Best Players (All Positions) in the Bundesliga (Mar 2026)
Ranked by Analytical Strength Score
Market Overview: Bundesliga Players (All Positions) 2025-26
Our database tracks 534 Bundesliga Players (All Positions) in the 2025-26 season, representing 34 clubs with a combined market value of €4.3B. The average market value for Bundesliga Players (All Positions) is €8.1M, with the average age at 26.6 years old.
The most valuable player in the Bundesliga is Jamal Musiala, worth €140.0M and playing for Bayern Munich at 23 years old. The top 5 Players (All Positions) average €88.0M in market value, including Michael Olise and Luis Díaz.
Age distribution shows the youngest tracked player is Patrice Covic (18 years, SV Werder Bremen, €2.5M), while the oldest is Manuel Neuer (39 years, Bayern Munich, €4.0M). Research shows Players (All Positions) typically peak at age 26-27.
Our 1-year forecast model projects 244 Players (All Positions) (46%) will increase in market value over the next 12 months based on age-curve trajectories, current performance trends, and playing time analysis. The Bundesliga market for Players (All Positions) remains highly competitive with significant transfer activity expected in the 2025-26 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 Players (All Positions). Identify undervalued assets and track market momentum across 34 clubs with €4.3B combined value.
Age Distribution: Bundesliga Players (All Positions)
The Bundesliga ALL market shows 5 distinct age segments, with the largest cohort in the 30+ bracket (139 players, 26% of market). The 27-29 age group holds the most value at €1.2B, averaging €10.0M per player.
Top Players (All Positions) by Age Bracket
U21 Years (43 players)
21-23 Years (108 players)
24-26 Years (125 players)
27-29 Years (119 players)
Market Value Distribution
Elite Tier Concentration
The top 54 Players (All Positions) (10% of players) control €2.0B
Market Tiers
Market structure shows distributed value with elite (€50m+) tier representing 1% of the Bundesliga ALL pool.
Elite (€50M+)
Premium (€30-50M)
High (€15-30M)
Club Distribution: Bundesliga Players (All Positions)
Among 34 Bundesliga clubs, Bayern Munich leads with 22 Players (All Positions) worth €903.5M (averaging €41.1M per player). The top 10 clubs account for 48% of tracked Players (All Positions).
Bayern Munich (22 Players (All Positions))
Borussia Dortmund (27 Players (All Positions))
Bayer 04 Leverkusen (23 Players (All Positions))
Eintracht Frankfurt (26 Players (All Positions))
Player Rankings
Ranked by APE Strength Score. Click any player to view full profile, or click the chart icon to see value history.
Jamal Musiala
Bayern Munich • 23 years old
€121.1M
€140.0M
+15.6%
Expected: €156.0M
95.5
Michael Olise
Bayern Munich • 24 years old
€86.5M
€100.0M
+15.6%
Expected: €106.6M
95.5
Luis Díaz
Bayern Munich • 29 years old
€90.4M
€70.0M
-22.6%
Expected: €60.4M
92.3
Harry Kane
Bayern Munich • 32 years old
€96.8M
€75.0M
-22.6%
Expected: €68.3M
91.0
Aleksandar Pavlovic
Bayern Munich • 21 years old
€47.6M
€55.0M
+15.6%
Expected: €65.6M
90.2
Angelo Stiller
VfB Stuttgart • 24 years old
€38.9M
€45.0M
+15.6%
Expected: €50.1M
88.8
Nicolas Jackson
Bayern Munich • 24 years old
€43.2M
€50.0M
+15.6%
Expected: €53.3M
88.7
Alphonso Davies
Bayern Munich • 25 years old
€43.2M
€50.0M
+15.6%
Expected: €50.9M
88.2
Joshua Kimmich
Bayern Munich • 31 years old
€58.1M
€45.0M
-22.6%
Expected: €39.0M
88.2
Dayot Upamecano
Bayern Munich • 27 years old
