Best Right-Backs in the MLS (Jul 2026)
Ranked by Analytical Strength Index
Market Overview: MLS Right-Backs 2025-26
Our database tracks 15 MLS Right-Backs in the 2025-26 season, representing 13 clubs with a combined market value of €22.2M. The average market value for MLS Right-Backs is €1.5M, with the average age at 28 years old.
The most valuable right-back in the MLS is Mikkel Desler, worth €3.0M and playing for Austin FC at 31 years old. The top 5 Right-Backs average €2.5M in market value, including Reggie Cannon and Silvan Hefti.
Age distribution shows the youngest tracked right-back is Giuseppe Bovalina (21 years, Vancouver Whitecaps FC, €200K), while the oldest is DeAndre Yedlin (33 years, Real Salt Lake, €2.0M). Research shows Right-Backs typically peak at age 27.
Our 1-year forecast model projects 4 Right-Backs (27%) will increase in market value over the next 12 months based on age-curve trajectories, current performance trends, and playing time analysis. The MLS market for Right-Backs remains actively developing with emerging talent in the 2025-26 season.
Explore Market Size by Position in MLS
Interactive bubble chart showing predicted 2-year growth vs current age for all MLS Right-Backs. Identify undervalued assets and track market momentum across 13 clubs with €22.2M 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 Right-Backs
The MLS RB market shows 3 distinct age segments, with the largest cohort in the 30+ bracket (6 players, 40% of market). The 30+ age group holds the most value at €11.0M, averaging €1.8M per player.
Top Right-Backs by Age Bracket
21-23 Years (4 players)
27-29 Years (5 players)
30+ Years (6 players)
Market Value Distribution
Elite Tier Concentration
The top 2 Right-Backs (13% of players) control €6.0M
Market Tiers
Market structure shows concentrated value with emerging (<€5m) tier representing 100% of the MLS RB pool.
Emerging (<€5M)
Club Distribution: MLS Right-Backs
Among 13 MLS clubs, Austin FC leads with 2 Right-Backs worth €5.0M (averaging €2.5M per player). The top 10 clubs account for 80% of tracked Right-Backs.
Austin FC (2 Right-Backs)
Colorado Rapids (1 Right-Backs)
D.C. United (1 Right-Backs)
Real Salt Lake (1 Right-Backs)
Player Rankings
Ranked by Analytical Strength Index. Click any player to view full profile, or click the chart icon to see value history.
Mikkel Desler
Austin FC • 31 years old
€3.9M
€3.0M
-22.6%
Expected: €2.5M
42.9
Reggie Cannon
Colorado Rapids • 28 years old
€3.2M
€3.0M
-5.4%
Expected: €2.7M
42.2
Silvan Hefti
D.C. United • 28 years old
€2.6M
€2.5M
-5.4%
Expected: €2.2M
39.8
DeAndre Yedlin
Real Salt Lake • 33 years old
€2.6M
€2.0M
-22.6%
Expected: €1.8M
38.2
Sergi Palencia
Los Angeles Football Club • 30 years old
€2.6M
€2.0M
-22.6%
Expected: €1.7M
37.5
Jon Gallagher
Austin FC • 30 years old
€2.6M
€2.0M
-22.6%
Expected: €1.7M
37.5
Steven Moreira
Columbus Crew • 31 years old
€1.9M
€1.5M
-22.6%
Expected: €1.3M
34.1
Shaq Moore
FC Dallas • 29 years old
€1.9M
€1.5M
-22.6%
Expected: €1.3M
33.6
Kyle Duncan
Minnesota United FC • 28 years old
€1.6M
€1.5M
-5.4%
Expected: €1.3M
33.4
Willy Kumado
San Diego Football Club • 23 years old
€1.0M
€1.2M
+15.6%
Expected: €1.3M
31.3
Justin Che
Red Bull New York • 22 years old
€605K
€700K
+15.6%
Expected: €772K
24.1
Andy Nájar
Nashville SC • 33 years old
€646K
€500K
-22.6%
Expected: €442K
20.7
Ronald Hernández
Atlanta United Football Club • 28 years old
€476K
€450K
-5.4%
Expected: €398K
18.1
Giuseppe Bovalina
Vancouver Whitecaps FC • 21 years old
€173K
€200K
+15.6%
Expected: €221K
8.0
Juan Mina
Red Bull New York • 21 years old
€173K
€200K
+15.6%
Expected: €229K
7.8
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)
San Diego Football Club's Willy Kumado at 23 years old has the highest Pre-Peak Value Efficiency at 1.71×. That means Willy Kumado is valued 1.71× higher than the median player in the 21-23 age bracket-representing exceptional value before reaching peak age.
