Best Left Wingers in the Superliga (Jul 2026)
Ranked by Analytical Strength Index
Market Overview: Superliga Left Wingers 2022-23
Our database tracked 62 Superliga Left Wingers in the 2022-23 season, representing 30 clubs with a combined market value of €47.5M. The average market value for Superliga Left Wingers was €767K, with the average age at 28 years old.
The most valuable left winger in the Superliga was Aral Şimşir, worth €6.0M and played for FC Midtjylland at 24 years old. The top 5 Left Wingers averaged €4.4M in market value, including Kristian Arnstad and Nicolai Vallys.
Age distribution showed the youngest tracked left winger was Mikel Gogorza (19 years, FC Midtjylland, €3.0M), while the oldest was Johan Absalonsen (40 years, Sönderjyske Fodbold, €200K). Research shows Left Wingers typically peak at age 26.
Historical analysis showed 22 Left Wingers (35%) 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 Left Wingers 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 Left Wingers. Identify undervalued assets and track market momentum across 30 clubs with €47.5M 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: Superliga Left Wingers
The Superliga LW market shows 5 distinct age segments, with the largest cohort in the 30+ bracket (20 players, 32% of market). The 21-23 age group holds the most value at €13.6M, averaging €1.0M per player.
Top Left Wingers by Age Bracket
U21 Years (3 players)
21-23 Years (13 players)
24-26 Years (10 players)
27-29 Years (16 players)
Market Value Distribution
Elite Tier Concentration
The top 7 Left Wingers (11% of players) control €25.7M
Market Tiers
Market structure shows distributed value with mid (€5-15m) tier representing 3% of the Superliga LW pool.
Mid (€5-15M)
Emerging (<€5M)
Club Distribution: Superliga Left Wingers
Among 30 Superliga clubs, FC Midtjylland leads with 6 Left Wingers worth €9.9M (averaging €1.7M per player). The top 10 clubs account for 53% of tracked Left Wingers.
FC Midtjylland (6 Left Wingers)
Aarhus GF (4 Left Wingers)
FC Copenhagen (2 Left Wingers)
Bröndby IF (1 Left Wingers)
Player Rankings
Ranked by Analytical Strength Index. Click any player to view full profile, or click the chart icon to see value history.
Aral Şimşir
FC Midtjylland • 24 years old
€5.2M
€6.0M
+15.6%
Expected: €6.1M
54.4
Kristian Arnstad
Aarhus GF • 22 years old
€4.3M
€5.0M
+15.6%
Expected: €5.3M
53.1
Nicolai Vallys
Bröndby IF • 29 years old
€5.8M
€4.5M
-22.6%
Expected: €3.7M
49.9
Elias Achouri
FC Copenhagen • 27 years old
€3.7M
€3.5M
-5.4%
Expected: €3.0M
46.9
Mikel Gogorza
FC Midtjylland • 19 years old
€2.6M
€3.0M
+15.6%
Expected: €3.6M
40.4
Robert
FC Copenhagen • 21 years old
€1.9M
€2.2M
+15.6%
Expected: €2.4M
38.4
Olti Hyseni
Sönderjyske Fodbold • 19 years old
€1.3M
€1.5M
+15.6%
Expected: €1.8M
32.0
Khozhimat Erkinov
Pakhtakor Tashkent • 25 years old
€1.1M
€1.3M
+15.6%
Expected: €1.3M
31.6
Oliver Ross
Silkeborg IF • 21 years old
€1.0M
€1.2M
+15.6%
Expected: €1.3M
31.1
Alexander Lyng
Sönderjyske Fodbold • 21 years old
€1.0M
€1.2M
+15.6%
Expected: €1.3M
31.1
Charly Nouck
Viborg FF • 22 years old
€865K
€1.0M
+15.6%
Expected: €1.1M
29.8
Mathias Greve
Randers FC • 31 years old
€1.2M
€900K
-22.6%
Expected: €738K
26.5
Ruslanbek Jiyanov
Navbahor Namangan • 25 years old
€649K
€750K
+15.6%
Expected: €733K
24.7
Tosin Kehinde
Randers FC • 28 years old
€968K
€750K
-22.6%
Expected: €649K
24.4
Tobias Bach
Aarhus GF • 23 years old
€562K
€650K
+15.6%
Expected: €696K
24.1
Yonis Njoh
Viborg FF • 22 years old
€476K
€550K
+15.6%
Expected: €582K
22.5
Mohammed Kamara
CFR Cluj • 28 years old
€775K
€600K
-22.6%
Expected: €519K
21.7
Valentin Gheorghe
Petrolul Ploiesti • 29 years old
€710K
€550K
-22.6%
Expected: €451K
20.6
Andres Sfait
CFR Cluj • 21 years old
€432K
€500K
+15.6%
Expected: €551K
20.5
Luan Campos
SC Otelul Galati • 24 years old
€432K
€500K
+15.6%
Expected: €512K
20.4
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)
FC Midtjylland's Aral Şimşir at 24 years old has the highest Pre-Peak Value Efficiency at 12.00×. That means Aral Şimşir is valued 12.00× higher than the median player in the 24-26 age bracket-representing exceptional value before reaching peak age.
