Best Centre-Backs in the Bundesliga (Jun 2026)
Ranked by Analytical Strength Score
Market Overview: Bundesliga Centre-Backs 2024-25
Our database tracked 100 Bundesliga Centre-Backs in the 2024-25 season, representing 27 clubs with a combined market value of €905.4M. The average market value for Bundesliga Centre-Backs was €9.1M, with the average age at 26.4 years old.
The most valuable centre-back in the Bundesliga was Dayot Upamecano, worth €70.0M and played for Bayern Munich at 27 years old. The top 5 Centre-Backs averaged €50.0M in market value, including Nico Schlotterbeck and Castello Lukeba.
Age distribution showed the youngest tracked centre-back was Luka Vuskovic (19 years, Hamburger SV, €40.0M), while the oldest was Aleksandar Dragovic (35 years, Austria Vienna, €800K). Research shows Centre-Backs typically peak at age 27.
Historical analysis showed 42 Centre-Backs (42%) 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 Centre-Backs remained highly competitive with significant transfer activity 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 Centre-Backs. Identify undervalued assets and track market momentum across 27 clubs with €905.4M combined value.
Age Distribution: Bundesliga Centre-Backs
The Bundesliga CB market shows 5 distinct age segments, with the largest cohort in the 27-29 bracket (31 players, 31% of market). The 27-29 age group holds the most value at €328.3M, averaging €10.6M per player.
Top Centre-Backs by Age Bracket
U21 Years (10 players)
21-23 Years (19 players)
24-26 Years (18 players)
27-29 Years (31 players)
Market Value Distribution
Elite Tier Concentration
The top 10 Centre-Backs (10% of players) control €393.0M
Market Tiers
Market structure shows distributed value with elite (€50m+) tier representing 2% of the Bundesliga CB pool.
Elite (€50M+)
Premium (€30-50M)
High (€15-30M)
Club Distribution: Bundesliga Centre-Backs
Among 27 Bundesliga clubs, Bayern Munich leads with 4 Centre-Backs worth €143.0M (averaging €35.8M per player). The top 10 clubs account for 49% of tracked Centre-Backs.
Bayern Munich (4 Centre-Backs)
Bayer 04 Leverkusen (4 Centre-Backs)
Borussia Dortmund (6 Centre-Backs)
RB Leipzig (5 Centre-Backs)
Player Rankings
Ranked by APE Strength Score. Click any player to view full profile, or click the chart icon to see value history.
Dayot Upamecano
Bayern Munich • 27 years old
€74.0M
€70.0M
-5.4%
Expected: €63.8M
92.1
Nico Schlotterbeck
Borussia Dortmund • 26 years old
€47.6M
€55.0M
+15.6%
Expected: €58.9M
88.8
Castello Lukeba
RB Leipzig • 23 years old
€38.9M
€45.0M
+15.6%
Expected: €50.1M
87.7
Jarell Quansah
Bayer 04 Leverkusen • 23 years old
€34.6M
€40.0M
+15.6%
Expected: €44.6M
86.2
Luka Vuskovic
Hamburger SV • 19 years old
€34.6M
€40.0M
+15.6%
Expected: €49.6M
83.8
Edmond Tapsoba
Bayer 04 Leverkusen • 27 years old
€37.0M
€35.0M
-5.4%
Expected: €31.9M
83.3
Jonathan Tah
Bayern Munich • 30 years old
€38.7M
€30.0M
-22.6%
Expected: €24.9M
78.3
Loïc Badé
Bayer 04 Leverkusen • 26 years old
€24.2M
€28.0M
+15.6%
Expected: €28.8M
76.8
Konstantinos Koulierakis
VfL Wolfsburg • 22 years old
€21.6M
€25.0M
+15.6%
Expected: €26.5M
76.2
Min-jae Kim
Bayern Munich • 29 years old
€32.3M
€25.0M
-22.6%
Expected: €20.7M
75.9
Arthur Theate
Eintracht Frankfurt • 26 years old
€20.8M
€24.0M
