Best Left Wingers in the MLS (Jul 2026)
Ranked by Analytical Strength Index
Market Overview: MLS Left Wingers 2024-25
Our database tracked 24 MLS Left Wingers in the 2024-25 season, representing 18 clubs with a combined market value of €94.6M. The average market value for MLS Left Wingers was €3.9M, with the average age at 28 years old.
The most valuable left winger in the MLS was Heung-min Son, worth €17.0M and played for Los Angeles Football Club at 34 years old. The top 5 Left Wingers averaged €10.3M in market value, including Joseph Paintsil and Jonathan Bamba.
Age distribution showed the youngest tracked left winger was Zach Booth (22 years, Real Salt Lake, €500K), while the oldest was Heung-min Son (34 years, Los Angeles Football Club, €17.0M). Research shows Left Wingers typically peak at age 26.
Historical analysis showed 8 Left Wingers (33%) 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 Left Wingers remained actively developing with emerging talent in the 2024-25 season.
Explore Market Size by Position in MLS
Interactive bubble chart showing predicted 2-year growth vs current age for all MLS Left Wingers. Identify undervalued assets and track market momentum across 18 clubs with €94.6M 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: MLS Left Wingers
The MLS LW market shows 4 distinct age segments, with the largest cohort in the 30+ bracket (9 players, 38% of market). The 30+ age group holds the most value at €61.6M, averaging €6.8M per player.
Top Left Wingers by Age Bracket
21-23 Years (1 players)
24-26 Years (8 players)
27-29 Years (6 players)
30+ Years (9 players)
Market Value Distribution
Elite Tier Concentration
The top 3 Left Wingers (13% of players) control €35.5M
Market Tiers
Market structure shows distributed value with high (€15-30m) tier representing 4% of the MLS LW pool.
High (€15-30M)
Mid (€5-15M)
Emerging (<€5M)
Club Distribution: MLS Left Wingers
Among 18 MLS clubs, Los Angeles Football Club leads with 3 Left Wingers worth €25.6M (averaging €8.5M per player). The top 10 clubs account for 67% of tracked Left Wingers.
Los Angeles Football Club (3 Left Wingers)
San Diego Football Club (3 Left Wingers)
Los Angeles Galaxy (1 Left Wingers)
Chicago Fire Soccer Club (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.
Heung-min Son
Los Angeles Football Club • 34 years old
€22.0M
€17.0M
-22.6%
Expected: €15.3M
69.6
Joseph Paintsil
Los Angeles Galaxy • 28 years old
€12.3M
€9.5M
-22.6%
Expected: €8.2M
59.0
Jonathan Bamba
Chicago Fire Soccer Club • 30 years old
€11.6M
€9.0M
-22.6%
Expected: €7.4M
58.2
Hirving Lozano
San Diego Football Club • 30 years old
€10.3M
€8.0M
-22.6%
Expected: €6.6M
56.8
Denis Bouanga
Los Angeles Football Club • 31 years old
€10.3M
€8.0M
-22.6%
Expected: €6.6M
56.8
Myrto Uzuni
Austin FC • 31 years old
€10.3M
€8.0M
-22.6%
Expected: €6.6M
56.8
Emil Forsberg
Red Bull New York • 34 years old
€6.5M
€5.0M
-22.6%
Expected: €4.3M
51.0
Kristoffer Velde
Portland Timbers • 26 years old
€3.9M
€4.5M
+15.6%
Expected: €4.6M
49.9
Lewis Morgan
San Diego Football Club • 29 years old
€5.2M
€4.0M
-22.6%
Expected: €3.3M
48.4
Wilfried Zaha
Charlotte Football Club • 33 years old
€5.2M
€4.0M
-22.6%
Expected: €3.5M
48.3
Ryan Kent
Seattle Sounders FC • 29 years old
€4.5M
€3.5M
-22.6%
Expected: €2.9M
46.8
Randall Leal
D.C. United • 29 years old
€4.5M
€3.5M
-22.6%
Expected: €2.9M
46.8
Saba Lobjanidze
Atlanta United Football Club • 31 years old
€2.6M
€2.0M
-22.6%
Expected: €1.6M
36.2
Antony
Portland Timbers • 24 years old
€1.6M
€1.8M
+15.6%
Expected: €1.8M
36.0
Peglow
D.C. United • 24 years old
€1.3M
€1.5M
+15.6%
Expected: €1.5M
33.8
Iván Angulo
Orlando City Soccer Club • 27 years old
€1.6M
€1.5M
-5.4%
Expected: €1.3M
32.8
Samuel Shashoua
Minnesota United FC • 27 years old
€1.1M
€1.0M
-5.4%
Expected: €866K
27.9
Alex Mighten
San Diego Football Club • 24 years old
€519K
€600K
+15.6%
Expected: €614K
22.6
Tyler Boyd
Los Angeles Football Club • 31 years old
€775K
€600K
-22.6%
Expected: €492K
21.6
Zach Booth
Real Salt Lake • 22 years old
€432K
€500K
+15.6%
Expected: €529K
21.3
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)
Portland Timbers's Antony at 24 years old has the highest Pre-Peak Value Efficiency at 3.00×. That means Antony is valued 3.00× higher than the median player in the 24-26 age bracket-representing exceptional value before reaching peak age.
