-showing dominant elite status.
In second is FC Midtjylland's Marco Larsen with a +-20.1% ASC (36.4% value share vs 56.5% player share in 30+ bracket). Third is Ferhan Hasani of Bröndby IF with a +-20.1% ASC (36.4% value vs 56.5% players in 30+ bracket).
How ASC is calculated: ASC = (% of total value) - (% of total players) in age bracket. A +-20.1% ASC means the player captures -20.1% 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 | Georgi Milanov FC Dinamo 1948 | 30+ | 36.4% | 56.5% | -20.1% |
| #2 | Marco Larsen FC Midtjylland | 30+ | 36.4% | 56.5% | -20.1% |
| #3 | Ferhan Hasani Bröndby IF | 30+ | 36.4% | 56.5% | -20.1% |
| #4 | Besar Halimi Bröndby IF | 30+ | 36.4% | 56.5% | -20.1% |
| #5 | Dan Nistor FC Universitatea Cluj | 30+ | 36.4% | 56.5% | -20.1% |
| #6 | Hervin Ongenda FC Botosani | 30+ | 36.4% | 56.5% | -20.1% |
| #7 | Simon Kroon Sönderjyske Fodbold | 30+ | 36.4% | 56.5% | -20.1% |
| #8 | Diego Montiel Vejle Boldklub | 30+ | 36.4% | 56.5% | -20.1% |
| #9 | László Kleinheisler FK Csikszereda Miercurea Ciuc | 30+ | 36.4% | 56.5% | -20.1% |
| #10 | Lyes Houri Universitatea Craiova | 30+ | 36.4% | 56.5% | -20.1% |
| #11 | Souheib Dhaflaoui FC Nordsjaelland | 30+ | 36.4% | 56.5% | -20.1% |
| #12 | Cristian Benavente ASFC Buzau (2016-2025) | 30+ | 36.4% | 56.5% | -20.1% |
| #13 | Nathan Oduwa Vejle Boldklub | 30+ | 36.4% | 56.5% | -20.1% |
| #14 | Christian Jakobsen Hvidovre IF | 30+ | 36.4% | 56.5% | -20.1% |
| #15 | Tobias Christensen FC Helsingör | 30+ | 36.4% | 56.5% | -20.1% |
| #16 | Desley Ubbink FC Metaloglobus Bucharest | 30+ | 36.4% | 56.5% | -20.1% |
| #17 | Pedro Nuno SC Otelul Galati | 30+ | 36.4% | 56.5% | -20.1% |
| #18 | Yann Rolim Aalborg BK | 30+ | 36.4% | 56.5% | -20.1% |
| #19 | Rawez Lawan FC Nordsjaelland | 30+ | 36.4% | 56.5% | -20.1% |
| #20 | João Amaral ACSM Politehnica Iasi | 30+ | 36.4% | 56.5% | -20.1% |
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: 0 immediate targets, 4 standard acquisitions, 0 watch-list prospects, 15 at peak.
BUY NOW - High Upside
No players in this category
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 €3.5M. 0 undervalued, 2 premium.
Value Positioning vs Peers
| Player | Market Value | Position Median | Z-Score | Assessment |
|---|---|---|---|---|
Mike Themsen Randers FC | €800K | €400K | -1.00 | Good Value |
Bertram Kvist Bröndby IF | €200K | €400K | -1.00 | Good Value |
Rezan Corlu Lyngby Boldklub | €300K | €400K | -0.82 | Good Value |
Alen Mustafic Odense Boldklub | €300K | €400K | -0.82 | Good Value |
Dmitriy Pletnev Bunyodkor Tashkent | €450K | €400K | -0.74 | Good Value |
Ágúst Hlynsson AC Horsens | €150K | €400K | -0.64 | Good Value |
Christian Tue Jensen FC Midtjylland | €150K | €400K | -0.64 | Good Value |
Emilio Simonsen FC Fredericia | €150K | €400K | -0.64 | Good Value |
Diego Montiel Vejle Boldklub | €150K | €400K | -0.50 | Fair Value |
Tobias Christensen FC Helsingör | €150K | €400K | -0.50 | Fair Value |
Rawez Lawan FC Nordsjaelland | €150K | €400K | -0.50 | Fair Value |
Mathias Gehrt Hvidovre IF | €150K | €400K | -0.50 | Fair Value |
Marco Larsen FC Midtjylland | €200K | €400K | -0.33 | Fair Value |
Simon Kroon Sönderjyske Fodbold | €200K | €400K | -0.33 | Fair Value |
Pedro Nuno SC Otelul Galati | €200K | €400K | -0.33 | Fair Value |
Felipe Tontini FC Helsingör | €200K | €400K | -0.33 | Fair Value |
Masaki Murata Vejle Boldklub | €400K | €400K | -0.18 | Fair Value |
Ferhan Hasani Bröndby IF | €250K | €400K | -0.17 | Fair Value |
Souheib Dhaflaoui FC Nordsjaelland | €250K | €400K | -0.17 | Fair Value |
Yann Rolim Aalborg BK | €250K | €400K | -0.17 | Fair Value |
How We Rank Superliga 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 Superliga 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 Superliga 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%)
Superliga competition level factored into comparative strength assessment.
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 Superliga Attacking Midfielders in the 2022-23 season
Who are the most valuable Attacking Midfielders in the Superliga in 2022-23?
The most valuable attacking midfielder in the Superliga in 2022-23 is Oscar Schwartau, who is worth €3.5M and plays for Bröndby IF. The second most valuable is Alexandru Cicâldău (€3.0M, Universitatea Craiova), followed by Callum McCowatt (€2.0M, Silkeborg IF). Our database tracks 46 Superliga Attacking Midfielders with comprehensive market valuations updated for the 2022-23 season.
How are Superliga Attacking Midfielders ranked?
Superliga 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 Superliga 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 Superliga?
Transfer fees for Superliga Attacking Midfielders vary significantly based on market value, contract length, and club bargaining position. For the top-ranked attacking midfielder Oscar Schwartau (market value: €3.5M), estimated transfer fees would range from €2.8M to €4.9M 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 Superliga transactions.
What is the value forecast for Superliga Attacking Midfielders?
Our 1-year forecast model projects market value changes for Superliga 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 Superliga attacking midfielder data come from?
Our Superliga 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 Superliga sources and updated monthly for the 2022-23 season to ensure accuracy for recruitment and investment decisions.