In second is Aarhus GF's Kristian Arnstad, who is 22 years old, with a 9.09× PPVE. Third is Robert of FC Copenhagen, who is 21 years old with a 4.00× 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 12.00× means the player is worth 1100% 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 | Aral Şimşir FC Midtjylland | 24 | 24-26 | €6.0M | €500K | 12.00× |
| #2 | Kristian Arnstad Aarhus GF | 22 | 21-23 | €5.0M | €550K | 9.09× |
| #3 | Robert FC Copenhagen | 21 | 21-23 | €2.2M | €550K | 4.00× |
| #4 | Khozhimat Erkinov Pakhtakor Tashkent | 25 | 24-26 | €1.3M | €500K | 2.60× |
| #5 | Oliver Ross Silkeborg IF | 21 | 21-23 | €1.2M | €550K | 2.18× |
| #6 | Alexander Lyng Sönderjyske Fodbold | 21 | 21-23 | €1.2M | €550K | 2.18× |
| #7 | Mikel Gogorza FC Midtjylland | 19 | U21 | €3.0M | €1.5M | 2.00× |
| #8 | Charly Nouck Viborg FF | 22 | 21-23 | €1.0M | €550K | 1.82× |
| #9 | Ruslanbek Jiyanov Navbahor Namangan | 25 | 24-26 | €750K | €500K | 1.50× |
| #10 | Tobias Bach Aarhus GF | 23 | 21-23 | €650K | €550K | 1.18× |
| #11 | Olti Hyseni Sönderjyske Fodbold | 19 | U21 | €1.5M | €1.5M | 1.00× |
| #12 | Yonis Njoh Viborg FF | 22 | 21-23 | €550K | €550K | 1.00× |
| #13 | Luan Campos SC Otelul Galati | 24 | 24-26 | €500K | €500K | 1.00× |
| #14 | Andres Sfait CFR Cluj | 21 | 21-23 | €500K | €550K | 0.91× |
| #15 | Magnus Kaastrup Lyngby Boldklub | 25 | 24-26 | €375K | €500K | 0.75× |
| #16 | Markus Jensen Odense Boldklub | 21 | 21-23 | €350K | €550K | 0.64× |
| #17 | Noah Shamoun Randers FC | 23 | 21-23 | €300K | €550K | 0.55× |
| #18 | Gustav Christensen FC Midtjylland | 21 | 21-23 | €300K | €550K | 0.55× |
| #19 | Brandon Pierrick Vejle Boldklub | 24 | 24-26 | €200K | €500K | 0.40× |
| #20 | Oucasse Mendy FC Universitatea Cluj | 25 | 24-26 | €150K | €500K | 0.30× |
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)
Aarhus GF's Frederik Emmery at 19 years old has the highest Return-to-Peak Potential at +40%. That means Frederik Emmery is projected to appreciate 40% as they reach their peak age in 7 years-representing significant upside before entering their prime.