In second is D.C. United's Peglow, who is 24 years old, with a 2.50× PPVE. Third is Alex Mighten of San Diego Football Club, who is 24 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 3.00× means the player is worth 200% 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 | Antony Portland Timbers | 24 | 24-26 | €1.8M | €600K | 3.00× |
| #2 | Peglow D.C. United | 24 | 24-26 | €1.5M | €600K | 2.50× |
| #3 | Alex Mighten San Diego Football Club | 24 | 24-26 | €600K | €600K | 1.00× |
| #4 | Zach Booth Real Salt Lake | 22 | 21-23 | €500K | €500K | 1.00× |
| #5 | Agustín Anello Philadelphia Union | 24 | 24-26 | €450K | €600K | 0.75× |
| #6 | Capita Sporting Kansas City | 24 | 24-26 | €250K | €600K | 0.42× |
| #7 | Christian Koffi Nashville SC | 25 | 24-26 | €150K | €600K | 0.25× |
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)
Real Salt Lake's Zach Booth at 22 years old has the highest Return-to-Peak Potential at +25%. That means Zach Booth is projected to appreciate 25% as they reach their peak age in 4 years-representing significant upside before entering their prime.
In second is San Diego Football Club's Alex Mighten, who is 24 years old, with a +14% RPP (2 years to peak). Third is Peglow of D.C. United, who is 24 years old with a +14% RPP (2 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 25% RPP means the player is expected to gain 25% 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 | Zach Booth Real Salt Lake | 22 | 4 | €500K | €668K | +25% |
| #2 | Alex Mighten San Diego Football Club | 24 | 2 | €600K | €694K | +14% |
| #3 | Peglow D.C. United | 24 | 2 | €1.5M | €1.7M | +14% |
| #4 | Capita Sporting Kansas City | 24 | 2 | €250K | €289K | +14% |
| #5 | Antony Portland Timbers | 24 | 2 | €1.8M | €2.1M | +14% |
| #6 | Agustín Anello Philadelphia Union | 24 | 2 | €450K | €520K | +14% |
| #7 | Christian Koffi Nashville SC | 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)
Real Salt Lake's Zach Booth has the highest Risk-Adjusted Upside at 15.3. That means Zach Booth has 6% upside potential with only 0% forecast uncertainty-representing excellent risk-reward for value appreciation.
In second is Portland Timbers's Kristoffer Velde with a 8.0 RAU (3% upside, 0% uncertainty). Third is Darius Johnson of San Jose Earthquakes with a 8.0 RAU (3% upside, 0% uncertainty).
How RAU is calculated: RAU divides upside potential by forecast uncertainty (RAU = Upside % ÷ Uncertainty %). A RAU of 15.3 means the upside is 15.3× 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 | Zach Booth Real Salt Lake | €529K | €434K-624K | +6% | 15.3 |
| #2 | Kristoffer Velde Portland Timbers | €4.6M | €3.8M-5.5M | +3% | 8.0 |
| #3 | Darius Johnson San Jose Earthquakes | €283K | €232K-334K | +3% | 8.0 |
| #4 | Antony Portland Timbers | €1.8M | €1.5M-2.2M | +2% | 6.5 |
| #5 | Agustín Anello Philadelphia Union | €461K | €378K-544K | +2% | 6.5 |
| #6 | Peglow D.C. United | €1.5M | €1.3M-1.8M | +2% | 6.5 |
| #7 | Alex Mighten San Diego Football Club | €614K | €504K-725K | +2% | 6.5 |
| #8 | Capita Sporting Kansas City | €256K | €210K-302K | +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)
Red Bull New York's Emil Forsberg in the 30+ age bracket has the highest Age-Share Concentration at +27.6%. That means Heung-min Son captures 65.1% of total market value while representing only 37.5% of players in their age group-showing dominant elite status.
In second is Charlotte Football Club's Wilfried Zaha with a +27.6% ASC (65.1% value share vs 37.5% player share in 30+ bracket). Third is Tyler Boyd of Los Angeles Football Club with a +27.6% ASC (65.1% value vs 37.5% players in 30+ bracket).