+15.6%
Expected: €24.7M
74.9
Chrislain Matsima
FC Augsburg • 24 years old
€19.0M
€22.0M
+15.6%
Expected: €22.5M
74.7
Finn Jeltsch
VfB Stuttgart • 19 years old
€21.6M
€25.0M
+15.6%
Expected: €29.8M
74.4
Leopold Querfeld
1.FC Union Berlin • 22 years old
€15.6M
€18.0M
+15.6%
Expected: €19.1M
72.1
Waldemar Anton
Borussia Dortmund • 29 years old
€23.2M
€18.0M
-22.6%
Expected: €14.9M
71.6
Hiroki Ito
Bayern Munich • 27 years old
€19.0M
€18.0M
-5.4%
Expected: €15.8M
71.6
Nnamdi Collins
Eintracht Frankfurt • 22 years old
€13.0M
€15.0M
+15.6%
Expected: €15.9M
69.8
Robin Koch
Eintracht Frankfurt • 29 years old
€19.4M
€15.0M
-22.6%
Expected: €12.4M
69.4
Jeff Chabot
VfB Stuttgart • 28 years old
€19.4M
€15.0M
-22.6%
Expected: €13.1M
69.2
El Chadaille Bitshiabu
RB Leipzig • 21 years old
€13.0M
€15.0M
+15.6%
Expected: €16.5M
69.2
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)
Hamburger SV's Luka Vuskovic at 19 years old has the highest Pre-Peak Value Efficiency at 13.33×. That means Luka Vuskovic is valued 13.33× higher than the median player in the U21 age bracket—representing exceptional value before reaching peak age.
In second is VfB Stuttgart's Finn Jeltsch, who is 19 years old, with a 8.33× PPVE. Third is Castello Lukeba of RB Leipzig, who is 23 years old with a 5.63× 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 13.33× means the player is worth 1233% 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 | Luka Vuskovic Hamburger SV | 19 | U21 | €40.0M | €3.0M | 13.33× |
| #2 | Finn Jeltsch VfB Stuttgart | 19 | U21 | €25.0M | €3.0M | 8.33× |
| #3 | Castello Lukeba RB Leipzig | 23 | 21-23 | €45.0M | €8.0M | 5.63× |
| #4 | Chrislain Matsima FC Augsburg | 24 | 24-26 | €22.0M | €4.0M | 5.50× |
| #5 | Jarell Quansah Bayer 04 Leverkusen | 23 | 21-23 | €40.0M | €8.0M | 5.00× |
| #6 | Noahkai Banks FC Augsburg | 19 | U21 | €15.0M | €3.0M | 5.00× |
| #7 | Joane Gadou Red Bull Salzburg | 19 | U21 | €12.0M | €3.0M | 4.00× |
| #8 | Konstantinos Koulierakis VfL Wolfsburg | 22 | 21-23 | €25.0M | €8.0M | 3.13× |
| #9 | Leopold Querfeld 1.FC Union Berlin | 22 | 21-23 | €18.0M | €8.0M | 2.25× |
| #10 | Nnamdi Collins Eintracht Frankfurt | 22 | 21-23 | €15.0M | €8.0M | 1.88× |
| #11 | El Chadaille Bitshiabu RB Leipzig | 21 | 21-23 | €15.0M | €8.0M | 1.88× |
| #12 | Jeanuël Belocian VfL Wolfsburg | 21 | 21-23 | €12.0M | €8.0M | 1.50× |
| #13 | Ramon Hendriks VfB Stuttgart | 24 | 24-26 | €5.0M | €4.0M | 1.25× |
| #14 | Luca Jaquez VfB Stuttgart | 23 | 21-23 | €10.0M | €8.0M | 1.25× |
| #15 | Arthur Chaves FC Augsburg | 25 | 24-26 | €5.0M | €4.0M | 1.25× |
| #16 | David Nemeth FC St. Pauli | 25 | 24-26 | €4.0M | €4.0M | 1.00× |
| #17 | Max Rosenfelder SC Freiburg | 23 | 21-23 | €8.0M | €8.0M | 1.00× |
| #18 | Ameen Al-Dakhil VfB Stuttgart | 24 | 24-26 | €4.0M | €4.0M | 1.00× |
| #19 | Rav van den Berg 1.FC Köln | 21 | 21-23 | €8.0M | €8.0M | 1.00× |
| #20 | Fabio Chiarodia Borussia Mönchengladbach | 20 | U21 | €3.0M | €3.0M | 1.00× |
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)
RB Leipzig's Jonathan Norbye at 19 years old has the highest Return-to-Peak Potential at +40%. That means Finn Jeltsch is projected to appreciate 40% as they reach their peak age in 7 years—representing significant upside before entering their prime.
