Best U23 Young Left Wingers in the MLS
21 players aged 23 or under · ranked by Analytical Strength Index
Best Young Left Wingers in the MLS (Sep 2026)
Ranked by Analytical Strength Index
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.
Mateo Silvetti
Club Internacional de Fútbol Miami • 20 years old
€5.2M
€6.0M
+15.6%
Expected: €6.6M
53.5
Agustín Ojeda
New York City Football Club • 22 years old
€4.3M
€5.0M
+15.6%
Expected: €5.1M
53.1
Tiago
Orlando City Soccer Club • 21 years old
€3.0M
€3.5M
+15.6%
Expected: €3.6M
47.8
Jayden Nelson
Austin FC • 23 years old
€1.7M
€2.0M
+15.6%
Expected: €2.0M
37.7
Kenji Cabrera
Vancouver Whitecaps FC • 23 years old
€1.4M
€1.6M
+15.6%
Expected: €1.6M
35.0
Warren Madrigal
Nashville SC • 22 years old
€1.3M
€1.5M
+15.6%
Expected: €1.5M
34.7
Bruno Caicedo
Vancouver Whitecaps FC • 21 years old
€1.3M
€1.5M
+15.6%
Expected: €1.5M
33.8
Alexis Manyoma
Colorado Rapids • 23 years old
€1.0M
€1.2M
+15.6%
Expected: €1.2M
31.5
Nimfasha Berchimas
Charlotte Football Club • 18 years old
€1.3M
€1.5M
+15.6%
Expected: €1.7M
31.1
Mohammed Sofo
Red Bull New York • 21 years old
€865K
€1.0M
+15.6%
Expected: €1.0M
28.9
Andy Rojas
Red Bull New York • 20 years old
€865K
€1.0M
+15.6%
Expected: €1.1M
28.0
Mauricio González
Minnesota United FC • 21 years old
€778K
€900K
+15.6%
Expected: €913K
27.6
Kenyel Michel
Minnesota United FC • 21 years old
€692K
€800K
+15.6%
Expected: €811K
26.2
Bryan Zamblé
San Diego Football Club • 18 years old
€692K
€800K
+15.6%
Expected: €882K
23.5
Malachi Jones
New York City Football Club • 22 years old
€346K
€400K
+15.6%
Expected: €406K
18.6
Zach Booth
Real Salt Lake • 22 years old
€303K
€350K
+15.6%
Expected: €355K
17.0
CJ Fodrey
Austin FC • 22 years old
€303K
€350K
+15.6%
Expected: €355K
17.0
Rafael Mosquera
Red Bull New York • 21 years old
€259K
€300K
+15.6%
Expected: €304K
14.2
Harvey Sarajian
Orlando City Soccer Club • 21 years old
€173K
€200K
+15.6%
Expected: €203K
9.3
Kimani Stewart-Baynes
Colorado Rapids • 21 years old
€173K
€200K
+15.6%
Expected: €203K
9.3
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Explore Market Size by Position in MLS
Interactive bubble chart showing predicted 2-year growth vs current age for all MLS Young Left Wingers. Identify undervalued assets and track market momentum across 12 clubs with €30.3M combined value.
Age Distribution: MLS Young Left Wingers
The MLS LW market shows 2 distinct age segments, with the largest cohort in the 21-23 bracket (16 players, 76% of market). The 21-23 age group holds the most value at €20.8M, averaging €1.3M per player.
Top Young Left Wingers by Age Bracket
U21 Years (5 players)
21-23 Years (16 players)
Market Value Distribution
Elite Tier Concentration
The top 3 Young Left Wingers (14% of players) control €14.5M
Market Tiers
Market structure shows distributed value with mid (€5-15m) tier representing 10% of the MLS LW pool.
Mid (€5-15M)
Emerging (<€5M)
Club Distribution: MLS Young Left Wingers
Among 12 MLS clubs, Club Internacional de Fútbol Miami leads with 2 Young Left Wingers worth €6.2M (averaging €3.1M per player). The top 10 clubs account for 90% of tracked Young Left Wingers.
Club Internacional de Fútbol Miami (2 Young Left Wingers)
New York City Football Club (2 Young Left Wingers)
Orlando City Soccer Club (2 Young Left Wingers)
Vancouver Whitecaps FC (2 Young Left Wingers)
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)
Club Internacional de Fútbol Miami's Mateo Silvetti at 20 years old has the highest Pre-Peak Value Efficiency at 6.00×. That means Mateo Silvetti is valued 6.00× higher than the median player in the U21 age bracket-representing exceptional value before reaching peak age.
