Best Left Wingers in the Bundesliga (Jun 2026)
Ranked by Analytical Strength Score
Market Overview: Bundesliga Left Wingers 2024-25
Our database tracked 26 Bundesliga Left Wingers in the 2024-25 season, representing 18 clubs with a combined market value of €287.7M. The average market value for Bundesliga Left Wingers was €11.1M, with the average age at 24.8 years old.
The most valuable left winger in the Bundesliga was Luis Díaz, worth €70.0M and played for Bayern Munich at 29 years old. The top 5 Left Wingers averaged €35.2M in market value, including Antonio Nusa and Jean-Mattéo Bahoya.
Age distribution showed the youngest tracked left winger was Tidiam Gomis (19 years, RB Leipzig, €3.0M), while the oldest was Vincenzo Grifo (33 years, SC Freiburg, €5.0M). Research shows Left Wingers typically peak at age 26.
Historical analysis showed 15 Left Wingers (58%) increased in market value over the following 12 months based on age-curve trajectories, then-current performance trends, and playing time analysis. The Bundesliga market for Left Wingers remained actively developing with emerging talent in the 2024-25 season.
💡 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.
Explore Market Size by Position in Bundesliga
Interactive bubble chart showing predicted 2-year growth vs current age for all Bundesliga Left Wingers. Identify undervalued assets and track market momentum across 18 clubs with €287.7M combined value.
Age Distribution: Bundesliga Left Wingers
The Bundesliga LW market shows 5 distinct age segments, with the largest cohort in the 21-23 bracket (10 players, 38% of market). The 21-23 age group holds the most value at €124.7M, averaging €12.5M per player.
Top Left Wingers by Age Bracket
U21 Years (4 players)
21-23 Years (10 players)
24-26 Years (1 players)
27-29 Years (8 players)
Market Value Distribution
Elite Tier Concentration
The top 3 Left Wingers (12% of players) control €127.0M
Market Tiers
Market structure shows distributed value with elite (€50m+) tier representing 4% of the Bundesliga LW pool.
Elite (€50M+)
Premium (€30-50M)
High (€15-30M)
Club Distribution: Bundesliga Left Wingers
Among 18 Bundesliga clubs, Bayern Munich leads with 1 Left Wingers worth €70.0M (averaging €70.0M per player). The top 10 clubs account for 65% of tracked Left Wingers.
Bayern Munich (1 Left Wingers)
Bayer 04 Leverkusen (2 Left Wingers)
RB Leipzig (2 Left Wingers)
Eintracht Frankfurt (1 Left Wingers)
Player Rankings
Ranked by APE Strength Score. Click any player to view full profile, or click the chart icon to see value history.
Luis Díaz
Bayern Munich • 29 years old
€90.4M
€70.0M
-22.6%
Expected: €60.4M
92.3
Antonio Nusa
RB Leipzig • 21 years old
€27.7M
€32.0M
+15.6%
Expected: €36.7M
82.3
Jean-Mattéo Bahoya
Eintracht Frankfurt • 21 years old
€21.6M
€25.0M
+15.6%
Expected: €27.6M
75.6
Eliesse Ben Seghir
Bayer 04 Leverkusen • 21 years old
€20.8M
€24.0M
+15.6%
Expected: €26.5M
75.1
Bazoumana Touré
TSG 1899 Hoffenheim • 20 years old
€21.6M
€25.0M
+15.6%
Expected: €28.7M
75.0
Samuel Mbangula
SV Werder Bremen • 22 years old
€12.1M
€14.0M
+15.6%
Expected: €14.8M
69.0
Jakub Kaminski
1.FC Köln • 23 years old
€10.4M
€12.0M
+15.6%
Expected: €12.8M
67.7
Martin Terrier
Bayer 04 Leverkusen • 29 years old
€15.5M
€12.0M
-22.6%
Expected: €9.9M
66.6
Robin Hack
Borussia Mönchengladbach • 27 years old
€12.7M
€12.0M
-5.4%
Expected: €10.5M
66.4
Chris Führich
VfB Stuttgart • 28 years old
€12.9M
€10.0M
-22.6%
Expected: €8.8M
60.6
Ismaël Gharbi
FC Augsburg • 22 years old
€6.1M
€7.0M
+15.6%
Expected: €7.4M
56.7
Derry Scherhant
SC Freiburg • 23 years old
€5.2M
€6.0M
+15.6%
Expected: €6.4M
55.4
Marco Grüll
SV Werder Bremen • 27 years old
€6.3M
€6.0M
-5.4%
Expected: €5.3M
54.1
Vincenzo Grifo
SC Freiburg • 33 years old
€6.5M
€5.0M
-22.6%
Expected: €4.4M
52.5
Clement Bischoff
Red Bull Salzburg • 20 years old
€4.3M
€5.0M
+15.6%
Expected: €5.7M
51.0
Jean-Luc Dompé
Hamburger SV • 30 years old
€4.5M
€3.5M
-22.6%
Expected: €2.9M
47.8
Mathias Pereira Lage
FC St. Pauli • 29 years old
€4.5M
€3.5M
-22.6%
Expected: €2.9M
47.6
Linton Maina
1.FC Köln • 26 years old
€2.6M
€3.0M
+15.6%
Expected: €3.1M
41.8
Tidiam Gomis
RB Leipzig • 19 years old
€2.6M
€3.0M
+15.6%
Expected: €3.6M
40.8
Petter Nosa Dahl
Rapid Vienna • 22 years old
€2.2M
€2.5M
+15.6%
Expected: €2.6M
40.0
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)
TSG 1899 Hoffenheim's Bazoumana Touré at 20 years old has the highest Pre-Peak Value Efficiency at 5.00×. That means Bazoumana Touré is valued 5.00× higher than the median player in the U21 age bracket—representing exceptional value before reaching peak age.
