Best U23 Young Midfielders in the MLS
36 players aged 23 or under · ranked by Analytical Strength Index
Best Young Midfielders 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.
Telasco Segovia
Club Internacional de Fútbol Miami • 23 years old
€5.2M
€6.0M
+15.6%
Expected: €5.8M
54.7
Jack McGlynn
Houston Dynamo • 23 years old
€4.3M
€5.0M
+15.6%
Expected: €4.9M
52.4
Quinn Sullivan
Philadelphia Union • 22 years old
€4.3M
€5.0M
+15.6%
Expected: €5.1M
52.0
Niko Tsakiris
San Jose Earthquakes • 21 years old
€4.3M
€5.0M
+15.6%
Expected: €5.1M
51.6
Owen Wolff
Austin FC • 21 years old
€3.5M
€4.0M
+15.6%
Expected: €4.1M
48.8
Nectarios Triantis
Minnesota United FC • 23 years old
€3.0M
€3.5M
+15.6%
Expected: €3.4M
48.0
Beau Leroux
San Jose Earthquakes • 23 years old
€2.6M
€3.0M
+15.6%
Expected: €2.9M
42.5
Samuel Gidi
Football Club Cincinnati • 22 years old
€2.2M
€2.5M
+15.6%
Expected: €2.5M
39.8
Brooklyn Raines
New England Revolution • 21 years old
€2.2M
€2.5M
+15.6%
Expected: €2.5M
39.4
Taha Habroune
Columbus Crew • 20 years old
€2.2M
€2.5M
+15.6%
Expected: €2.8M
38.9
Ronald Donkor
Red Bull New York • 21 years old
€1.7M
€2.0M
+15.6%
Expected: €2.0M
36.6
Owen Gene
Minnesota United FC • 23 years old
€1.3M
€1.5M
+15.6%
Expected: €1.5M
33.9
Nicolás Dubersarsky
Austin FC • 21 years old
€1.3M
€1.5M
+15.6%
Expected: €1.5M
33.0
Baye Coulibaly
Charlotte Football Club • 20 years old
€1.3M
€1.5M
+15.6%
Expected: €1.7M
32.6
Ajani Fortune
Atlanta United Football Club • 23 years old
€1.0M
€1.2M
+15.6%
Expected: €1.2M
31.1
Elijah Wynder
Los Angeles Galaxy • 23 years old
€1.0M
€1.2M
+15.6%
Expected: €1.2M
31.1
Ran Binyamin
FC Dallas • 22 years old
€1.0M
€1.2M
+15.6%
Expected: €1.2M
30.6
Nikola Petković
Seattle Sounders FC • 23 years old
€865K
€1.0M
+15.6%
Expected: €970K
28.8
Sergio Oregel
Chicago Fire Soccer Club • 21 years old
€865K
€1.0M
+15.6%
Expected: €1.0M
28.0
Noel Buck
San Jose Earthquakes • 21 years old
€865K
€1.0M
+15.6%
Expected: €1.0M
28.0
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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 Midfielders. Identify undervalued assets and track market momentum across 24 clubs with €59.2M combined value.
Age Distribution: MLS Young Midfielders
The MLS CM market shows 2 distinct age segments, with the largest cohort in the 21-23 bracket (24 players, 69% of market). The 21-23 age group holds the most value at €50.7M, averaging €2.1M per player.
Top Young Midfielders by Age Bracket
U21 Years (11 players)
21-23 Years (24 players)
Market Value Distribution
Elite Tier Concentration
The top 4 Young Midfielders (11% of players) control €21.0M
Market Tiers
Market structure shows distributed value with mid (€5-15m) tier representing 11% of the MLS CM pool.
Mid (€5-15M)
Emerging (<€5M)
Club Distribution: MLS Young Midfielders
Among 24 MLS clubs, San Jose Earthquakes leads with 3 Young Midfielders worth €9.0M (averaging €3.0M per player). The top 10 clubs account for 54% of tracked Young Midfielders.
San Jose Earthquakes (3 Young Midfielders)
Club Internacional de Fútbol Miami (2 Young Midfielders)
Austin FC (2 Young Midfielders)
Houston Dynamo (1 Young Midfielders)
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)
Columbus Crew's Taha Habroune at 20 years old has the highest Pre-Peak Value Efficiency at 4.17×. That means Taha Habroune is valued 4.17× higher than the median player in the U21 age bracket-representing exceptional value before reaching peak age.