In second is Sönderjyske Fodbold's Olti Hyseni, who is 19 years old, with a +40% RPP (7 years to peak). Third is Mikel Gogorza of FC Midtjylland, 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 | Frederik Emmery Aarhus GF | 19 | 7 | €350K | €582K | +40% |
| #2 | Olti Hyseni Sönderjyske Fodbold | 19 | 7 | €1.5M | €2.5M | +40% |
| #3 | Mikel Gogorza FC Midtjylland | 19 | 7 | €3.0M | €5.0M | +40% |
| #4 | Markus Jensen Odense Boldklub | 21 | 5 | €350K | €503K | +30% |
| #5 | Andres Sfait CFR Cluj | 21 | 5 | €500K | €719K | +30% |
| #6 | Gustav Christensen FC Midtjylland | 21 | 5 | €300K | €431K | +30% |
| #7 | Oliver Ross Silkeborg IF | 21 | 5 | €1.2M | €1.7M | +30% |
| #8 | Alexander Lyng Sönderjyske Fodbold | 21 | 5 | €1.2M | €1.7M | +30% |
| #9 | Robert FC Copenhagen | 21 | 5 | €2.2M | €3.2M | +30% |
| #10 | Kristian Arnstad Aarhus GF | 22 | 4 | €5.0M | €6.7M | +25% |
| #11 | Obule Moses FC Midtjylland | 22 | 4 | €150K | €201K | +25% |
| #12 | Enock Otoo Lyngby Boldklub | 22 | 4 | €150K | €201K | +25% |
| #13 | Charly Nouck Viborg FF | 22 | 4 | €1.0M | €1.3M | +25% |
| #14 | Yonis Njoh Viborg FF | 22 | 4 | €550K | €735K | +25% |
| #15 | Noah Shamoun Randers FC | 23 | 3 | €300K | €373K | +20% |
| #16 | Tobias Bach Aarhus GF | 23 | 3 | €650K | €808K | +20% |
| #17 | Aral Şimşir FC Midtjylland | 24 | 2 | €6.0M | €6.9M | +14% |
| #18 | Luan Campos SC Otelul Galati | 24 | 2 | €500K | €578K | +14% |
| #19 | Brandon Pierrick Vejle Boldklub | 24 | 2 | €200K | €231K | +14% |
| #20 | Oucasse Mendy FC Universitatea Cluj | 25 | 1 | €150K | €161K | +7% |
Risk-Adjusted Upside (RAU)
Upside potential weighted against forecast uncertainty. Higher RAU = better risk-reward profile.
Understanding Risk-Adjusted Upside (RAU)
Aarhus GF's Frederik Emmery has the highest Risk-Adjusted Upside at 38.7. That means Frederik Emmery has 19% upside potential with only 0% forecast uncertainty-representing excellent risk-reward for value appreciation.
In second is Sönderjyske Fodbold's Olti Hyseni with a 38.7 RAU (19% upside, 0% uncertainty). Third is Mikel Gogorza of FC Midtjylland with a 38.7 RAU (19% upside, 0% uncertainty).
How RAU is calculated: RAU divides upside potential by forecast uncertainty (RAU = Upside % ÷ Uncertainty %). A RAU of 38.7 means the upside is 38.7× 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 | Frederik Emmery Aarhus GF | €417K | €330K-503K | +19% | 38.7 |
| #2 | Olti Hyseni Sönderjyske Fodbold | €1.8M | €1.4M-2.2M | +19% | 38.7 |
| #3 | Mikel Gogorza FC Midtjylland | €3.6M | €2.8M-4.3M | +19% | 38.7 |
| #4 | Markus Jensen Odense Boldklub | €386K | €306K-466K | +10% | 22.5 |
| #5 | Andres Sfait CFR Cluj | €551K | €437K-665K | +10% | 22.5 |
| #6 | Gustav Christensen FC Midtjylland | €331K | €262K-399K | +10% | 22.5 |
| #7 | Oliver Ross Silkeborg IF | €1.3M | €1.0M-1.6M | +10% | 22.5 |
| #8 | Alexander Lyng Sönderjyske Fodbold | €1.3M | €1.0M-1.6M | +10% | 22.5 |
| #9 | Robert FC Copenhagen | €2.4M | €1.9M-2.9M | +10% | 22.5 |
| #10 | Noah Shamoun Randers FC | €321K | €263K-379K | +7% | 18.3 |
| #11 | Tobias Bach Aarhus GF | €696K | €571K-821K | +7% | 18.3 |
| #12 | Obule Moses FC Midtjylland | €159K | €130K-187K | +6% | 15.3 |
| #13 | Enock Otoo Lyngby Boldklub | €159K | €130K-187K | +6% | 15.3 |
| #14 | Charly Nouck Viborg FF | €1.1M | €868K-1.2M | +6% | 15.3 |
| #15 | Kristian Arnstad Aarhus GF | €5.3M | €4.3M-6.2M | +6% | 15.3 |
| #16 | Yonis Njoh Viborg FF | €582K | €477K-687K | +6% | 15.3 |
| #17 | Oliver Klitten Aalborg BK | €309K | €253K-364K | +3% | 8.0 |
| #18 | Jubril Adedeji Aalborg BK | €309K | €253K-364K | +3% | 8.0 |
| #19 | Dennis Politic FCSB | €257K | €211K-304K | +3% | 8.0 |
| #20 | Brandon Pierrick Vejle Boldklub | €205K | €168K-242K | +2% | 6.5 |
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: left winger 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)
Hobro IK's Wilfried Domoraud in the 30+ age bracket has the highest Age-Share Concentration at +-19.4%. That means Mathias Greve captures 12.8% of total market value while representing only 32.3% of players in their age group-showing dominant elite status.