In second is RB Leipzig's Antonio Nusa, who is 21 years old, with a 2.67× PPVE. Third is Jean-Mattéo Bahoya of Eintracht Frankfurt, who is 21 years old with a 2.08× 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 5.00× means the player is worth 400% 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 | Bazoumana Touré TSG 1899 Hoffenheim | 20 | U21 | €25.0M | €5.0M | 5.00× |
| #2 | Antonio Nusa RB Leipzig | 21 | 21-23 | €32.0M | €12.0M | 2.67× |
| #3 | Jean-Mattéo Bahoya Eintracht Frankfurt | 21 | 21-23 | €25.0M | €12.0M | 2.08× |
| #4 | Eliesse Ben Seghir Bayer 04 Leverkusen | 21 | 21-23 | €24.0M | €12.0M | 2.00× |
| #5 | Samuel Mbangula SV Werder Bremen | 22 | 21-23 | €14.0M | €12.0M | 1.17× |
| #6 | Jakub Kaminski 1.FC Köln | 23 | 21-23 | €12.0M | €12.0M | 1.00× |
| #7 | Clement Bischoff Red Bull Salzburg | 20 | U21 | €5.0M | €5.0M | 1.00× |
| #8 | Tidiam Gomis RB Leipzig | 19 | U21 | €3.0M | €5.0M | 0.60× |
| #9 | Ismaël Gharbi FC Augsburg | 22 | 21-23 | €7.0M | €12.0M | 0.58× |
| #10 | Derry Scherhant SC Freiburg | 23 | 21-23 | €6.0M | €12.0M | 0.50× |
| #11 | Petter Nosa Dahl Rapid Vienna | 22 | 21-23 | €2.5M | €12.0M | 0.21× |
| #12 | Justin Diehl VfB Stuttgart | 21 | 21-23 | €1.8M | €12.0M | 0.15× |
| #13 | Mickael Dosso Wolfsberger AC | 20 | U21 | €175K | €5.0M | 0.03× |
| #14 | David Preu 1.FC Union Berlin | 21 | 21-23 | €400K | €12.0M | 0.03× |
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)
RB Leipzig's Tidiam Gomis at 19 years old has the highest Return-to-Peak Potential at +40%. That means Tidiam Gomis is projected to appreciate 40% as they reach their peak age in 7 years—representing significant upside before entering their prime.
In second is Wolfsberger AC's Mickael Dosso, who is 20 years old, with a +35% RPP (6 years to peak). Third is Bazoumana Touré of TSG 1899 Hoffenheim, who is 20 years old with a +35% RPP (6 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 40% RPP means the player is expected to gain 40% 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 | Tidiam Gomis RB Leipzig | 19 | 7 | €3.0M | €5.0M | +40% |
| #2 | Mickael Dosso Wolfsberger AC | 20 | 6 | €175K | €270K | +35% |
| #3 | Bazoumana Touré TSG 1899 Hoffenheim | 20 | 6 | €25.0M | €38.6M | +35% |
| #4 | Clement Bischoff Red Bull Salzburg | 20 | 6 | €5.0M | €7.7M | +35% |
| #5 | Antonio Nusa RB Leipzig | 21 | 5 | €32.0M | €46.0M | +30% |
| #6 | Justin Diehl VfB Stuttgart | 21 | 5 | €1.8M | €2.6M | +30% |
| #7 | Jean-Mattéo Bahoya Eintracht Frankfurt | 21 | 5 | €25.0M | €35.9M | +30% |
| #8 | David Preu 1.FC Union Berlin | 21 | 5 | €400K | €575K | +30% |
| #9 | Eliesse Ben Seghir Bayer 04 Leverkusen | 21 | 5 | €24.0M | €34.5M | +30% |
| #10 | Petter Nosa Dahl Rapid Vienna | 22 | 4 | €2.5M | €3.3M | +25% |
| #11 | Samuel Mbangula SV Werder Bremen | 22 | 4 | €14.0M | €18.7M | +25% |
| #12 | Ismaël Gharbi FC Augsburg | 22 | 4 | €7.0M | €9.4M | +25% |
| #13 | Jakub Kaminski 1.FC Köln | 23 | 3 | €12.0M | €14.9M | +20% |
| #14 | Derry Scherhant SC Freiburg | 23 | 3 | €6.0M | €7.5M | +20% |
Risk-Adjusted Upside (RAU)
Upside potential weighted against forecast uncertainty. Higher RAU = better risk-reward profile.
