Best Attacking Midfielders in the MLS (Jul 2026)
Ranked by Analytical Strength Index
Market Overview: MLS Attacking Midfielders 2022-23
Our database tracked 22 MLS Attacking Midfielders in the 2022-23 season, representing 18 clubs with a combined market value of €93.4M. The average market value for MLS Attacking Midfielders was €4.2M, with the average age at 29 years old.
The most valuable attacking midfielder in the MLS was Hany Mukhtar, worth €12.0M and played for Nashville SC at 31 years old. The top 5 Attacking Midfielders averaged €8.8M in market value, including Aleksey Miranchuk and Evander.
Age distribution showed the youngest tracked attacking midfielder was Paxten Aaronson (22 years, Colorado Rapids, €7.0M), while the oldest was Maxi Moralez (39 years, New York City Football Club, €200K). Research shows Attacking Midfielders typically peak at age 26.
Historical analysis showed 4 Attacking Midfielders (18%) 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 Attacking Midfielders remained actively developing with emerging talent in the 2022-23 season.
Explore Market Size by Position in MLS
Interactive bubble chart showing predicted 2-year growth vs current age for all MLS Attacking Midfielders. Identify undervalued assets and track market momentum across 18 clubs with €93.4M 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 Attacking Midfielders
The MLS CAM market shows 4 distinct age segments, with the largest cohort in the 30+ bracket (9 players, 41% of market). The 30+ age group holds the most value at €44.1M, averaging €4.9M per player.
Top Attacking Midfielders by Age Bracket
21-23 Years (2 players)
24-26 Years (4 players)
27-29 Years (7 players)
30+ Years (9 players)
Market Value Distribution
Elite Tier Concentration
The top 3 Attacking Midfielders (14% of players) control €30.0M
Market Tiers
Market structure shows distributed value with mid (€5-15m) tier representing 41% of the MLS CAM pool.
Mid (€5-15M)
Emerging (<€5M)
Club Distribution: MLS Attacking Midfielders
Among 18 MLS clubs, Nashville SC leads with 1 Attacking Midfielders worth €12.0M (averaging €12.0M per player). The top 10 clubs account for 64% of tracked Attacking Midfielders.
Nashville SC (1 Attacking Midfielders)
Atlanta United Football Club (1 Attacking Midfielders)
Football Club Cincinnati (2 Attacking Midfielders)
Portland Timbers (2 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.
Hany Mukhtar
Nashville SC • 31 years old
€15.5M
€12.0M
-22.6%
Expected: €9.9M
66.5
Aleksey Miranchuk
Atlanta United Football Club • 30 years old
€12.9M
€10.0M
-22.6%
Expected: €8.3M
60.5
Evander
Football Club Cincinnati • 28 years old
€10.3M
€8.0M
-22.6%
Expected: €7.0M
57.5
Paxten Aaronson
Colorado Rapids • 22 years old
€6.1M
€7.0M
+15.6%
Expected: €7.4M
56.4
Ryan Gauld
Vancouver Whitecaps FC • 30 years old
€9.0M
€7.0M
-22.6%
Expected: €5.8M
56.1
David Da Costa
Portland Timbers • 25 years old
€5.2M
€6.0M
+15.6%
Expected: €5.9M
54.2
Marco Reus
Los Angeles Galaxy • 37 years old
€6.5M
€5.0M
-22.6%
Expected: €4.4M
53.4
Carles Gil
New England Revolution • 33 years old
€6.5M
€5.0M
-22.6%
Expected: €4.4M
52.2
Iván Jaime
Club de Foot Montréal • 25 years old
€4.3M
€5.0M
+15.6%
Expected: €4.9M
51.9
Manu García
Sporting Kansas City • 28 years old
€4.5M
€3.5M
-22.6%
Expected: €3.1M
47.2
Ondrej Lingr
Houston Dynamo • 27 years old
€3.7M
€3.5M
-5.4%
Expected: €3.1M
47.1
Pep Biel
Charlotte Football Club • 29 years old
€3.9M
€3.0M
-22.6%
Expected: €2.5M
41.8
Djordje Mihailovic
Toronto FC • 27 years old
€3.2M
€3.0M
-5.4%
Expected: €2.6M
41.6
Albert Rusnák
Seattle Sounders FC • 32 years old
€3.2M
€2.5M
-22.6%
Expected: €2.2M
39.9
Amine Bassi
Houston Dynamo • 28 years old
€3.2M
€2.5M
-22.6%
Expected: €2.2M
39.4
Caden Clark
D.C. United • 23 years old
€1.7M
€2.0M
+15.6%
Expected: €2.1M
37.9
Cole Bassett
Portland Timbers • 24 years old
€1.7M
€2.0M
+15.6%
Expected: €2.0M
37.4
Erik Thommy
Los Angeles Galaxy • 31 years old
€2.6M
€2.0M
-22.6%
Expected: €1.7M
37.0
André Franco
Chicago Fire Soccer Club • 28 years old
€2.6M
€2.0M
-22.6%
Expected: €1.8M
36.7
Tomas Ostrák
St. Louis City Soccer Club • 26 years old
€1.6M
€1.8M
+15.6%
Expected: €1.9M
35.1
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 David Da Costa at 25 years old has the highest Pre-Peak Value Efficiency at 1.20×. That means David Da Costa is valued 1.20× higher than the median player in the 24-26 age bracket-representing exceptional value before reaching peak age.