In second is Red Bull New York's Justin Che, who is 22 years old, with a 1.00× PPVE. Third is Giuseppe Bovalina of Vancouver Whitecaps FC, who is 21 years old with a 0.29× 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 1.71× means the player is worth 71% 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 | Willy Kumado San Diego Football Club | 23 | 21-23 | €1.2M | €700K | 1.71× |
| #2 | Justin Che Red Bull New York | 22 | 21-23 | €700K | €700K | 1.00× |
| #3 | Giuseppe Bovalina Vancouver Whitecaps FC | 21 | 21-23 | €200K | €700K | 0.29× |
| #4 | Juan Mina Red Bull New York | 21 | 21-23 | €200K | €700K | 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)
Red Bull New York's Juan Mina at 21 years old has the highest Return-to-Peak Potential at +35%. That means Juan Mina is projected to appreciate 35% as they reach their peak age in 5 years-representing significant upside before entering their prime.
In second is Red Bull New York's Justin Che, who is 22 years old, with a +30% RPP (4 years to peak). Third is Giuseppe Bovalina of Vancouver Whitecaps FC, who is 21 years old with a +30% RPP (5 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 35% RPP means the player is expected to gain 35% 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 | Juan Mina Red Bull New York | 21 | 5 | €200K | €309K | +35% |
| #2 | Justin Che Red Bull New York | 22 | 4 | €700K | €1.0M | +30% |
| #3 | Giuseppe Bovalina Vancouver Whitecaps FC | 21 | 5 | €200K | €287K | +30% |
| #4 | Willy Kumado San Diego Football Club | 23 | 3 | €1.2M | €1.6M | +25% |
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 Juan Mina has the highest Risk-Adjusted Upside at 55.6. That means Juan Mina has 15% upside potential with only 0% forecast uncertainty-representing excellent risk-reward for value appreciation.
In second is Red Bull New York's Justin Che with a 46.5 RAU (10% upside, 0% uncertainty). Third is Giuseppe Bovalina of Vancouver Whitecaps FC with a 33.7 RAU (10% upside, 0% uncertainty).
How RAU is calculated: RAU divides upside potential by forecast uncertainty (RAU = Upside % ÷ Uncertainty %). A RAU of 55.6 means the upside is 55.6× 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 | Juan Mina Red Bull New York | €229K | €203K-256K | +15% | 55.6 |
| #2 | Justin Che Red Bull New York | €772K | €695K-849K | +10% | 46.5 |
| #3 | Giuseppe Bovalina Vancouver Whitecaps FC | €221K | €190K-251K | +10% | 33.7 |
| #4 | Willy Kumado San Diego Football Club | €1.3M | €1.1M-1.4M | +6% | 27.6 |
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: right-back 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)
Vancouver Whitecaps FC's Giuseppe Bovalina in the 21-23 age bracket has the highest Age-Share Concentration at +-16.3%. That means Willy Kumado captures 10.3% of total market value while representing only 26.7% of players in their age group-showing dominant elite status.
In second is Red Bull New York's Juan Mina with a +-16.3% ASC (10.3% value share vs 26.7% player share in 21-23 bracket). Third is Justin Che of Red Bull New York with a +-16.3% ASC (10.3% value vs 26.7% players in 21-23 bracket).
How ASC is calculated: ASC = (% of total value) - (% of total players) in age bracket. A +-16.3% ASC means the player captures -16.3% 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 | Giuseppe Bovalina Vancouver Whitecaps FC | 21-23 | 10.3% | 26.7% | -16.3% |
| #2 | Juan Mina Red Bull New York | 21-23 | 10.3% | 26.7% | -16.3% |
| #3 | Justin Che Red Bull New York | 21-23 | 10.3% | 26.7% | -16.3% |
| #4 | Willy Kumado San Diego Football Club | 21-23 | 10.3% | 26.7% | -16.3% |
| #5 | Andy Nájar Nashville SC | 30+ | 49.4% | 40.0% | +9.4% |
| #6 | Steven Moreira Columbus Crew | 30+ | 49.4% | 40.0% | +9.4% |
| #7 | Mikkel Desler Austin FC | 30+ | 49.4% | 40.0% | +9.4% |
| #8 | DeAndre Yedlin Real Salt Lake | 30+ | 49.4% | 40.0% | +9.4% |
| #9 | Sergi Palencia Los Angeles Football Club | 30+ | 49.4% | 40.0% | +9.4% |
| #10 | Jon Gallagher Austin FC | 30+ | 49.4% | 40.0% | +9.4% |
| #11 | Silvan Hefti D.C. United | 27-29 | 40.2% | 33.3% | +6.9% |
| #12 | Shaq Moore FC Dallas | 27-29 | 40.2% | 33.3% | +6.9% |
| #13 | Kyle Duncan Minnesota United FC | 27-29 | 40.2% | 33.3% | +6.9% |
| #14 | Ronald Hernández Atlanta United Football Club | 27-29 | 40.2% | 33.3% | +6.9% |
| #15 | Reggie Cannon Colorado Rapids | 27-29 | 40.2% | 33.3% | +6.9% |
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, 4 standard acquisitions, 0 watch-list prospects, 4 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 €2.0M. 1 undervalued, 1 premium.