In second is VfL Wolfsburg's Mathys Angély, who is 19 years old, with a +40% RPP (7 years to peak). Third is Noahkai Banks of FC Augsburg, who is 19 years old with a +40% RPP (7 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 | Jonathan Norbye RB Leipzig | 19 | 7 | €300K | €499K | +40% |
| #2 | Mathys Angély VfL Wolfsburg | 19 | 7 | €600K | €997K | +40% |
| #3 | Noahkai Banks FC Augsburg | 19 | 7 | €15.0M | €24.9M | +40% |
| #4 | Finn Jeltsch VfB Stuttgart | 19 | 7 | €25.0M | €41.5M | +40% |
| #5 | Joane Gadou Red Bull Salzburg | 19 | 7 | €12.0M | €19.9M | +40% |
| #6 | Luka Vuskovic Hamburger SV | 19 | 7 | €40.0M | €66.5M | +40% |
| #7 | Fabio Chiarodia Borussia Mönchengladbach | 20 | 6 | €3.0M | €4.6M | +35% |
| #8 | Bruno Ogbus SC Freiburg | 20 | 6 | €1.0M | €1.5M | +35% |
| #9 | Ludwig Vraa Grazer AK 1902 | 20 | 6 | €300K | €464K | +35% |
| #10 | Maxim Dal 1.FSV Mainz 05 | 20 | 6 | €150K | €232K | +35% |
| #11 | Rav van den Berg 1.FC Köln | 21 | 5 | €8.0M | €11.5M | +30% |
| #12 | El Chadaille Bitshiabu RB Leipzig | 21 | 5 | €15.0M | €21.6M | +30% |
| #13 | Filippo Mane Borussia Dortmund | 21 | 5 | €2.5M | €3.6M | +30% |
| #14 | Jeanuël Belocian VfL Wolfsburg | 21 | 5 | €12.0M | €17.2M | +30% |
| #15 | Nnamdi Collins Eintracht Frankfurt | 22 | 4 | €15.0M | €20.1M | +25% |
| #16 | Tim Oermann Bayer 04 Leverkusen | 22 | 4 | €4.0M | €5.3M | +25% |
| #17 | Anrie Chase Red Bull Salzburg | 22 | 4 | €2.0M | €2.7M | +25% |
| #18 | Leopold Querfeld 1.FC Union Berlin | 22 | 4 | €18.0M | €24.1M | +25% |
| #19 | Konstantinos Koulierakis VfL Wolfsburg | 22 | 4 | €25.0M | €33.4M | +25% |
| #20 | Elias Bakatukanda FC Blau-Weiss Linz | 22 | 4 | €400K | €535K | +25% |
Risk-Adjusted Upside (RAU)
Upside potential weighted against forecast uncertainty. Higher RAU = better risk-reward profile.
Understanding Risk-Adjusted Upside (RAU)
Hamburger SV's Luka Vuskovic has the highest Risk-Adjusted Upside at 70.0. That means Luka Vuskovic has 24% upside potential with only 0% forecast uncertainty—representing excellent risk-reward for value appreciation.
In second is RB Leipzig's Jonathan Norbye with a 58.0 RAU (19% upside, 0% uncertainty). Third is Mathys Angély of VfL Wolfsburg with a 58.0 RAU (19% upside, 0% uncertainty).