In second is Club Internacional de Fútbol Miami's Telasco Segovia, who is 23 years old, with a 4.00× PPVE. Third is Jack McGlynn of Houston Dynamo, who is 23 years old with a 3.33× 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 4.17× means the player is worth 317% 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 | Taha Habroune Columbus Crew | 20 | U21 | €2.5M | €600K | 4.17× |
| #2 | Telasco Segovia Club Internacional de Fútbol Miami | 23 | 21-23 | €6.0M | €1.5M | 4.00× |
| #3 | Jack McGlynn Houston Dynamo | 23 | 21-23 | €5.0M | €1.5M | 3.33× |
| #4 | Quinn Sullivan Philadelphia Union | 22 | 21-23 | €5.0M | €1.5M | 3.33× |
| #5 | Niko Tsakiris San Jose Earthquakes | 21 | 21-23 | €5.0M | €1.5M | 3.33× |
| #6 | Owen Wolff Austin FC | 21 | 21-23 | €4.0M | €1.5M | 2.67× |
| #7 | Baye Coulibaly Charlotte Football Club | 20 | U21 | €1.5M | €600K | 2.50× |
| #8 | Nectarios Triantis Minnesota United FC | 23 | 21-23 | €3.5M | €1.5M | 2.33× |
| #9 | Beau Leroux San Jose Earthquakes | 23 | 21-23 | €3.0M | €1.5M | 2.00× |
| #10 | Samuel Gidi Football Club Cincinnati | 22 | 21-23 | €2.5M | €1.5M | 1.67× |
| #11 | Jonathan Shore New York City Football Club | 19 | U21 | €1.0M | €600K | 1.67× |
| #12 | Cooper Sanchez Atlanta United Football Club | 18 | U21 | €1.0M | €600K | 1.67× |
| #13 | Brooklyn Raines New England Revolution | 21 | 21-23 | €2.5M | €1.5M | 1.67× |
| #14 | Jeevan Badwal Vancouver Whitecaps FC | 20 | U21 | €800K | €600K | 1.33× |
| #15 | Ronald Donkor Red Bull New York | 21 | 21-23 | €2.0M | €1.5M | 1.33× |
| #16 | Luca Moisa Real Salt Lake | 18 | U21 | €600K | €600K | 1.00× |
| #17 | Nicolás Dubersarsky Austin FC | 21 | 21-23 | €1.5M | €1.5M | 1.00× |
| #18 | Owen Gene Minnesota United FC | 23 | 21-23 | €1.5M | €1.5M | 1.00× |
| #19 | Elijah Wynder Los Angeles Galaxy | 23 | 21-23 | €1.2M | €1.5M | 0.80× |
| #20 | Ajani Fortune Atlanta United Football Club | 23 | 21-23 | €1.2M | €1.5M | 0.80× |
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)
Atlanta United Football Club's Cooper Sanchez at 18 years old has the highest Return-to-Peak Potential at +48%. That means Cooper Sanchez is projected to appreciate 48% as they reach their peak age in 8 years-representing significant upside before entering their prime.