Value Positioning vs Peers
| Player | Market Value | Position Median | Z-Score | Assessment |
|---|---|---|---|---|
Andy Nájar Nashville SC | €500K | €1.5M | -3.00 | Undervalued |
Ronald Hernández Atlanta United Football Club | €450K | €1.5M | -1.05 | Good Value |
Steven Moreira Columbus Crew | €1.5M | €1.5M | -1.00 | Good Value |
Giuseppe Bovalina Vancouver Whitecaps FC | €200K | €1.5M | -0.50 | Fair Value |
Juan Mina Red Bull New York | €200K | €1.5M | -0.50 | Fair Value |
DeAndre Yedlin Real Salt Lake | €2.0M | €1.5M | 0.00 | Fair Value |
Sergi Palencia Los Angeles Football Club | €2.0M | €1.5M | 0.00 | Fair Value |
Shaq Moore FC Dallas | €1.5M | €1.5M | 0.00 | Fair Value |
Kyle Duncan Minnesota United FC | €1.5M | €1.5M | 0.00 | Fair Value |
Jon Gallagher Austin FC | €2.0M | €1.5M | 0.00 | Fair Value |
Justin Che Red Bull New York | €700K | €1.5M | 0.00 | Fair Value |
Willy Kumado San Diego Football Club | €1.2M | €1.5M | +0.50 | Fair Value |
Silvan Hefti D.C. United | €2.5M | €1.5M | +1.00 | Above Market |
Reggie Cannon Colorado Rapids | €3.0M | €1.5M | +1.50 | Above Market |
Mikkel Desler Austin FC | €3.0M | €1.5M | +2.00 | Premium |
How We Rank MLS Right-Backs
Our Analytical Strength Index is calibrated specifically for right-backs, 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 RB
Historical Achievement Index (35%)
Peak career market value for MLS right-backs, 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 right-backs, capturing recent form, injuries, and current performance level. Weighted to reflect age-related depreciation patterns.
Playing Time Utilization (18%)
Defenders with 2,500+ minutes score highest, indicating regular starting role and sustained performance.
Age-Adjusted Performance Curve (12%)
Defenders peak at 27 with 5.0%/year decline rate. 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.
RB Performance Benchmarks
Peak Age: 27 years (balance of physicality and tactical intelligence)
Decline Rate: 5.0% per year (moderate decline as positioning offsets pace loss)
Optimal Minutes: 2,500 per season (regular starter with rotation management)
1-Year Market Value Forecast
Probabilistic model combining age-curve depreciation, value momentum, and playing time factors:
• Age Factor: Defender -5.0%/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: ±10% confidence interval
Research Foundation
• Dendir (2016): Age-performance curves for right-backs
• 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 Right-Backs in the 2025-26 season
Who are the most valuable Right-Backs in the MLS in 2025-26?
The most valuable right-back in the MLS in 2025-26 is Mikkel Desler, who is worth €3.0M and plays for Austin FC. The second most valuable is Reggie Cannon (€3.0M, Colorado Rapids), followed by Silvan Hefti (€2.5M, D.C. United). Our database tracks 15 MLS Right-Backs with comprehensive market valuations updated for the 2025-26 season.
How are MLS Right-Backs ranked?
MLS Right-Backs are ranked by our proprietary Analytical Strength Index, which is specifically calibrated for Right-Backs. 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 Right-Backs peak?
Defenders typically peak at age 27, with a decline rate of 5.0% per year after peak. Research shows defenders balance physical attributes with tactical intelligence, allowing them to maintain high performance through their late 20s. The optimal playing time for peak performance is around 2,500 minutes per season.
How much does it cost to sign a top right-back from the MLS?
Transfer fees for MLS Right-Backs vary significantly based on market value, contract length, and club bargaining position. For the top-ranked right-back Mikkel Desler (market value: €3.0M), estimated transfer fees would range from €2.4M to €4.2M 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 Right-Backs?
Our 1-year forecast model projects market value changes for MLS Right-Backs 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-defenders have ±10% 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 right-back data come from?
Our MLS right-back 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 2025-26 season to ensure accuracy for recruitment and investment decisions.