In second is New York City Football Club's Agustín Ojeda, who is 22 years old, with a 5.00× PPVE. Third is Tiago of Orlando City Soccer Club, who is 21 years old with a 3.50× 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 6.00× means the player is worth 500% 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 | Mateo Silvetti Club Internacional de Fútbol Miami | 20 | U21 | €6.0M | €1.0M | 6.00× |
| #2 | Agustín Ojeda New York City Football Club | 22 | 21-23 | €5.0M | €1.0M | 5.00× |
| #3 | Tiago Orlando City Soccer Club | 21 | 21-23 | €3.5M | €1.0M | 3.50× |
| #4 | Jayden Nelson Austin FC | 23 | 21-23 | €2.0M | €1.0M | 2.00× |
| #5 | Kenji Cabrera Vancouver Whitecaps FC | 23 | 21-23 | €1.6M | €1.0M | 1.60× |
| #6 | Nimfasha Berchimas Charlotte Football Club | 18 | U21 | €1.5M | €1.0M | 1.50× |
| #7 | Bruno Caicedo Vancouver Whitecaps FC | 21 | 21-23 | €1.5M | €1.0M | 1.50× |
| #8 | Warren Madrigal Nashville SC | 22 | 21-23 | €1.5M | €1.0M | 1.50× |
| #9 | Alexis Manyoma Colorado Rapids | 23 | 21-23 | €1.2M | €1.0M | 1.20× |
| #10 | Andy Rojas Red Bull New York | 20 | U21 | €1.0M | €1.0M | 1.00× |
| #11 | Mohammed Sofo Red Bull New York | 21 | 21-23 | €1.0M | €1.0M | 1.00× |
| #12 | Mauricio González Minnesota United FC | 21 | 21-23 | €900K | €1.0M | 0.90× |
| #13 | Kenyel Michel Minnesota United FC | 21 | 21-23 | €800K | €1.0M | 0.80× |
| #14 | Bryan Zamblé San Diego Football Club | 18 | U21 | €800K | €1.0M | 0.80× |
| #15 | Malachi Jones New York City Football Club | 22 | 21-23 | €400K | €1.0M | 0.40× |
| #16 | Zach Booth Real Salt Lake | 22 | 21-23 | €350K | €1.0M | 0.35× |
| #17 | CJ Fodrey Austin FC | 22 | 21-23 | €350K | €1.0M | 0.35× |
| #18 | Rafael Mosquera Red Bull New York | 21 | 21-23 | €300K | €1.0M | 0.30× |
| #19 | Dániel Pintér Club Internacional de Fútbol Miami | 19 | U21 | €200K | €1.0M | 0.20× |
| #20 | Kimani Stewart-Baynes Colorado Rapids | 21 | 21-23 | €200K | €1.0M | 0.20× |
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)
Charlotte Football Club's Nimfasha Berchimas at 18 years old has the highest Return-to-Peak Potential at +44%. That means Nimfasha Berchimas is projected to appreciate 44% as they reach their peak age in 8 years-representing significant upside before entering their prime.