In second is Real Salt Lake's Luca Moisa, who is 18 years old, with a +48% RPP (8 years to peak). Third is Máximo Carrizo of New York City Football Club, who is 18 years old with a +48% RPP (8 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 48% RPP means the player is expected to gain 48% 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 | Cooper Sanchez Atlanta United Football Club | 18 | 8 | €1.0M | €1.9M | +48% |
| #2 | Luca Moisa Real Salt Lake | 18 | 8 | €600K | €1.2M | +48% |
| #3 | Máximo Carrizo New York City Football Club | 18 | 8 | €400K | €769K | +48% |
| #4 | Stiven Jimenez Football Club Cincinnati | 19 | 7 | €200K | €357K | +44% |
| #5 | Santi Morales Club Internacional de Fútbol Miami | 19 | 7 | €125K | €223K | +44% |
| #6 | Jonathan Shore New York City Football Club | 19 | 7 | €1.0M | €1.8M | +44% |
| #7 | Cole Mrowka Columbus Crew | 20 | 6 | €125K | €208K | +40% |
| #8 | Jeevan Badwal Vancouver Whitecaps FC | 20 | 6 | €800K | €1.3M | +40% |
| #9 | Kwaku Agyabeng Sporting Kansas City | 20 | 6 | €250K | €415K | +40% |
| #10 | Taha Habroune Columbus Crew | 20 | 6 | €2.5M | €4.2M | +40% |
| #11 | Baye Coulibaly Charlotte Football Club | 20 | 6 | €1.5M | €2.5M | +40% |
| #12 | Nicolás Dubersarsky Austin FC | 21 | 5 | €1.5M | €2.3M | +35% |
| #13 | Markus Cimermancic Toronto FC | 21 | 5 | €250K | €386K | +35% |
| #14 | Ronald Donkor Red Bull New York | 21 | 5 | €2.0M | €3.1M | +35% |
| #15 | Owen Wolff Austin FC | 21 | 5 | €4.0M | €6.2M | +35% |
| #16 | Sergio Oregel Chicago Fire Soccer Club | 21 | 5 | €1.0M | €1.5M | +35% |
| #17 | Noel Buck San Jose Earthquakes | 21 | 5 | €1.0M | €1.5M | +35% |
| #18 | Brooklyn Raines New England Revolution | 21 | 5 | €2.5M | €3.9M | +35% |
| #19 | Niko Tsakiris San Jose Earthquakes | 21 | 5 | €5.0M | €7.7M | +35% |
| #20 | Miguel Perez St. Louis City Soccer Club | 21 | 5 | €500K | €773K | +35% |
Risk-Adjusted Upside (RAU)
Upside potential weighted against forecast uncertainty. Higher RAU = better risk-reward profile.
Understanding Risk-Adjusted Upside (RAU)
Charlotte Football Club's Baye Coulibaly has the highest Risk-Adjusted Upside at 31.1. That means Baye Coulibaly has 10% upside potential with only 0% forecast uncertainty-representing excellent risk-reward for value appreciation.
In second is Club Internacional de Fútbol Miami's Santi Morales with a 31.1 RAU (10% upside, 0% uncertainty). Third is Jonathan Shore of New York City Football Club 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 31.1 means the upside is 31.1× 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 | Baye Coulibaly Charlotte Football Club | €1.7M | €1.4M-1.9M | +10% | 31.1 |
| #2 | Santi Morales Club Internacional de Fútbol Miami | €138K | €117K-158K | +10% | 31.1 |
| #3 | Jonathan Shore New York City Football Club | €1.1M | €938K-1.3M | +10% | 31.1 |
| #4 | Cole Mrowka Columbus Crew | €138K | €117K-158K | +10% | 31.1 |
| #5 | Cooper Sanchez Atlanta United Football Club | €1.1M | €938K-1.3M | +10% | 31.1 |
| #6 | Taha Habroune Columbus Crew | €2.8M | €2.3M-3.2M | +10% | 31.1 |
| #7 | Kwaku Agyabeng Sporting Kansas City | €276K | €234K-317K | +10% | 31.1 |
| #8 | Luca Moisa Real Salt Lake | €662K | €563K-760K | +10% | 31.1 |
| #9 | Stiven Jimenez Football Club Cincinnati | €221K | €188K-253K | +10% | 31.1 |
| #10 | Jeevan Badwal Vancouver Whitecaps FC | €882K | €750K-1.0M | +10% | 31.1 |
| #11 | Máximo Carrizo New York City Football Club | €441K | €375K-507K | +10% | 31.1 |
| #12 | Samuel Gidi Football Club Cincinnati | €2.5M | €2.2M-2.9M | +1% | 5.4 |
| #13 | Quinn Sullivan Philadelphia Union | €5.1M | €4.4M-5.7M | +1% | 5.4 |
| #14 | Wayne Frederick Colorado Rapids | €609K | €529K-688K | +1% | 5.4 |
| #15 | Ran Binyamin FC Dallas | €1.2M | €1.1M-1.4M | +1% | 5.4 |
| #16 | Brooklyn Raines New England Revolution | €2.5M | €2.2M-2.9M | +1% | 4.7 |
| #17 | Niko Tsakiris San Jose Earthquakes | €5.1M | €4.3M-5.8M | +1% | 4.7 |
| #18 | Nicolás Dubersarsky Austin FC | €1.5M | €1.3M-1.7M | +1% | 4.7 |
| #19 | Markus Cimermancic Toronto FC | €254K | €216K-291K | +1% | 4.7 |
| #20 | Ronald Donkor Red Bull New York | €2.0M | €1.7M-2.3M | +1% | 4.7 |
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 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)
Toronto FC's Markus Cimermancic in the 21-23 age bracket has the highest Age-Share Concentration at +17.1%. That means Telasco Segovia captures 85.6% of total market value while representing only 68.6% of players in their age group-showing dominant elite status.