How RAU is calculated: RAU divides upside potential by forecast uncertainty (RAU = Upside % ÷ Uncertainty %). A RAU of 70.0 means the upside is 70.0× 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 | Luka Vuskovic Hamburger SV | €49.6M | €42.7M-56.4M | +24% | 70.0 |
| #2 | Jonathan Norbye RB Leipzig | €357K | €308K-407K | +19% | 58.0 |
| #3 | Mathys Angély VfL Wolfsburg | €714K | €616K-813K | +19% | 58.0 |
| #4 | Joane Gadou Red Bull Salzburg | €14.3M | €12.3M-16.3M | +19% | 58.0 |
| #5 | Finn Jeltsch VfB Stuttgart | €29.8M | €25.7M-33.9M | +19% | 58.0 |
| #6 | Noahkai Banks FC Augsburg | €17.9M | €15.4M-20.3M | +19% | 58.0 |
| #7 | Bruno Ogbus SC Freiburg | €1.1M | €988K-1.3M | +15% | 46.3 |
| #8 | Ludwig Vraa Grazer AK 1902 | €344K | €297K-391K | +15% | 46.3 |
| #9 | Maxim Dal 1.FSV Mainz 05 | €172K | €148K-196K | +15% | 46.3 |
| #10 | Fabio Chiarodia Borussia Mönchengladbach | €3.4M | €3.0M-3.9M | +15% | 46.3 |
| #11 | Jarell Quansah Bayer 04 Leverkusen | €44.6M | €39.2M-49.9M | +11% | 42.8 |
| #12 | Castello Lukeba RB Leipzig | €50.1M | €44.1M-56.2M | +11% | 42.8 |
| #13 | Filippo Mane Borussia Dortmund | €2.8M | €2.4M-3.1M | +10% | 33.7 |
| #14 | Jeanuël Belocian VfL Wolfsburg | €13.2M | €11.4M-15.1M | +10% | 33.7 |
| #15 | El Chadaille Bitshiabu RB Leipzig | €16.5M | €14.3M-18.8M | +10% | 33.7 |
| #16 | Rav van den Berg 1.FC Köln | €8.8M | €7.6M-10.0M | +10% | 33.7 |
| #17 | Nico Schlotterbeck Borussia Dortmund | €58.9M | €51.9M-66.0M | +7% | 27.8 |
| #18 | Max Rosenfelder SC Freiburg | €8.6M | €7.5M-9.6M | +7% | 27.5 |
| #19 | Jamie Lawrence WSG Tirol | €642K | €565K-719K | +7% | 27.5 |
| #20 | Luca Jaquez VfB Stuttgart | €10.7M | €9.4M-12.0M | +7% | 27.5 |
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: centre-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)
FC Augsburg's Jeffrey Gouweleeuw in the 30+ age bracket has the highest Age-Share Concentration at +-12.4%. That means Jonathan Tah captures 9.6% of total market value while representing only 22.0% of players in their age group—showing dominant elite status.
In second is 1.FC Köln's Dominique Heintz with a +-12.4% ASC (9.6% value share vs 22.0% player share in 30+ bracket). Third is Dominik Kohr of 1.FSV Mainz 05 with a +-12.4% ASC (9.6% value vs 22.0% players in 30+ bracket).