In second is Club de Foot Montréal's Iván Jaime, who is 25 years old, with a 1.00× PPVE. Third is Paxten Aaronson of Colorado Rapids, who is 22 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 1.20× means the player is worth 20% 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 | David Da Costa Portland Timbers | 25 | 24-26 | €6.0M | €5.0M | 1.20× |
| #2 | Iván Jaime Club de Foot Montréal | 25 | 24-26 | €5.0M | €5.0M | 1.00× |
| #3 | Paxten Aaronson Colorado Rapids | 22 | 21-23 | €7.0M | €7.0M | 1.00× |
| #4 | Cole Bassett Portland Timbers | 24 | 24-26 | €2.0M | €5.0M | 0.40× |
| #5 | Caden Clark D.C. United | 23 | 21-23 | €2.0M | €7.0M | 0.29× |
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)
Colorado Rapids's Paxten Aaronson at 22 years old has the highest Return-to-Peak Potential at +25%. That means Paxten Aaronson is projected to appreciate 25% as they reach their peak age in 4 years-representing significant upside before entering their prime.
In second is D.C. United's Caden Clark, who is 23 years old, with a +20% RPP (3 years to peak). Third is Cole Bassett of Portland Timbers, 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 | Paxten Aaronson Colorado Rapids | 22 | 4 | €7.0M | €9.4M | +25% |
| #2 | Caden Clark D.C. United | 23 | 3 | €2.0M | €2.5M | +20% |
| #3 | Cole Bassett Portland Timbers | 24 | 2 | €2.0M | €2.3M | +14% |
| #4 | Iván Jaime Club de Foot Montréal | 25 | 1 | €5.0M | €5.4M | +7% |
| #5 | David Da Costa Portland Timbers | 25 | 1 | €6.0M | €6.5M | +7% |
Risk-Adjusted Upside (RAU)
Upside potential weighted against forecast uncertainty. Higher RAU = better risk-reward profile.
Understanding Risk-Adjusted Upside (RAU)
D.C. United's Caden Clark has the highest Risk-Adjusted Upside at 25.4. That means Caden Clark has 7% upside potential with only 0% forecast uncertainty-representing excellent risk-reward for value appreciation.
In second is Colorado Rapids's Paxten Aaronson with a 21.2 RAU (6% upside, 0% uncertainty). Third is Tomas Ostrák of St. Louis City Soccer Club with a 11.1 RAU (3% upside, 0% uncertainty).
How RAU is calculated: RAU divides upside potential by forecast uncertainty (RAU = Upside % ÷ Uncertainty %). A RAU of 25.4 means the upside is 25.4× 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 | Caden Clark D.C. United | €2.1M | €1.9M-2.4M | +7% | 25.4 |
| #2 | Paxten Aaronson Colorado Rapids | €7.4M | €6.4M-8.4M | +6% | 21.2 |
| #3 | Tomas Ostrák St. Louis City Soccer Club | €1.9M | €1.6M-2.1M | +3% | 11.1 |
| #4 | Cole Bassett Portland Timbers | €2.0M | €1.8M-2.3M | +2% | 9.1 |
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 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)
New England Revolution's Carles Gil in the 30+ age bracket has the highest Age-Share Concentration at +6.3%. That means Hany Mukhtar captures 47.2% of total market value while representing only 40.9% of players in their age group-showing dominant elite status.
In second is Nashville SC's Hany Mukhtar with a +6.3% ASC (47.2% value share vs 40.9% player share in 30+ bracket). Third is Erik Thommy of Los Angeles Galaxy with a +6.3% ASC (47.2% value vs 40.9% players in 30+ bracket).