€52.8M
€50.0M
-5.4%
Expected: €45.5M
87.9
Gregor Kobel
Borussia Dortmund • 28 years old
€34.6M
€40.0M
+15.6%
Expected: €40.7M
87.5
Karim Adeyemi
Borussia Dortmund • 24 years old
€38.9M
€45.0M
+15.6%
Expected: €48.0M
87.2
Serhou Guirassy
Borussia Dortmund • 29 years old
€58.1M
€45.0M
-22.6%
Expected: €38.8M
86.6
Castello Lukeba
RB Leipzig • 23 years old
€34.6M
€40.0M
+15.6%
Expected: €44.6M
86.2
Min-jae Kim
Bayern Munich • 29 years old
€51.7M
€40.0M
-22.6%
Expected: €34.5M
85.3
Victor Boniface
SV Werder Bremen • 25 years old
€34.6M
€40.0M
+15.6%
Expected: €40.7M
85.3
Hugo Larsson
Eintracht Frankfurt • 21 years old
€34.6M
€40.0M
+15.6%
Expected: €45.9M
85.0
Exequiel Palacios
Bayer 04 Leverkusen • 27 years old
€42.3M
€40.0M
-5.4%
Expected: €36.4M
84.9
Nico Schlotterbeck
Borussia Dortmund • 26 years old
€34.6M
€40.0M
+15.6%
Expected: €42.9M
84.5
Jonathan Burkardt
Eintracht Frankfurt • 25 years old
€30.3M
€35.0M
+15.6%
Expected: €35.6M
83.6
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)
Bayern Munich's Jamal Musiala at 23 years old has the highest Pre-Peak Value Efficiency at 28.00×. That means Jamal Musiala is valued 28.00× higher than the median player in the 21-23 age bracket—representing exceptional value before reaching peak age.
In second is Bayern Munich's Michael Olise, who is 24 years old, with a 20.00× PPVE. Third is Aleksandar Pavlovic of Bayern Munich, who is 21 years old with a 11.00× 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 28.00× means the player is worth 2700% 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 | Jamal Musiala Bayern Munich | 23 | 21-23 | €140.0M | €5.0M | 28.00× |
| #2 | Michael Olise Bayern Munich | 24 | 24-26 | €100.0M | €5.0M | 20.00× |
| #3 | Aleksandar Pavlovic Bayern Munich | 21 | 21-23 | €55.0M | €5.0M | 11.00× |
| #4 | Alphonso Davies Bayern Munich | 25 | 24-26 | €50.0M | €5.0M | 10.00× |
| #5 | Nicolas Jackson Bayern Munich | 24 | 24-26 | €50.0M | €5.0M | 10.00× |
| #6 | Angelo Stiller VfB Stuttgart | 24 | 24-26 | €45.0M | €5.0M | 9.00× |
| #7 | Karim Adeyemi Borussia Dortmund | 24 | 24-26 | €45.0M | €5.0M | 9.00× |
| #8 | Castello Lukeba RB Leipzig | 23 | 21-23 | €40.0M | €5.0M | 8.00× |
| #9 | Victor Boniface SV Werder Bremen | 25 | 24-26 | €40.0M | €5.0M | 8.00× |
| #10 | Hugo Larsson Eintracht Frankfurt | 21 | 21-23 | €40.0M | €5.0M | 8.00× |
| #11 | Jonathan Burkardt Eintracht Frankfurt | 25 | 24-26 | €35.0M | €5.0M | 7.00× |
| #12 | Malik Tillman Bayer 04 Leverkusen | 23 | 21-23 | €32.0M | €5.0M | 6.40× |
| #13 | Josip Stanisic Bayern Munich | 25 | 24-26 | €32.0M | €5.0M | 6.40× |
| #14 | Mohamed Amoura VfL Wolfsburg | 25 | 24-26 | €32.0M | €5.0M | 6.40× |
| #15 | Johan Bakayoko RB Leipzig | 22 | 21-23 | €30.0M | €5.0M | 6.00× |
| #16 | Felix Nmecha Borussia Dortmund | 25 | 24-26 | €28.0M | €5.0M | 5.60× |
| #17 | Bilal El Khannouss VfB Stuttgart | 21 | 21-23 | €28.0M | €5.0M | 5.60× |
| #18 | Eliesse Ben Seghir Bayer 04 Leverkusen | 21 | 21-23 | €28.0M | €5.0M | 5.60× |
| #19 | Maximilian Beier Borussia Dortmund | 23 | 21-23 | €25.0M | €5.0M | 5.00× |
| #20 | Konstantinos Koulierakis VfL Wolfsburg | 22 | 21-23 | €25.0M | €5.0M | 5.00× |
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)
Borussia Mönchengladbach's Tiago Pereira Cardoso at 19 years old has the highest Return-to-Peak Potential at +52%. That means Tiago Pereira Cardoso is projected to appreciate 52% as they reach their peak age in 7 years—representing significant upside before entering their prime.