In second is Football Club Cincinnati's Samuel Gidi with a +17.1% ASC (85.6% value share vs 68.6% player share in 21-23 bracket). Third is Wayne Frederick of Colorado Rapids with a +17.1% ASC (85.6% value vs 68.6% players in 21-23 bracket).
How ASC is calculated: ASC = (% of total value) - (% of total players) in age bracket. A +17.1% ASC means the player captures 17.1% 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 | Markus Cimermancic Toronto FC | 21-23 | 85.6% | 68.6% | +17.1% |
| #2 | Samuel Gidi Football Club Cincinnati | 21-23 | 85.6% | 68.6% | +17.1% |
| #3 | Wayne Frederick Colorado Rapids | 21-23 | 85.6% | 68.6% | +17.1% |
| #4 | Ronald Donkor Red Bull New York | 21-23 | 85.6% | 68.6% | +17.1% |
| #5 | Nicolás Dubersarsky Austin FC | 21-23 | 85.6% | 68.6% | +17.1% |
| #6 | Beau Leroux San Jose Earthquakes | 21-23 | 85.6% | 68.6% | +17.1% |
| #7 | Nikola Petković Seattle Sounders FC | 21-23 | 85.6% | 68.6% | +17.1% |
| #8 | Will Reilly Atlanta United Football Club | 21-23 | 85.6% | 68.6% | +17.1% |
| #9 | Elijah Wynder Los Angeles Galaxy | 21-23 | 85.6% | 68.6% | +17.1% |
| #10 | Jack McGlynn Houston Dynamo | 21-23 | 85.6% | 68.6% | +17.1% |
| #11 | Alejandro Alvarado San Diego Football Club | 21-23 | 85.6% | 68.6% | +17.1% |
| #12 | Ajani Fortune Atlanta United Football Club | 21-23 | 85.6% | 68.6% | +17.1% |
| #13 | Quinn Sullivan Philadelphia Union | 21-23 | 85.6% | 68.6% | +17.1% |
| #14 | Owen Wolff Austin FC | 21-23 | 85.6% | 68.6% | +17.1% |
| #15 | Sergio Oregel Chicago Fire Soccer Club | 21-23 | 85.6% | 68.6% | +17.1% |
| #16 | Telasco Segovia Club Internacional de Fútbol Miami | 21-23 | 85.6% | 68.6% | +17.1% |
| #17 | Noel Buck San Jose Earthquakes | 21-23 | 85.6% | 68.6% | +17.1% |
| #18 | Griffin Dillon Real Salt Lake | 21-23 | 85.6% | 68.6% | +17.1% |
| #19 | Brooklyn Raines New England Revolution | 21-23 | 85.6% | 68.6% | +17.1% |
| #20 | Owen Gene Minnesota United FC | 21-23 | 85.6% | 68.6% | +17.1% |
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, 11 standard acquisitions, 24 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 €5.0M. 0 undervalued, 1 premium.