How ASC is calculated: ASC = (% of total value) - (% of total players) in age bracket. A +27.6% ASC means the player captures 27.6% 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 | Emil Forsberg Red Bull New York | 30+ | 65.1% | 37.5% | +27.6% |
| #2 | Wilfried Zaha Charlotte Football Club | 30+ | 65.1% | 37.5% | +27.6% |
| #3 | Tyler Boyd Los Angeles Football Club | 30+ | 65.1% | 37.5% | +27.6% |
| #4 | Denis Bouanga Los Angeles Football Club | 30+ | 65.1% | 37.5% | +27.6% |
| #5 | Saba Lobjanidze Atlanta United Football Club | 30+ | 65.1% | 37.5% | +27.6% |
| #6 | Jonathan Bamba Chicago Fire Soccer Club | 30+ | 65.1% | 37.5% | +27.6% |
| #7 | Myrto Uzuni Austin FC | 30+ | 65.1% | 37.5% | +27.6% |
| #8 | Hirving Lozano San Diego Football Club | 30+ | 65.1% | 37.5% | +27.6% |
| #9 | Heung-min Son Los Angeles Football Club | 30+ | 65.1% | 37.5% | +27.6% |
| #10 | Christian Koffi Nashville SC | 24-26 | 10.1% | 33.3% | -23.3% |
| #11 | Kristoffer Velde Portland Timbers | 24-26 | 10.1% | 33.3% | -23.3% |
| #12 | Alex Mighten San Diego Football Club | 24-26 | 10.1% | 33.3% | -23.3% |
| #13 | Peglow D.C. United | 24-26 | 10.1% | 33.3% | -23.3% |
| #14 | Capita Sporting Kansas City | 24-26 | 10.1% | 33.3% | -23.3% |
| #15 | Darius Johnson San Jose Earthquakes | 24-26 | 10.1% | 33.3% | -23.3% |
| #16 | Antony Portland Timbers | 24-26 | 10.1% | 33.3% | -23.3% |
| #17 | Agustín Anello Philadelphia Union | 24-26 | 10.1% | 33.3% | -23.3% |
| #18 | Zach Booth Real Salt Lake | 21-23 | 0.5% | 4.2% | -3.6% |
| #19 | Ryan Kent Seattle Sounders FC | 27-29 | 24.3% | 25.0% | -0.7% |
| #20 | Randall Leal D.C. United | 27-29 | 24.3% | 25.0% | -0.7% |
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, 1 standard acquisitions, 0 watch-list prospects, 11 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 €450K. 0 undervalued, 1 premium.
Value Positioning vs Peers
| Player | Market Value | Position Median | Z-Score | Assessment |
|---|---|---|---|---|
Samuel Shashoua Minnesota United FC | €1.0M | €3.5M | -1.25 | Good Value |
Iván Angulo Orlando City Soccer Club | €1.5M | €3.5M | -1.00 | Good Value |
Tyler Boyd Los Angeles Football Club | €600K | €3.5M | -0.41 | Fair Value |
Christian Koffi Nashville SC | €150K | €3.5M | -0.30 | Fair Value |
Capita Sporting Kansas City | €250K | €3.5M | -0.23 | Fair Value |
Darius Johnson San Jose Earthquakes | €275K | €3.5M | -0.21 | Fair Value |
Agustín Anello Philadelphia Union | €450K | €3.5M | -0.10 | Fair Value |
Emil Forsberg Red Bull New York | €5.0M | €3.5M | 0.00 | Fair Value |
Denis Bouanga Los Angeles Football Club | €8.0M | €3.5M | 0.00 | Fair Value |
Saba Lobjanidze Atlanta United Football Club | €2.0M | €3.5M | 0.00 | Fair Value |
Ryan Kent Seattle Sounders FC | €3.5M | €3.5M | 0.00 | Fair Value |
Jonathan Bamba Chicago Fire Soccer Club | €9.0M | €3.5M | 0.00 | Fair Value |
Randall Leal D.C. United | €3.5M | €3.5M | 0.00 | Fair Value |
Myrto Uzuni Austin FC | €8.0M | €3.5M | 0.00 | Fair Value |
Hirving Lozano San Diego Football Club | €8.0M | €3.5M | 0.00 | Fair Value |
Alex Mighten San Diego Football Club | €600K | €3.5M | 0.00 | Fair Value |
Joseph Paintsil Los Angeles Galaxy | €9.5M | €3.5M | 0.00 | Fair Value |
Zach Booth Real Salt Lake | €500K | €3.5M | 0.00 | Fair Value |
Heung-min Son Los Angeles Football Club | €17.0M | €3.5M | 0.00 | Fair Value |
Lewis Morgan San Diego Football Club | €4.0M | €3.5M | +0.25 | Fair Value |
How We Rank MLS 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 MLS 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 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: 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 MLS Left Wingers in the 2024-25 season
Who are the most valuable Left Wingers in the MLS in 2024-25?
The most valuable left winger in the MLS in 2024-25 is Heung-min Son, who is worth €17.0M and plays for Los Angeles Football Club. The second most valuable is Joseph Paintsil (€9.5M, Los Angeles Galaxy), followed by Jonathan Bamba (€9.0M, Chicago Fire Soccer Club). Our database tracks 24 MLS Left Wingers with comprehensive market valuations updated for the 2024-25 season.
How are MLS Left Wingers ranked?
MLS 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 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 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 MLS?
Transfer fees for MLS Left Wingers vary significantly based on market value, contract length, and club bargaining position. For the top-ranked left winger Heung-min Son (market value: €17.0M), estimated transfer fees would range from €13.6M to €23.8M 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 Left Wingers?
Our 1-year forecast model projects market value changes for MLS 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 MLS left winger data come from?
Our MLS 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 2024-25 season to ensure accuracy for recruitment and investment decisions.