In second is FC St. Pauli's Marwin Schmitz, who is 19 years old, with a +44% RPP (7 years to peak). Third is Matteo Bignetti of SK Sturm Graz, who is 21 years old with a +44% 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 52% RPP means the player is expected to gain 52% 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 | Tiago Pereira Cardoso Borussia Mönchengladbach | 19 | 7 | €1.5M | €3.1M | +52% |
| #2 | Marwin Schmitz FC St. Pauli | 19 | 7 | €200K | €357K | +44% |
| #3 | Matteo Bignetti SK Sturm Graz | 21 | 5 | €400K | €715K | +44% |
| #4 | Mathys Angély VfL Wolfsburg | 18 | 8 | €600K | €1.1M | +44% |
| #5 | Patrice Covic SV Werder Bremen | 18 | 8 | €2.5M | €4.5M | +44% |
| #6 | Niklas Swider Borussia Mönchengladbach | 19 | 7 | €250K | €447K | +44% |
| #7 | Mio Backhaus SV Werder Bremen | 21 | 5 | €2.0M | €3.6M | +44% |
| #8 | Tom Ritzy Hülsmann TSV Hartberg | 21 | 5 | €500K | €894K | +44% |
| #9 | Joane Gadou Red Bull Salzburg | 19 | 7 | €15.0M | €24.9M | +40% |
| #10 | Julien Duranville Borussia Dortmund | 19 | 7 | €8.5M | €14.1M | +40% |
| #11 | Almugera Kabar Borussia Dortmund | 19 | 7 | €1.0M | €1.7M | +40% |
| #12 | Assan Ouédraogo RB Leipzig | 19 | 7 | €7.0M | €11.6M | +40% |
| #13 | Silas Ostrzinski Borussia Dortmund | 22 | 4 | €200K | €332K | +40% |
| #14 | Lúkas Petersson TSG 1899 Hoffenheim | 22 | 4 | €250K | €415K | +40% |
| #15 | Daniil Khudyakov SK Sturm Graz | 22 | 4 | €800K | €1.3M | +40% |
| #16 | Frank Feller 1.FC Heidenheim 1846 | 22 | 4 | €500K | €831K | +40% |
| #17 | Luka Vuskovic Hamburger SV | 19 | 7 | €12.0M | €19.9M | +40% |
| #18 | Noahkai Banks FC Augsburg | 19 | 7 | €6.0M | €10.0M | +40% |
| #19 | Finn Jeltsch VfB Stuttgart | 19 | 7 | €20.0M | €33.2M | +40% |
| #20 | Tidiam Gomis RB Leipzig | 19 | 7 | €3.0M | €5.0M | +40% |
Risk-Adjusted Upside (RAU)
Upside potential weighted against forecast uncertainty. Higher RAU = better risk-reward profile.
Understanding Risk-Adjusted Upside (RAU)
Borussia Mönchengladbach's Tiago Pereira Cardoso has the highest Risk-Adjusted Upside at 154.3. That means Tiago Pereira Cardoso has 40% upside potential with only 0% forecast uncertainty—representing excellent risk-reward for value appreciation.
In second is SV Werder Bremen's Mio Backhaus with a 103.3 RAU (23% upside, 0% uncertainty). Third is Tom Ritzy Hülsmann of TSV Hartberg with a 103.3 RAU (23% upside, 0% uncertainty).