How ASC is calculated: ASC = (% of total value) - (% of total players) in age bracket. A +6.3% ASC means the player captures 6.3% 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 | Carles Gil New England Revolution | 30+ | 47.2% | 40.9% | +6.3% |
| #2 | Hany Mukhtar Nashville SC | 30+ | 47.2% | 40.9% | +6.3% |
| #3 | Erik Thommy Los Angeles Galaxy | 30+ | 47.2% | 40.9% | +6.3% |
| #4 | Yuya Kubo Football Club Cincinnati | 30+ | 47.2% | 40.9% | +6.3% |
| #5 | Ryan Gauld Vancouver Whitecaps FC | 30+ | 47.2% | 40.9% | +6.3% |
| #6 | Aleksey Miranchuk Atlanta United Football Club | 30+ | 47.2% | 40.9% | +6.3% |
| #7 | Maxi Moralez New York City Football Club | 30+ | 47.2% | 40.9% | +6.3% |
| #8 | Marco Reus Los Angeles Galaxy | 30+ | 47.2% | 40.9% | +6.3% |
| #9 | Albert Rusnák Seattle Sounders FC | 30+ | 47.2% | 40.9% | +6.3% |
| #10 | Pep Biel Charlotte Football Club | 27-29 | 27.3% | 31.8% | -4.5% |
| #11 | Manu García Sporting Kansas City | 27-29 | 27.3% | 31.8% | -4.5% |
| #12 | Ondrej Lingr Houston Dynamo | 27-29 | 27.3% | 31.8% | -4.5% |
| #13 | Evander Football Club Cincinnati | 27-29 | 27.3% | 31.8% | -4.5% |
| #14 | André Franco Chicago Fire Soccer Club | 27-29 | 27.3% | 31.8% | -4.5% |
| #15 | Djordje Mihailovic Toronto FC | 27-29 | 27.3% | 31.8% | -4.5% |
| #16 | Amine Bassi Houston Dynamo | 27-29 | 27.3% | 31.8% | -4.5% |
| #17 | Tomas Ostrák St. Louis City Soccer Club | 24-26 | 15.8% | 18.2% | -2.3% |
| #18 | Cole Bassett Portland Timbers | 24-26 | 15.8% | 18.2% | -2.3% |
| #19 | Iván Jaime Club de Foot Montréal | 24-26 | 15.8% | 18.2% | -2.3% |
| #20 | David Da Costa Portland Timbers | 24-26 | 15.8% | 18.2% | -2.3% |
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, 2 standard acquisitions, 0 watch-list prospects, 10 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 €8.0M. 0 undervalued, 0 premium.
Value Positioning vs Peers
| Player | Market Value | Position Median | Z-Score | Assessment |
|---|---|---|---|---|
Tomas Ostrák St. Louis City Soccer Club | €1.8M | €3.5M | -1.00 | Good Value |
André Franco Chicago Fire Soccer Club | €2.0M | €3.5M | -1.00 | Good Value |
Iván Jaime Club de Foot Montréal | €5.0M | €3.5M | -1.00 | Good Value |
Maxi Moralez New York City Football Club | €200K | €3.5M | -0.86 | Good Value |
Yuya Kubo Football Club Cincinnati | €400K | €3.5M | -0.76 | Good Value |
Amine Bassi Houston Dynamo | €2.5M | €3.5M | -0.50 | Fair Value |
Carles Gil New England Revolution | €5.0M | €3.5M | -0.40 | Fair Value |
Marco Reus Los Angeles Galaxy | €5.0M | €3.5M | -0.40 | Fair Value |
Erik Thommy Los Angeles Galaxy | €2.0M | €3.5M | 0.00 | Fair Value |
Ryan Gauld Vancouver Whitecaps FC | €7.0M | €3.5M | 0.00 | Fair Value |
Pep Biel Charlotte Football Club | €3.0M | €3.5M | 0.00 | Fair Value |
Evander Football Club Cincinnati | €8.0M | €3.5M | 0.00 | Fair Value |
Djordje Mihailovic Toronto FC | €3.0M | €3.5M | 0.00 | Fair Value |
Cole Bassett Portland Timbers | €2.0M | €3.5M | 0.00 | Fair Value |
David Da Costa Portland Timbers | €6.0M | €3.5M | 0.00 | Fair Value |
Caden Clark D.C. United | €2.0M | €3.5M | 0.00 | Fair Value |
Paxten Aaronson Colorado Rapids | €7.0M | €3.5M | 0.00 | Fair Value |
Albert Rusnák Seattle Sounders FC | €2.5M | €3.5M | +0.24 | Fair Value |
Manu García Sporting Kansas City | €3.5M | €3.5M | +0.50 | Fair Value |
Ondrej Lingr Houston Dynamo | €3.5M | €3.5M | +0.50 | Fair Value |
How We Rank MLS 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 MLS 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 MLS 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%)
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.
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 MLS Attacking Midfielders in the 2022-23 season
Who are the most valuable Attacking Midfielders in the MLS in 2022-23?
The most valuable attacking midfielder in the MLS in 2022-23 is Hany Mukhtar, who is worth €12.0M and plays for Nashville SC. The second most valuable is Aleksey Miranchuk (€10.0M, Atlanta United Football Club), followed by Evander (€8.0M, Football Club Cincinnati). Our database tracks 22 MLS Attacking Midfielders with comprehensive market valuations updated for the 2022-23 season.
How are MLS Attacking Midfielders ranked?
MLS 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 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 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 MLS?
Transfer fees for MLS Attacking Midfielders vary significantly based on market value, contract length, and club bargaining position. For the top-ranked attacking midfielder Hany Mukhtar (market value: €12.0M), estimated transfer fees would range from €9.6M to €16.8M 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 Attacking Midfielders?
Our 1-year forecast model projects market value changes for MLS 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 MLS attacking midfielder data come from?
Our MLS 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 MLS sources and updated monthly for the 2022-23 season to ensure accuracy for recruitment and investment decisions.