In second is San Diego Football Club's Bryan Zamblé, who is 18 years old, with a +44% RPP (8 years to peak). Third is Dániel Pintér of Club Internacional de Fútbol Miami, 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 44% RPP means the player is expected to gain 44% 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 | Nimfasha Berchimas Charlotte Football Club | 18 | 8 | €1.5M | €2.7M | +44% |
| #2 | Bryan Zamblé San Diego Football Club | 18 | 8 | €800K | €1.4M | +44% |
| #3 | Dániel Pintér Club Internacional de Fútbol Miami | 19 | 7 | €200K | €332K | +40% |
| #4 | Mateo Silvetti Club Internacional de Fútbol Miami | 20 | 6 | €6.0M | €9.3M | +35% |
| #5 | Andy Rojas Red Bull New York | 20 | 6 | €1.0M | €1.5M | +35% |
| #6 | Mohammed Sofo Red Bull New York | 21 | 5 | €1.0M | €1.4M | +30% |
| #7 | Mauricio González Minnesota United FC | 21 | 5 | €900K | €1.3M | +30% |
| #8 | Rafael Mosquera Red Bull New York | 21 | 5 | €300K | €431K | +30% |
| #9 | Kenyel Michel Minnesota United FC | 21 | 5 | €800K | €1.1M | +30% |
| #10 | Tiago Orlando City Soccer Club | 21 | 5 | €3.5M | €5.0M | +30% |
| #11 | Kimani Stewart-Baynes Colorado Rapids | 21 | 5 | €200K | €287K | +30% |
| #12 | Bruno Caicedo Vancouver Whitecaps FC | 21 | 5 | €1.5M | €2.2M | +30% |
| #13 | Harvey Sarajian Orlando City Soccer Club | 21 | 5 | €200K | €287K | +30% |
| #14 | Zach Booth Real Salt Lake | 22 | 4 | €350K | €468K | +25% |
| #15 | CJ Fodrey Austin FC | 22 | 4 | €350K | €468K | +25% |
| #16 | Agustín Ojeda New York City Football Club | 22 | 4 | €5.0M | €6.7M | +25% |
| #17 | Malachi Jones New York City Football Club | 22 | 4 | €400K | €535K | +25% |
| #18 | Warren Madrigal Nashville SC | 22 | 4 | €1.5M | €2.0M | +25% |
| #19 | Alexis Manyoma Colorado Rapids | 23 | 3 | €1.2M | €1.5M | +20% |
| #20 | Jayden Nelson Austin FC | 23 | 3 | €2.0M | €2.5M | +20% |
Risk-Adjusted Upside (RAU)
Upside potential weighted against forecast uncertainty. Higher RAU = better risk-reward profile.
Understanding Risk-Adjusted Upside (RAU)
Red Bull New York's Andy Rojas has the highest Risk-Adjusted Upside at 22.5. That means Andy Rojas has 10% upside potential with only 0% forecast uncertainty-representing excellent risk-reward for value appreciation.
In second is Charlotte Football Club's Nimfasha Berchimas with a 22.5 RAU (10% upside, 0% uncertainty). Third is Mateo Silvetti of Club Internacional de Fútbol Miami with a 22.5 RAU (10% upside, 0% uncertainty).
How RAU is calculated: RAU divides upside potential by forecast uncertainty (RAU = Upside % ÷ Uncertainty %). A RAU of 22.5 means the upside is 22.5× 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 | Andy Rojas Red Bull New York | €1.1M | €874K-1.3M | +10% | 22.5 |
| #2 | Nimfasha Berchimas Charlotte Football Club | €1.7M | €1.3M-2.0M | +10% | 22.5 |
| #3 | Mateo Silvetti Club Internacional de Fútbol Miami | €6.6M | €5.2M-8.0M | +10% | 22.5 |
| #4 | Dániel Pintér Club Internacional de Fútbol Miami | €221K | €175K-266K | +10% | 22.5 |
| #5 | Bryan Zamblé San Diego Football Club | €882K | €699K-1.1M | +10% | 22.5 |
| #6 | Alexis Manyoma Colorado Rapids | €1.2M | €1.0M-1.5M | +2% | 6.5 |
| #7 | Jayden Nelson Austin FC | €2.0M | €1.7M-2.4M | +2% | 6.5 |
| #8 | Kenji Cabrera Vancouver Whitecaps FC | €1.6M | €1.3M-1.9M | +2% | 6.5 |
| #9 | Zach Booth Real Salt Lake | €355K | €291K-419K | +1% | 3.9 |
| #10 | CJ Fodrey Austin FC | €355K | €291K-419K | +1% | 3.9 |
| #11 | Agustín Ojeda New York City Football Club | €5.1M | €4.2M-6.0M | +1% | 3.9 |
| #12 | Malachi Jones New York City Football Club | €406K | €333K-479K | +1% | 3.9 |
| #13 | Warren Madrigal Nashville SC | €1.5M | €1.2M-1.8M | +1% | 3.9 |
| #14 | Rafael Mosquera Red Bull New York | €304K | €241K-367K | +1% | 3.4 |
| #15 | Tiago Orlando City Soccer Club | €3.6M | €2.8M-4.3M | +1% | 3.4 |
| #16 | Kenyel Michel Minnesota United FC | €811K | €643K-979K | +1% | 3.4 |
| #17 | Kimani Stewart-Baynes Colorado Rapids | €203K | €161K-245K | +1% | 3.4 |
| #18 | Harvey Sarajian Orlando City Soccer Club | €203K | €161K-245K | +1% | 3.4 |
| #19 | Bruno Caicedo Vancouver Whitecaps FC | €1.5M | €1.2M-1.8M | +1% | 3.4 |
| #20 | Mohammed Sofo Red Bull New York | €1.0M | €804K-1.2M | +1% | 3.4 |
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: young left winger position shows weak 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)
Charlotte Football Club's Nimfasha Berchimas in the U21 age bracket has the highest Age-Share Concentration at +7.5%. That means Mateo Silvetti captures 31.4% of total market value while representing only 23.8% of players in their age group-showing dominant elite status.