How RAU is calculated: RAU divides upside potential by forecast uncertainty (RAU = Upside % ÷ Uncertainty %). A RAU of 154.3 means the upside is 154.3× 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 | Tiago Pereira Cardoso Borussia Mönchengladbach | €2.1M | €1.9M-2.3M | +40% | 154.3 |
| #2 | Mio Backhaus SV Werder Bremen | €2.5M | €2.2M-2.7M | +23% | 103.3 |
| #3 | Tom Ritzy Hülsmann TSV Hartberg | €617K | €561K-674K | +23% | 103.3 |
| #4 | Matteo Bignetti SK Sturm Graz | €494K | €448K-539K | +23% | 103.3 |
| #5 | Lúkas Petersson TSG 1899 Hoffenheim | €298K | €274K-321K | +19% | 100.1 |
| #6 | Frank Feller 1.FC Heidenheim 1846 | €595K | €548K-643K | +19% | 100.1 |
| #7 | Silas Ostrzinski Borussia Dortmund | €238K | €219K-257K | +19% | 100.1 |
| #8 | Daniil Khudyakov SK Sturm Graz | €953K | €876K-1.0M | +19% | 100.1 |
| #9 | Kauã Santos Eintracht Frankfurt | €3.0M | €2.7M-3.2M | +19% | 100.1 |
| #10 | Jonas Urbig Bayern Munich | €14.3M | €13.1M-15.4M | +19% | 100.1 |
| #11 | Noah Atubolu SC Freiburg | €20.6M | €19.0M-22.3M | +15% | 79.9 |
| #12 | Karl Hein SV Werder Bremen | €3.4M | €3.2M-3.7M | +15% | 79.9 |
| #13 | Niklas Swider Borussia Mönchengladbach | €309K | €266K-351K | +23% | 68.9 |
| #14 | Mathys Angély VfL Wolfsburg | €741K | €639K-843K | +23% | 68.9 |
| #15 | Marwin Schmitz FC St. Pauli | €247K | €213K-281K | +23% | 68.9 |
| #16 | Aleksandar Pavlovic Bayern Munich | €65.6M | €56.6M-74.7M | +19% | 58.7 |
| #17 | Diant Ramaj 1.FC Heidenheim 1846 | €7.7M | €7.1M-8.3M | +10% | 58.1 |
| #18 | Maarten Vandevoordt RB Leipzig | €8.8M | €8.1M-9.5M | +10% | 58.1 |
| #19 | Daniel Klein FC Augsburg | €165K | €152K-179K | +10% | 58.1 |
| #20 | Lasse Rieß 1.FSV Mainz 05 | €441K | €406K-476K | +10% | 58.1 |
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: player 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)
Hatta Club's Lucas Galvão in the 30+ age bracket has the highest Age-Share Concentration at +-13.0%. That means Harry Kane captures 13.0% of total market value while representing only 26.0% of players in their age group—showing dominant elite status.
In second is 1.FC Köln's Florian Kainz with a +-13.0% ASC (13.0% value share vs 26.0% player share in 30+ bracket). Third is Jeffrey Gouweleeuw of FC Augsburg with a +-13.0% ASC (13.0% value vs 26.0% players in 30+ bracket).