Understanding Risk-Adjusted Upside (RAU)
RB Leipzig's Tidiam Gomis has the highest Risk-Adjusted Upside at 58.0. That means Tidiam Gomis has 19% upside potential with only 0% forecast uncertainty—representing excellent risk-reward for value appreciation.
In second is RB Leipzig's Antonio Nusa with a 46.6 RAU (15% upside, 0% uncertainty). Third is Mickael Dosso of Wolfsberger AC with a 46.3 RAU (15% upside, 0% uncertainty).
How RAU is calculated: RAU divides upside potential by forecast uncertainty (RAU = Upside % ÷ Uncertainty %). A RAU of 58.0 means the upside is 58.0× 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 | Tidiam Gomis RB Leipzig | €3.6M | €3.1M-4.1M | +19% | 58.0 |
| #2 | Antonio Nusa RB Leipzig | €36.7M | €31.7M-41.8M | +15% | 46.6 |
| #3 | Mickael Dosso Wolfsberger AC | €201K | €173K-228K | +15% | 46.3 |
| #4 | Bazoumana Touré TSG 1899 Hoffenheim | €28.7M | €24.7M-32.6M | +15% | 46.3 |
| #5 | Clement Bischoff Red Bull Salzburg | €5.7M | €4.9M-6.5M | +15% | 46.3 |
| #6 | Eliesse Ben Seghir Bayer 04 Leverkusen | €26.5M | €22.8M-30.1M | +10% | 33.7 |
| #7 | Jean-Mattéo Bahoya Eintracht Frankfurt | €27.6M | €23.8M-31.4M | +10% | 33.7 |
| #8 | David Preu 1.FC Union Berlin | €441K | €380K-502K | +10% | 33.7 |
| #9 | Justin Diehl VfB Stuttgart | €2.0M | €1.7M-2.3M | +10% | 33.7 |
| #10 | Jakub Kaminski 1.FC Köln | €12.8M | €11.3M-14.4M | +7% | 27.5 |
| #11 | Derry Scherhant SC Freiburg | €6.4M | €5.7M-7.2M | +7% | 27.5 |
| #12 | Samuel Mbangula SV Werder Bremen | €14.8M | €13.0M-16.6M | +6% | 23.0 |
| #13 | Ismaël Gharbi FC Augsburg | €7.4M | €6.5M-8.3M | +6% | 23.0 |
| #14 | Petter Nosa Dahl Rapid Vienna | €2.6M | €2.3M-3.0M | +6% | 23.0 |
| #15 | Linton Maina 1.FC Köln | €3.1M | €2.7M-3.5M | +3% | 12.0 |
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 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)
Wolfsberger AC's Donis Avdijaj in the 27-29 age bracket has the highest Age-Share Concentration at +9.7%. That means Luis Díaz captures 40.4% of total market value while representing only 30.8% of players in their age group—showing dominant elite status.
In second is VfB Stuttgart's Chris Führich with a +9.7% ASC (40.4% value share vs 30.8% player share in 27-29 bracket). Third is Mathias Honsak of 1.FC Heidenheim 1846 with a +9.7% ASC (40.4% value vs 30.8% players in 27-29 bracket).