In second is Red Bull New York's Andy Rojas with a +7.5% ASC (31.4% value share vs 23.8% player share in U21 bracket). Third is Dániel Pintér of Club Internacional de Fútbol Miami with a +7.5% ASC (31.4% value vs 23.8% players in U21 bracket).
How ASC is calculated: ASC = (% of total value) - (% of total players) in age bracket. A +7.5% ASC means the player captures 7.5% 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 | Nimfasha Berchimas Charlotte Football Club | U21 | 31.4% | 23.8% | +7.5% |
| #2 | Andy Rojas Red Bull New York | U21 | 31.4% | 23.8% | +7.5% |
| #3 | Dániel Pintér Club Internacional de Fútbol Miami | U21 | 31.4% | 23.8% | +7.5% |
| #4 | Mateo Silvetti Club Internacional de Fútbol Miami | U21 | 31.4% | 23.8% | +7.5% |
| #5 | Bryan Zamblé San Diego Football Club | U21 | 31.4% | 23.8% | +7.5% |
| #6 | Kenyel Michel Minnesota United FC | 21-23 | 68.6% | 76.2% | -7.5% |
| #7 | Mauricio González Minnesota United FC | 21-23 | 68.6% | 76.2% | -7.5% |
| #8 | Tiago Orlando City Soccer Club | 21-23 | 68.6% | 76.2% | -7.5% |
| #9 | Kimani Stewart-Baynes Colorado Rapids | 21-23 | 68.6% | 76.2% | -7.5% |
| #10 | Mohammed Sofo Red Bull New York | 21-23 | 68.6% | 76.2% | -7.5% |
| #11 | Malachi Jones New York City Football Club | 21-23 | 68.6% | 76.2% | -7.5% |
| #12 | Bruno Caicedo Vancouver Whitecaps FC | 21-23 | 68.6% | 76.2% | -7.5% |
| #13 | Harvey Sarajian Orlando City Soccer Club | 21-23 | 68.6% | 76.2% | -7.5% |
| #14 | Jayden Nelson Austin FC | 21-23 | 68.6% | 76.2% | -7.5% |
| #15 | Zach Booth Real Salt Lake | 21-23 | 68.6% | 76.2% | -7.5% |
| #16 | Warren Madrigal Nashville SC | 21-23 | 68.6% | 76.2% | -7.5% |
| #17 | Kenji Cabrera Vancouver Whitecaps FC | 21-23 | 68.6% | 76.2% | -7.5% |
| #18 | CJ Fodrey Austin FC | 21-23 | 68.6% | 76.2% | -7.5% |
| #19 | Rafael Mosquera Red Bull New York | 21-23 | 68.6% | 76.2% | -7.5% |
| #20 | Agustín Ojeda New York City Football Club | 21-23 | 68.6% | 76.2% | -7.5% |
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, 5 standard acquisitions, 16 watch-list prospects, 0 at peak.
BUY NOW - High Upside
No players in this category
WATCH LIST - High Upside
BUY NOW - Medium Upside
PEAK Players
No players in this category
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 €800K. 0 undervalued, 1 premium.