In second is Aalborg BK's Lucas Andersen with a +-19.4% ASC (12.8% value share vs 32.3% player share in 30+ bracket). Third is Aron Sigurdarson of AC Horsens with a +-19.4% ASC (12.8% value vs 32.3% players in 30+ bracket).
How ASC is calculated: ASC = (% of total value) - (% of total players) in age bracket. A +-19.4% ASC means the player captures -19.4% 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 | Wilfried Domoraud Hobro IK | 30+ | 12.8% | 32.3% | -19.4% |
| #2 | Lucas Andersen Aalborg BK | 30+ | 12.8% | 32.3% | -19.4% |
| #3 | Aron Sigurdarson AC Horsens | 30+ | 12.8% | 32.3% | -19.4% |
| #4 | Emmanuel Okwi Sönderjyske Fodbold | 30+ | 12.8% | 32.3% | -19.4% |
| #5 | Adnane Tighadouini Esbjerg fB | 30+ | 12.8% | 32.3% | -19.4% |
| #6 | Ninos Gouriye Vendsyssel FF | 30+ | 12.8% | 32.3% | -19.4% |
| #7 | Jung-bin Park Viborg FF | 30+ | 12.8% | 32.3% | -19.4% |
| #8 | Johan Absalonsen Sönderjyske Fodbold | 30+ | 12.8% | 32.3% | -19.4% |
| #9 | Milan Jevtovic Aarhus GF | 30+ | 12.8% | 32.3% | -19.4% |
| #10 | Mathias Greve Randers FC | 30+ | 12.8% | 32.3% | -19.4% |
| #11 | Musefiu Ashiru FC Midtjylland | 30+ | 12.8% | 32.3% | -19.4% |
| #12 | Anders Holst FC Helsingör | 30+ | 12.8% | 32.3% | -19.4% |
| #13 | Edgar Babayan Randers FC | 30+ | 12.8% | 32.3% | -19.4% |
| #14 | Andreas Laudrup FC Nordsjaelland | 30+ | 12.8% | 32.3% | -19.4% |
| #15 | Emil Lyng Silkeborg IF | 30+ | 12.8% | 32.3% | -19.4% |
| #16 | Daniel Royer FC Midtjylland | 30+ | 12.8% | 32.3% | -19.4% |
| #17 | Sören Frederiksen Sönderjyske Fodbold | 30+ | 12.8% | 32.3% | -19.4% |
| #18 | Cédric N'Koum Odense Boldklub | 30+ | 12.8% | 32.3% | -19.4% |
| #19 | Gheorghe Grozav Petrolul Ploiesti | 30+ | 12.8% | 32.3% | -19.4% |
| #20 | Emil Larsen Lyngby Boldklub | 30+ | 12.8% | 32.3% | -19.4% |
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: 3 immediate targets, 13 standard acquisitions, 0 watch-list prospects, 17 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 €500K. 0 undervalued, 6 premium.