How ASC is calculated: ASC = (% of total value) - (% of total players) in age bracket. A +-13.0% ASC means the player captures -13.0% 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 | Lucas Galvão Hatta Club | 30+ | 13.0% | 26.0% | -13.0% |
| #2 | Florian Kainz 1.FC Köln | 30+ | 13.0% | 26.0% | -13.0% |
| #3 | Jeffrey Gouweleeuw FC Augsburg | 30+ | 13.0% | 26.0% | -13.0% |
| #4 | Kevin Stöger Borussia Mönchengladbach | 30+ | 13.0% | 26.0% | -13.0% |
| #5 | Marcel Sabitzer Borussia Dortmund | 30+ | 13.0% | 26.0% | -13.0% |
| #6 | Leart Paçarada 1.FC Heidenheim 1846 | 30+ | 13.0% | 26.0% | -13.0% |
| #7 | Jonas Meffert Hamburger SV | 30+ | 13.0% | 26.0% | -13.0% |
| #8 | Frederik Rönnow 1.FC Union Berlin | 30+ | 13.0% | 26.0% | -13.0% |
| #9 | Dominique Heintz 1.FC Köln | 30+ | 13.0% | 26.0% | -13.0% |
| #10 | Anthony Losilla VfL Bochum | 30+ | 13.0% | 26.0% | -13.0% |
| #11 | Dejan Stojanovic SCR Altach | 30+ | 13.0% | 26.0% | -13.0% |
| #12 | Marius Bülter 1.FC Köln | 30+ | 13.0% | 26.0% | -13.0% |
| #13 | Marnon Busch 1.FC Heidenheim 1846 | 30+ | 13.0% | 26.0% | -13.0% |
| #14 | Maximilian Arnold VfL Wolfsburg | 30+ | 13.0% | 26.0% | -13.0% |
| #15 | Marius Müller VfL Wolfsburg | 30+ | 13.0% | 26.0% | -13.0% |
| #16 | Alessandro Schöpf Wolfsberger AC | 30+ | 13.0% | 26.0% | -13.0% |
| #17 | Dominik Kohr 1.FSV Mainz 05 | 30+ | 13.0% | 26.0% | -13.0% |
| #18 | Ivan Ordets Without Club | 30+ | 13.0% | 26.0% | -13.0% |
| #19 | Mitchell Weiser SV Werder Bremen | 30+ | 13.0% | 26.0% | -13.0% |
| #20 | Karim Onisiwo Red Bull Salzburg | 30+ | 13.0% | 26.0% | -13.0% |
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: 27 immediate targets, 136 standard acquisitions, 0 watch-list prospects, 191 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 €800K. 2 undervalued, 12 premium.
Value Positioning vs Peers
| Player | Market Value | Position Median | Z-Score | Assessment |
|---|---|---|---|---|
Benjamin Henrichs RB Leipzig | €15.0M | €4.0M | -1.67 | Undervalued |
Chris Führich VfB Stuttgart | €15.0M | €4.0M | -1.67 | Undervalued |
Amadou Haidara RB Leipzig | €16.0M | €4.0M | -1.33 | Good Value |
Johan Bakayoko RB Leipzig | €30.0M | €4.0M | -1.25 | Good Value |
Tim Kleindienst Borussia Mönchengladbach | €17.0M | €4.0M | -1.00 | Good Value |
Dayot Upamecano Bayern Munich | €50.0M | €4.0M | -1.00 | Good Value |
Diogo Leite 1.FC Union Berlin | €17.0M | €4.0M | -1.00 | Good Value |
Lovro Majer VfL Wolfsburg | €17.0M | €4.0M | -1.00 | Good Value |
Martin Terrier Bayer 04 Leverkusen | €17.0M | €4.0M | -1.00 | Good Value |
Rocco Reitz Borussia Mönchengladbach | €15.0M | €4.0M | -1.00 | Good Value |
Malik Tillman Bayer 04 Leverkusen | €32.0M | €4.0M | -1.00 | Good Value |
Mert Kömür FC Augsburg | €5.0M | €4.0M | -1.00 | Good Value |
Aleksandar Pavlovic Bayern Munich | €55.0M | €4.0M | -1.00 | Good Value |
Adam Daghim VfL Wolfsburg | €5.0M | €4.0M | -1.00 | Good Value |
Jeanuël Belocian Bayer 04 Leverkusen | €15.0M | €4.0M | -1.00 | Good Value |
Clement Bischoff Red Bull Salzburg | €5.0M | €4.0M | -1.00 | Good Value |
Jakub Kaminski 1.FC Köln | €5.0M | €4.0M | -0.83 | Good Value |
Igor Matanovic SC Freiburg | €5.0M | €4.0M | -0.83 | Good Value |
Anton Kade FC Augsburg | €5.0M | €4.0M | -0.83 | Good Value |
Tim Oermann SK Sturm Graz | €5.0M | €4.0M | -0.83 | Good Value |