Value Positioning vs Peers
| Player | Market Value | Position Median | Z-Score | Assessment |
|---|---|---|---|---|
Santi Morales Club Internacional de Fútbol Miami | €125K | €1.0M | -0.59 | Good Value |
Cole Mrowka Columbus Crew | €125K | €1.0M | -0.59 | Good Value |
Alejandro Alvarado San Diego Football Club | €200K | €1.0M | -0.53 | Good Value |
Markus Cimermancic Toronto FC | €250K | €1.0M | -0.50 | Fair Value |
Stiven Jimenez Football Club Cincinnati | €200K | €1.0M | -0.50 | Fair Value |
Kwaku Agyabeng Sporting Kansas City | €250K | €1.0M | -0.44 | Fair Value |
Will Reilly Atlanta United Football Club | €400K | €1.0M | -0.42 | Fair Value |
Miguel Perez St. Louis City Soccer Club | €500K | €1.0M | -0.37 | Fair Value |
Wayne Frederick Colorado Rapids | €600K | €1.0M | -0.32 | Fair Value |
Griffin Dillon Real Salt Lake | €600K | €1.0M | -0.32 | Fair Value |
Máximo Carrizo New York City Football Club | €400K | €1.0M | -0.25 | Fair Value |
Nikola Petković Seattle Sounders FC | €1.0M | €1.0M | -0.11 | Fair Value |
Sergio Oregel Chicago Fire Soccer Club | €1.0M | €1.0M | -0.11 | Fair Value |
Noel Buck San Jose Earthquakes | €1.0M | €1.0M | -0.11 | Fair Value |
Luca Moisa Real Salt Lake | €600K | €1.0M | 0.00 | Fair Value |
Elijah Wynder Los Angeles Galaxy | €1.2M | €1.0M | 0.00 | Fair Value |
Jack McGlynn Houston Dynamo | €5.0M | €1.0M | 0.00 | Fair Value |
Ajani Fortune Atlanta United Football Club | €1.2M | €1.0M | 0.00 | Fair Value |
Quinn Sullivan Philadelphia Union | €5.0M | €1.0M | 0.00 | Fair Value |
Niko Tsakiris San Jose Earthquakes | €5.0M | €1.0M | 0.00 | Fair Value |
Market Overview: MLS Young Midfielders 2024-25
Our database tracked 35 MLS Young Midfielders in the 2024-25 season, representing 24 clubs with a combined market value of €59.2M. The average market value for MLS Young Midfielders was €1.7M, with the average age at 21 years old.
The most valuable young midfielder in the MLS was Telasco Segovia, worth €6.0M and played for Club Internacional de Fútbol Miami at 23 years old. The top 5 Young Midfielders averaged €5.0M in market value, including Jack McGlynn and Quinn Sullivan.
Age distribution showed the youngest tracked young midfielder was Cooper Sanchez (18 years, Atlanta United Football Club, €1.0M), while the oldest was Telasco Segovia (23 years, Club Internacional de Fútbol Miami, €6.0M). Research shows Young Midfielders typically peak at age 27.
Historical analysis showed 24 Young Midfielders (69%) 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 Midfielders remained actively developing with emerging talent in the 2024-25 season.
How We Rank MLS Young Midfielders
Our Analytical Strength Index is calibrated specifically for young 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 CM
Historical Achievement Index (35%)
Peak career market value for MLS young 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 young 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 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.
CM Performance Benchmarks
Peak Age: 27 years (technical skill and tactical awareness)
Decline Rate: Widening steps, not a flat rate: about -5% at 28, -10% at 29, steeper from 30 (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: Compounding and banded around a peak of 27: +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: ±12-15% confidence interval
Research Foundation
• Dendir (2016): Age-performance curves for young 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 Young Midfielders in the 2024-25 season
Who are the most valuable Young Midfielders in the MLS in 2024-25?
The most valuable young midfielder in the MLS in 2024-25 is Telasco Segovia, who is worth €6.0M and plays for Club Internacional de Fútbol Miami. The second most valuable is Jack McGlynn (€5.0M, Houston Dynamo), followed by Quinn Sullivan (€5.0M, Philadelphia Union). Our database tracks 35 MLS Young Midfielders with comprehensive market valuations updated for the 2024-25 season.
How are MLS Young Midfielders ranked?
MLS Young Midfielders are ranked by our proprietary Analytical Strength Index, which is specifically calibrated for Young 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 Young Midfielders peak?
Midfielders typically peak at age 27. In our valuation model, value then falls in widening steps rather than at a flat annual rate: around -5% at 28, -10% at 29, -15% at 30, and steeper thereafter. Central midfielders require a blend of physicality, technical skill, and tactical awareness. The optimal playing time for peak performance is around 2,400-2,500 minutes per season.
How much does it cost to sign a top young midfielder from the MLS?
Transfer fees for MLS Young Midfielders vary significantly based on market value, contract length, and club bargaining position. For the top-ranked young midfielder Telasco Segovia (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 Midfielders?
Our 1-year forecast model projects market value changes for MLS Young Midfielders 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-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 young midfielder data come from?
Our MLS young 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 2024-25 season to ensure accuracy for recruitment and investment decisions.