Value Positioning vs Peers
| Player | Market Value | Position Median | Z-Score | Assessment |
|---|---|---|---|---|
Dániel Pintér Club Internacional de Fútbol Miami | €200K | €1.0M | -1.14 | Good Value |
Kimani Stewart-Baynes Colorado Rapids | €200K | €1.0M | -0.61 | Good Value |
Harvey Sarajian Orlando City Soccer Club | €200K | €1.0M | -0.61 | Good Value |
Rafael Mosquera Red Bull New York | €300K | €1.0M | -0.52 | Good Value |
Zach Booth Real Salt Lake | €350K | €1.0M | -0.48 | Fair Value |
CJ Fodrey Austin FC | €350K | €1.0M | -0.48 | Fair Value |
Malachi Jones New York City Football Club | €400K | €1.0M | -0.43 | Fair Value |
Bryan Zamblé San Diego Football Club | €800K | €1.0M | -0.29 | Fair Value |
Kenyel Michel Minnesota United FC | €800K | €1.0M | -0.09 | Fair Value |
Andy Rojas Red Bull New York | €1.0M | €1.0M | 0.00 | Fair Value |
Mauricio González Minnesota United FC | €900K | €1.0M | 0.00 | Fair Value |
Mateo Silvetti Club Internacional de Fútbol Miami | €6.0M | €1.0M | 0.00 | Fair Value |
Agustín Ojeda New York City Football Club | €5.0M | €1.0M | 0.00 | Fair Value |
Mohammed Sofo Red Bull New York | €1.0M | €1.0M | +0.09 | Fair Value |
Alexis Manyoma Colorado Rapids | €1.2M | €1.0M | +0.26 | Fair Value |
Bruno Caicedo Vancouver Whitecaps FC | €1.5M | €1.0M | +0.52 | Above Market |
Warren Madrigal Nashville SC | €1.5M | €1.0M | +0.52 | Above Market |
Kenji Cabrera Vancouver Whitecaps FC | €1.6M | €1.0M | +0.61 | Above Market |
Nimfasha Berchimas Charlotte Football Club | €1.5M | €1.0M | +0.71 | Above Market |
Jayden Nelson Austin FC | €2.0M | €1.0M | +0.96 | Above Market |
Market Overview: MLS Young Left Wingers 2022-23
Our database tracked 21 MLS Young Left Wingers in the 2022-23 season, representing 12 clubs with a combined market value of €30.3M. The average market value for MLS Young Left Wingers was €1.4M, with the average age at 21 years old.
The most valuable young left winger in the MLS was Mateo Silvetti, worth €6.0M and played for Club Internacional de Fútbol Miami at 20 years old. The top 5 Young Left Wingers averaged €3.6M in market value, including Agustín Ojeda and Tiago.
Age distribution showed the youngest tracked young left winger was Nimfasha Berchimas (18 years, Charlotte Football Club, €1.5M), while the oldest was Jayden Nelson (23 years, Austin FC, €2.0M). Research shows Young Left Wingers typically peak at age 26.
Historical analysis showed 21 Young Left Wingers (100%) increased in market value over the following 12 months based on age-curve trajectories, then-current performance trends, and playing time analysis. The MLS market for Young Left Wingers remained actively developing with emerging talent in the 2022-23 season.
How We Rank MLS Young Left Wingers
Our Analytical Strength Index is calibrated specifically for young 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 MLS young 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 MLS young 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%)
MLS 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: Widening steps, not a flat rate: about -5% at 27, -10% at 28, steeper from 29 (earliest onset, 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: Compounding and banded around a peak of 26: +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: ±18% confidence interval (most volatile, form-dependent)
Research Foundation
• Dendir (2016): Age-performance curves for young 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 MLS Young Left Wingers in the 2022-23 season
Who are the most valuable Young Left Wingers in the MLS in 2022-23?
The most valuable young left winger in the MLS in 2022-23 is Mateo Silvetti, who is worth €6.0M and plays for Club Internacional de Fútbol Miami. The second most valuable is Agustín Ojeda (€5.0M, New York City Football Club), followed by Tiago (€3.5M, Orlando City Soccer Club). Our database tracks 21 MLS Young Left Wingers with comprehensive market valuations updated for the 2022-23 season.
How are MLS Young Left Wingers ranked?
MLS Young Left Wingers are ranked by our proprietary Analytical Strength Index, which is specifically calibrated for Young 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 MLS 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 Young Left Wingers peak?
Attackers peak earliest, typically at age 26. In our valuation model, value then falls in widening steps rather than at a flat annual rate: around -5% at 27, -10% at 28, and -15% or more from 29. 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 young left winger from the MLS?
Transfer fees for MLS Young Left Wingers vary significantly based on market value, contract length, and club bargaining position. For the top-ranked young left winger Mateo Silvetti (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 MLS transactions.
What is the value forecast for MLS Young Left Wingers?
Our 1-year forecast model projects market value changes for MLS Young 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 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-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 MLS young left winger data come from?
Our MLS young 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 MLS sources and updated monthly for the 2022-23 season to ensure accuracy for recruitment and investment decisions.