Best Players (All Positions) in the Bundesliga (Dec 2025)
Ranked by Analytical Strength Score
Market Overview: Bundesliga Players (All Positions) 2022-23
Our database tracked 534 Bundesliga Players (All Positions) in the 2022-23 season, representing 34 clubs with a combined market value of €4.3B. The average market value for Bundesliga Players (All Positions) was €8.1M, with the average age at 26.3 years old.
The most valuable player in the Bundesliga was Michael Olise, worth €100.0M and played for Bayern Munich at 24 years old. The top 5 Players (All Positions) averaged €88.0M in market value, including Jamal Musiala and Luis Díaz.
Age distribution showed the youngest tracked player was Joane Gadou (18 years, Red Bull Salzburg, €15.0M), while the oldest was Manuel Neuer (39 years, Bayern Munich, €4.0M). Research shows Players (All Positions) typically peak at age 26-27.
Historical analysis showed 255 Players (All Positions) (48%) 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 Players (All Positions) remained highly competitive with significant transfer activity in the 2022-23 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 (132 players, 25% of market). The 24-26 age group holds the most value at €1.2B, averaging €9.4M per player.
Top Players (All Positions) by Age Bracket
U21 Years (48 players)
21-23 Years (114 players)
24-26 Years (124 players)
27-29 Years (116 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.
Michael Olise
Bayern Munich • 24 years old
€86.5M
€100.0M
+15.6%
Expected: €106.6M
95.5
Jamal Musiala
Bayern Munich • 22 years old
€121.1M
€140.0M
+15.6%
Expected: €154.2M
94.4
Luis Díaz
Bayern Munich • 28 years old
€90.4M
€70.0M
-22.6%
Expected: €63.8M
92.2
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 • 30 years old
€58.1M
€45.0M
-22.6%
Expected: €39.0M
88.1
Dayot Upamecano
Bayern Munich • 27 years old
€52.8M
€50.0M
-5.4%
Expected: €45.5M
87.9
Karim Adeyemi
Borussia Dortmund • 23 years old
€38.9M
€45.0M
+15.6%
Expected: €50.1M
87.7
Gregor Kobel
Borussia Dortmund • 28 years old
€34.6M
€40.0M
+15.6%
Expected: €40.7M
87.5
Serhou Guirassy
Borussia Dortmund • 29 years old
€58.1M
€45.0M
-22.6%
Expected: €38.8M
86.6
Victor Boniface
SV Werder Bremen • 24 years old
€34.6M
€40.0M
+15.6%
Expected: €42.6M
85.8
Castello Lukeba
RB Leipzig • 22 years old
€34.6M
€40.0M
+15.6%
Expected: €44.1M
85.6
Min-jae Kim
Bayern Munich • 29 years old
€51.7M
€40.0M
-22.6%
Expected: €34.5M
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 22 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 22.22× PPVE. Third is Alphonso Davies of Bayern Munich, who is 25 years old with a 11.11× 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 | 22 | 21-23 | €140.0M | €5.0M | 28.00× |
| #2 | Michael Olise Bayern Munich | 24 | 24-26 | €100.0M | €4.5M | 22.22× |
| #3 | Alphonso Davies Bayern Munich | 25 | 24-26 | €50.0M | €4.5M | 11.11× |
| #4 | Nicolas Jackson Bayern Munich | 24 | 24-26 | €50.0M | €4.5M | 11.11× |
| #5 | Aleksandar Pavlovic Bayern Munich | 21 | 21-23 | €55.0M | €5.0M | 11.00× |
| #6 | Angelo Stiller VfB Stuttgart | 24 | 24-26 | €45.0M | €4.5M | 10.00× |
| #7 | Karim Adeyemi Borussia Dortmund | 23 | 21-23 | €45.0M | €5.0M | 9.00× |
| #8 | Victor Boniface SV Werder Bremen | 24 | 24-26 | €40.0M | €4.5M | 8.89× |
| #9 | Castello Lukeba RB Leipzig | 22 | 21-23 | €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 | €4.5M | 7.78× |
| #12 | Josip Stanisic Bayern Munich | 25 | 24-26 | €32.0M | €4.5M | 7.11× |
| #13 | Mohamed Amoura VfL Wolfsburg | 25 | 24-26 | €32.0M | €4.5M | 7.11× |