How ASC is calculated: ASC = (% of total value) - (% of total players) in age bracket. A +9.7% ASC means the player captures 9.7% 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 | Donis Avdijaj Wolfsberger AC | 27-29 | 40.4% | 30.8% | +9.7% |
| #2 | Chris Führich VfB Stuttgart | 27-29 | 40.4% | 30.8% | +9.7% |
| #3 | Mathias Honsak 1.FC Heidenheim 1846 | 27-29 | 40.4% | 30.8% | +9.7% |
| #4 | Robin Hack Borussia Mönchengladbach | 27-29 | 40.4% | 30.8% | +9.7% |
| #5 | Marco Grüll SV Werder Bremen | 27-29 | 40.4% | 30.8% | +9.7% |
| #6 | Mathias Pereira Lage FC St. Pauli | 27-29 | 40.4% | 30.8% | +9.7% |
| #7 | Martin Terrier Bayer 04 Leverkusen | 27-29 | 40.4% | 30.8% | +9.7% |
| #8 | Luis Díaz Bayern Munich | 27-29 | 40.4% | 30.8% | +9.7% |
| #9 | Marius Bülter 1.FC Köln | 30+ | 3.6% | 11.5% | -7.9% |
| #10 | Vincenzo Grifo SC Freiburg | 30+ | 3.6% | 11.5% | -7.9% |
| #11 | Jean-Luc Dompé Hamburger SV | 30+ | 3.6% | 11.5% | -7.9% |
| #12 | Jakub Kaminski 1.FC Köln | 21-23 | 43.3% | 38.5% | +4.9% |
| #13 | Samuel Mbangula SV Werder Bremen | 21-23 | 43.3% | 38.5% | +4.9% |
| #14 | Justin Diehl VfB Stuttgart | 21-23 | 43.3% | 38.5% | +4.9% |
| #15 | David Preu 1.FC Union Berlin | 21-23 | 43.3% | 38.5% | +4.9% |
| #16 | Ismaël Gharbi FC Augsburg | 21-23 | 43.3% | 38.5% | +4.9% |
| #17 | Eliesse Ben Seghir Bayer 04 Leverkusen | 21-23 | 43.3% | 38.5% | +4.9% |
| #18 | Derry Scherhant SC Freiburg | 21-23 | 43.3% | 38.5% | +4.9% |
| #19 | Antonio Nusa RB Leipzig | 21-23 | 43.3% | 38.5% | +4.9% |
| #20 | Petter Nosa Dahl Rapid Vienna | 21-23 | 43.3% | 38.5% | +4.9% |
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: 1 immediate targets, 13 standard acquisitions, 0 watch-list prospects, 4 at peak.
BUY NOW - High Upside
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 €70.0M. 1 undervalued, 0 premium.
Value Positioning vs Peers
| Player | Market Value | Position Median | Z-Score | Assessment |
|---|---|---|---|---|
Marco Grüll SV Werder Bremen | €6.0M | €6.0M | -3.00 | Undervalued |
Mickael Dosso Wolfsberger AC | €175K | €6.0M | -1.00 | Good Value |
Marius Bülter 1.FC Köln | €2.0M | €6.0M | -1.00 | Good Value |
Chris Führich VfB Stuttgart | €10.0M | €6.0M | -1.00 | Good Value |
Eliesse Ben Seghir Bayer 04 Leverkusen | €24.0M | €6.0M | -1.00 | Good Value |
Derry Scherhant SC Freiburg | €6.0M | €6.0M | -0.86 | Good Value |
Ismaël Gharbi FC Augsburg | €7.0M | €6.0M | -0.71 | Good Value |
David Preu 1.FC Union Berlin | €400K | €6.0M | -0.67 | Good Value |
Donis Avdijaj Wolfsberger AC | €800K | €6.0M | -0.44 | Fair Value |
Bazoumana Touré TSG 1899 Hoffenheim | €25.0M | €6.0M | 0.00 | Fair Value |
Vincenzo Grifo SC Freiburg | €5.0M | €6.0M | 0.00 | Fair Value |
Mathias Honsak 1.FC Heidenheim 1846 | €2.0M | €6.0M | 0.00 | Fair Value |
Robin Hack Borussia Mönchengladbach | €12.0M | €6.0M | 0.00 | Fair Value |
Jean-Luc Dompé Hamburger SV | €3.5M | €6.0M | 0.00 | Fair Value |
Linton Maina 1.FC Köln | €3.0M | €6.0M | 0.00 | Fair Value |
Jakub Kaminski 1.FC Köln | €12.0M | €6.0M | 0.00 | Fair Value |
Martin Terrier Bayer 04 Leverkusen | €12.0M | €6.0M | 0.00 | Fair Value |
Luis Díaz Bayern Munich | €70.0M | €6.0M | 0.00 | Fair Value |
Justin Diehl VfB Stuttgart | €1.8M | €6.0M | 0.00 | Fair Value |
Antonio Nusa RB Leipzig | €32.0M | €6.0M | 0.00 | Fair Value |