Value Positioning vs Peers
| Player | Market Value | Position Median | Z-Score | Assessment |
|---|---|---|---|---|
Oucasse Mendy FC Universitatea Cluj | €150K | €300K | -0.60 | Good Value |
Wilfried Domoraud Hobro IK | €150K | €300K | -0.50 | Fair Value |
Emil Lyng Silkeborg IF | €150K | €300K | -0.50 | Fair Value |
Obule Moses FC Midtjylland | €150K | €300K | -0.44 | Fair Value |
Enock Otoo Lyngby Boldklub | €150K | €300K | -0.44 | Fair Value |
Frederik Emmery Aarhus GF | €350K | €300K | -0.43 | Fair Value |
Brandon Pierrick Vejle Boldklub | €200K | €300K | -0.40 | Fair Value |
Zé Pedro UTA Arad | €175K | €300K | -0.36 | Fair Value |
Adel Bettaieb ACSC FC Arges | €175K | €300K | -0.36 | Fair Value |
Agon Mucolli FC Fredericia | €200K | €300K | -0.29 | Fair Value |
Denis Yanakov AFC Unirea 04 Slobozia | €200K | €300K | -0.29 | Fair Value |
Noah Shamoun Randers FC | €300K | €300K | -0.28 | Fair Value |
Gustav Christensen FC Midtjylland | €300K | €300K | -0.28 | Fair Value |
Ninos Gouriye Vendsyssel FF | €200K | €300K | -0.25 | Fair Value |
Johan Absalonsen Sönderjyske Fodbold | €200K | €300K | -0.25 | Fair Value |
Musefiu Ashiru FC Midtjylland | €200K | €300K | -0.25 | Fair Value |
Anders Holst FC Helsingör | €200K | €300K | -0.25 | Fair Value |
Andreas Laudrup FC Nordsjaelland | €200K | €300K | -0.25 | Fair Value |
Sören Frederiksen Sönderjyske Fodbold | €200K | €300K | -0.25 | Fair Value |
Markus Jensen Odense Boldklub | €350K | €300K | -0.22 | Fair Value |
How We Rank Superliga Left Wingers
Our Analytical Strength Index is calibrated specifically for left wingers, 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 LW
Historical Achievement Index (35%)
Peak career market value for Superliga left wingers, 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 left wingers, capturing recent form, injuries, and current performance level. Weighted to reflect age-related depreciation patterns.
Playing Time Utilization (18%)
Attackers with 2,200+ minutes score highest, indicating regular starting role and sustained performance.
Age-Adjusted Performance Curve (12%)
Attackers peak at 26 with fastest 7.0%/year decline (pace-dependent). 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.
LW Performance Benchmarks
Peak Age: 26 years (peak pace and finishing efficiency)
Decline Rate: 7.0% per year (fastest decline, pace-dependent position)
Optimal Minutes: 2,200-2,400 per season (high-intensity position requires rotation)
1-Year Market Value Forecast
Probabilistic model combining age-curve depreciation, value momentum, and playing time factors:
• Age Factor: Attacker -7.0%/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: ±18% confidence interval (most volatile, form-dependent)
Research Foundation
• Dendir (2016): Age-performance curves for left wingers
• 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 Left Wingers in the 2022-23 season
Who are the most valuable Left Wingers in the Superliga in 2022-23?
The most valuable left winger in the Superliga in 2022-23 is Aral Şimşir, who is worth €6.0M and plays for FC Midtjylland. The second most valuable is Kristian Arnstad (€5.0M, Aarhus GF), followed by Nicolai Vallys (€4.5M, Bröndby IF). Our database tracks 62 Superliga Left Wingers with comprehensive market valuations updated for the 2022-23 season.
How are Superliga Left Wingers ranked?
Superliga Left Wingers are ranked by our proprietary Analytical Strength Index, which is specifically calibrated for Left Wingers. 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 Left Wingers peak?
Attackers typically peak at age 26, with the fastest decline rate of 7.0% per year after peak. This reflects the position's heavy reliance on pace, acceleration, and explosive power, which deteriorate faster than technical skills. Research by Carmichael et al. (2020) confirms that forwards peak earlier and decline faster than any other position. The optimal playing time is around 2,200-2,400 minutes per season.
How much does it cost to sign a top left winger from the Superliga?
Transfer fees for Superliga Left Wingers vary significantly based on market value, contract length, and club bargaining position. For the top-ranked left winger Aral Şimşir (market value: €6.0M), estimated transfer fees would range from €4.8M to €8.4M 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 Left Wingers?
Our 1-year forecast model projects market value changes for Superliga Left Wingers 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-attackers have ±18% volatility (most volatile due to form-dependency). 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 left winger data come from?
Our Superliga left winger 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.