| #14 | Malik Tillman Bayer 04 Leverkusen | 23 | 21-23 | €32.0M | €5.0M | 6.40× |
| #15 | Felix Nmecha Borussia Dortmund | 25 | 24-26 | €28.0M | €4.5M | 6.22× |
| #16 | Johan Bakayoko RB Leipzig | 22 | 21-23 | €30.0M | €5.0M | 6.00× |
| #17 | Bilal El Khannouss VfB Stuttgart | 21 | 21-23 | €28.0M | €5.0M | 5.60× |
| #18 | Loïc Badé Bayer 04 Leverkusen | 25 | 24-26 | €25.0M | €4.5M | 5.56× |
| #19 | Arthur Theate Eintracht Frankfurt | 25 | 24-26 | €24.0M | €4.5M | 5.33× |
| #20 | Maximilian Beier Borussia Dortmund | 23 | 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 18 years old, with a +48% RPP (8 years to peak). Third is Niklas Swider of Borussia Mönchengladbach, 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 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 | 18 | 8 | €200K | €384K | +48% |
| #3 | Niklas Swider Borussia Mönchengladbach | 18 | 8 | €250K | €480K | +48% |
| #4 | Joane Gadou Red Bull Salzburg | 18 | 8 | €15.0M | €26.8M | +44% |
| #5 | Luka Vuskovic Hamburger SV | 18 | 8 | €12.0M | €21.4M | +44% |
| #6 | Matteo Bignetti SK Sturm Graz | 21 | 5 | €400K | €715K | +44% |
| #7 | Daniil Khudyakov SK Sturm Graz | 21 | 5 | €800K | €1.4M | +44% |
| #8 | Mathys Angély VfL Wolfsburg | 18 | 8 | €600K | €1.1M | +44% |
| #9 | Patrice Covic SV Werder Bremen | 18 | 8 | €2.5M | €4.5M | +44% |
| #10 | Mio Backhaus SV Werder Bremen | 21 | 5 | €2.0M | €3.6M | +44% |
| #11 | Tom Ritzy Hülsmann TSV Hartberg | 21 | 5 | €500K | €894K | +44% |
| #12 | Lúkas Petersson TSG 1899 Hoffenheim | 21 | 5 | €250K | €447K | +44% |
| #13 | Frank Feller 1.FC Heidenheim 1846 | 21 | 5 | €500K | €894K | +44% |
| #14 | Alejo Sarco Bayer 04 Leverkusen | 19 | 7 | €800K | €1.3M | +40% |
| #15 | Bazoumana Touré TSG 1899 Hoffenheim | 19 | 7 | €9.0M | €15.0M | +40% |
| #16 | Julien Duranville Borussia Dortmund | 19 | 7 | €8.5M | €14.1M | +40% |
| #17 | Bruno Ogbus SC Freiburg | 19 | 7 | €1.0M | €1.7M | +40% |
| #18 | Almugera Kabar Borussia Dortmund | 19 | 7 | €1.0M | €1.7M | +40% |
| #19 | Assan Ouédraogo RB Leipzig | 19 | 7 | €7.0M | €11.6M | +40% |
| #20 | Max Moerstedt TSG 1899 Hoffenheim | 19 | 7 | €7.0M | €11.6M | +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 | Lúkas Petersson TSG 1899 Hoffenheim | €309K | €280K-337K | +23% | 103.3 |
| #5 | Frank Feller 1.FC Heidenheim 1846 | €617K | €561K-674K | +23% | 103.3 |
| #6 | Matteo Bignetti SK Sturm Graz | €494K | €448K-539K | +23% | 103.3 |
| #7 | Daniil Khudyakov SK Sturm Graz | €988K | €897K-1.1M | +23% | 103.3 |
| #8 | Silas Ostrzinski Borussia Dortmund | €238K | €219K-257K | +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 | Maarten Vandevoordt RB Leipzig | €9.2M | €8.4M-9.9M | +15% | 79.9 |
| #12 | Noah Atubolu SC Freiburg | €20.6M | €19.0M-22.3M | +15% | 79.9 |
| #13 | Karl Hein SV Werder Bremen | €3.4M | €3.2M-3.7M | +15% | 79.9 |
| #14 | Marwin Schmitz FC St. Pauli | €256K | €220K-291K | +28% | 79.0 |
| #15 | Niklas Swider Borussia Mönchengladbach | €320K | €276K-364K | +28% | 79.0 |
| #16 | Luka Vuskovic Hamburger SV | €14.8M | €12.8M-16.9M | +23% | 68.9 |
| #17 | Mathys Angély VfL Wolfsburg | €741K | €639K-843K | +23% | 68.9 |
| #18 | Joane Gadou Red Bull Salzburg | €18.5M | €16.0M-21.1M | +23% | 68.9 |
| #19 | Aleksandar Pavlovic Bayern Munich | €65.6M | €56.6M-74.7M | +19% | 58.7 |
| #20 | Diant Ramaj 1.FC Heidenheim 1846 | €7.7M | €7.1M-8.3M | +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 +-13.3%. That means Harry Kane captures 11.4% of total market value while representing only 24.7% of players in their age group—showing dominant elite status.