How ASC is calculated: ASC = (% of total value) - (% of total players) in age bracket. A +-12.4% ASC means the player captures -12.4% 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 | Jeffrey Gouweleeuw FC Augsburg | 30+ | 9.6% | 22.0% | -12.4% |
| #2 | Dominique Heintz 1.FC Köln | 30+ | 9.6% | 22.0% | -12.4% |
| #3 | Dominik Kohr 1.FSV Mainz 05 | 30+ | 9.6% | 22.0% | -12.4% |
| #4 | Emre Can Borussia Dortmund | 30+ | 9.6% | 22.0% | -12.4% |
| #5 | Matthias Ginter SC Freiburg | 30+ | 9.6% | 22.0% | -12.4% |
| #6 | Lukas Spendlhofer TSV Hartberg | 30+ | 9.6% | 22.0% | -12.4% |
| #7 | Patrick Mainka 1.FC Heidenheim 1846 | 30+ | 9.6% | 22.0% | -12.4% |
| #8 | Karol Mets FC St. Pauli | 30+ | 9.6% | 22.0% | -12.4% |
| #9 | Hauke Wahl FC St. Pauli | 30+ | 9.6% | 22.0% | -12.4% |
| #10 | Kevin Akpoguma TSG 1899 Hoffenheim | 30+ | 9.6% | 22.0% | -12.4% |
| #11 | Niklas Stark SV Werder Bremen | 30+ | 9.6% | 22.0% | -12.4% |
| #12 | Niklas Süle Borussia Dortmund | 30+ | 9.6% | 22.0% | -12.4% |
| #13 | Marvin Friedrich Borussia Mönchengladbach | 30+ | 9.6% | 22.0% | -12.4% |
| #14 | Jonathan Tah Bayern Munich | 30+ | 9.6% | 22.0% | -12.4% |
| #15 | Adam Dzwigala FC St. Pauli | 30+ | 9.6% | 22.0% | -12.4% |
| #16 | Denis Vavro VfL Wolfsburg | 30+ | 9.6% | 22.0% | -12.4% |
| #17 | Ramy Bensebaini Borussia Dortmund | 30+ | 9.6% | 22.0% | -12.4% |
| #18 | Anthony Jung SC Freiburg | 30+ | 9.6% | 22.0% | -12.4% |
| #19 | Aleksandar Dragovic Austria Vienna | 30+ | 9.6% | 22.0% | -12.4% |
| #20 | Stefan Bell 1.FSV Mainz 05 | 30+ | 9.6% | 22.0% | -12.4% |
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: 6 immediate targets, 23 standard acquisitions, 0 watch-list prospects, 35 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 €900K. 0 undervalued, 3 premium.
Value Positioning vs Peers
| Player | Market Value | Position Median | Z-Score | Assessment |
|---|---|---|---|---|
Niklas Süle Borussia Dortmund | €5.0M | €5.0M | -1.00 | Good Value |
Jeff Chabot VfB Stuttgart | €15.0M | €5.0M | -1.00 | Good Value |
Robin Koch Eintracht Frankfurt | €15.0M | €5.0M | -1.00 | Good Value |
Jarell Quansah Bayer 04 Leverkusen | €40.0M | €5.0M | -1.00 | Good Value |
Noahkai Banks FC Augsburg | €15.0M | €5.0M | -1.00 | Good Value |
Jean Marcelin Rapid Vienna | €800K | €5.0M | -0.80 | Good Value |
Jenson Seelt VfL Wolfsburg | €5.0M | €5.0M | -0.75 | Good Value |
Xavier Mbuyamba LASK | €1.0M | €5.0M | -0.67 | Good Value |
Maxim Dal 1.FSV Mainz 05 | €150K | €5.0M | -0.64 | Good Value |
Lukas Spendlhofer TSV Hartberg | €200K | €5.0M | -0.62 | Good Value |
Elias Bakatukanda FC Blau-Weiss Linz | €400K | €5.0M | -0.58 | Good Value |
Maxim Leitsch 1.FSV Mainz 05 | €1.5M | €5.0M | -0.50 | Fair Value |
Aurèle Amenda Eintracht Frankfurt | €6.0M | €5.0M | -0.50 | Fair Value |
Jamie Lawrence WSG Tirol | €600K | €5.0M | -0.47 | Fair Value |
Jonathan Norbye RB Leipzig | €300K | €5.0M | -0.43 | Fair Value |
Ludwig Vraa Grazer AK 1902 | €300K | €5.0M | -0.43 | Fair Value |
Cleiton VfL Wolfsburg | €800K | €5.0M | -0.37 | Fair Value |
Stanley Nsoki 1.FC Union Berlin | €1.8M | €5.0M | -0.35 | Fair Value |
Emanuel Aiwu SK Sturm Graz | €1.5M | €5.0M | -0.33 | Fair Value |
Chrislain Matsima FC Augsburg | €22.0M | €5.0M | -0.33 | Fair Value |