In second is 1.FC Köln's Florian Kainz with a +-13.3% ASC (11.4% value share vs 24.7% player share in 30+ bracket). Third is Jeffrey Gouweleeuw of FC Augsburg with a +-13.3% ASC (11.4% value vs 24.7% players in 30+ bracket).
How ASC is calculated: ASC = (% of total value) - (% of total players) in age bracket. A +-13.3% ASC means the player captures -13.3% 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 | Lucas Galvão Hatta Club | 30+ | 11.4% | 24.7% | -13.3% |
| #2 | Florian Kainz 1.FC Köln | 30+ | 11.4% | 24.7% | -13.3% |
| #3 | Jeffrey Gouweleeuw FC Augsburg | 30+ | 11.4% | 24.7% | -13.3% |
| #4 | Kevin Stöger Borussia Mönchengladbach | 30+ | 11.4% | 24.7% | -13.3% |
| #5 | Marcel Sabitzer Borussia Dortmund | 30+ | 11.4% | 24.7% | -13.3% |
| #6 | Leart Paçarada 1.FC Heidenheim 1846 | 30+ | 11.4% | 24.7% | -13.3% |
| #7 | Jonas Meffert Hamburger SV | 30+ | 11.4% | 24.7% | -13.3% |
| #8 | Frederik Rönnow 1.FC Union Berlin | 30+ | 11.4% | 24.7% | -13.3% |
| #9 | Dominique Heintz 1.FC Köln | 30+ | 11.4% | 24.7% | -13.3% |
| #10 | Anthony Losilla VfL Bochum | 30+ | 11.4% | 24.7% | -13.3% |
| #11 | Dejan Stojanovic SCR Altach | 30+ | 11.4% | 24.7% | -13.3% |
| #12 | Marius Bülter 1.FC Köln | 30+ | 11.4% | 24.7% | -13.3% |
| #13 | Marnon Busch 1.FC Heidenheim 1846 | 30+ | 11.4% | 24.7% | -13.3% |
| #14 | Maximilian Arnold VfL Wolfsburg | 30+ | 11.4% | 24.7% | -13.3% |
| #15 | Marius Müller VfL Wolfsburg | 30+ | 11.4% | 24.7% | -13.3% |
| #16 | Alessandro Schöpf Wolfsberger AC | 30+ | 11.4% | 24.7% | -13.3% |
| #17 | Dominik Kohr 1.FSV Mainz 05 | 30+ | 11.4% | 24.7% | -13.3% |
| #18 | Ivan Ordets Without Club | 30+ | 11.4% | 24.7% | -13.3% |
| #19 | Mitchell Weiser SV Werder Bremen | 30+ | 11.4% | 24.7% | -13.3% |
| #20 | Karim Onisiwo Red Bull Salzburg | 30+ | 11.4% | 24.7% | -13.3% |
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: 35 immediate targets, 142 standard acquisitions, 0 watch-list prospects, 188 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. 0 undervalued, 9 premium.
Value Positioning vs Peers
| Player | Market Value | Position Median | Z-Score | Assessment |
|---|---|---|---|---|
Johan Bakayoko RB Leipzig | €30.0M | €4.0M | -1.25 | Good Value |
Tim Kleindienst Borussia Mönchengladbach | €17.0M | €4.0M | -1.00 | Good Value |
Alejandro Grimaldo Bayer 04 Leverkusen | €30.0M | €4.0M | -1.00 | Good Value |
Benjamin Henrichs RB Leipzig | €15.0M | €4.0M | -1.00 | Good Value |
Chris Führich VfB Stuttgart | €15.0M | €4.0M | -1.00 | Good Value |
Dayot Upamecano Bayern Munich | €50.0M | €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 |
Clement Bischoff Red Bull Salzburg | €5.0M | €4.0M | -1.00 | Good Value |
Ansgar Knauff Eintracht Frankfurt | €15.0M | €4.0M | -0.83 | Good Value |
Rocco Reitz Borussia Mönchengladbach | €15.0M | €4.0M | -0.83 | Good Value |
Amadou Haidara RB Leipzig | €16.0M | €4.0M | -0.80 | Good Value |
Anderson Niangbo Without Club | €150K | €4.0M | -0.74 | Good Value |
Daniel Klein FC Augsburg | €150K | €4.0M | -0.74 | Good Value |
Fabian Ehmann Grazer AK 1902 | €175K | €4.0M | -0.73 | Good Value |
Nikolai Baden Frederiksen WSG Tirol | €300K | €4.0M | -0.68 | Good Value |
Stefan Drljaca VfB Stuttgart | €325K | €4.0M | -0.67 | Good Value |
Maximilian Arnold VfL Wolfsburg | €5.0M | €4.0M | -0.67 | Good Value |