Best Centre-Backs in the Ligue 1 (Jul 2026)
Ranked by Analytical Strength Index
Market Overview: Ligue 1 Centre-Backs 2025-26
Our database tracks 235 Ligue 1 Centre-Backs in the 2025-26 season, representing 36 clubs with a combined market value of €737.2M. The average market value for Ligue 1 Centre-Backs is €3.1M, with the average age at 30 years old.
The most valuable centre-back in the Ligue 1 is Willian Pacho, worth €70.0M and playing for Paris Saint-Germain at 24 years old. The top 5 Centre-Backs average €38.4M in market value, including Ilya Zabarnyi and Marquinhos.
Age distribution shows the youngest tracked centre-back is Kyllian Antonio (18 years, RC Lens, €250K), while the oldest is Laurent Koscielny (40 years, FC Girondins Bordeaux, €3.0M). Research shows Centre-Backs typically peak at age 27.
Our 1-year forecast model projects 83 Centre-Backs (35%) will increase in market value over the next 12 months based on age-curve trajectories, current performance trends, and playing time analysis. The Ligue 1 market for Centre-Backs remains highly competitive with significant transfer activity expected in the 2025-26 season.
Explore Market Size by Position in Ligue 1
Interactive bubble chart showing predicted 2-year growth vs current age for all Ligue 1 Centre-Backs. Identify undervalued assets and track market momentum across 36 clubs with €737.2M 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: Ligue 1 Centre-Backs
The Ligue 1 CB market shows 5 distinct age segments, with the largest cohort in the 30+ bracket (124 players, 53% of market). The 21-23 age group holds the most value at €196.1M, averaging €5.4M per player.
Top Centre-Backs by Age Bracket
U21 Years (9 players)
21-23 Years (36 players)
24-26 Years (33 players)
27-29 Years (33 players)
Market Value Distribution
Elite Tier Concentration
The top 24 Centre-Backs (10% of players) control €454.0M
Market Tiers
Market structure shows distributed value with elite (€50m+) tier representing 1% of the Ligue 1 CB pool.
Elite (€50M+)
Premium (€30-50M)
High (€15-30M)
Club Distribution: Ligue 1 Centre-Backs
Among 36 Ligue 1 clubs, Paris Saint-Germain leads with 9 Centre-Backs worth €176.6M (averaging €19.6M per player). The top 10 clubs account for 38% of tracked Centre-Backs.
Paris Saint-Germain (9 Centre-Backs)
Olympique Marseille (11 Centre-Backs)
Stade Rennais FC (11 Centre-Backs)
AS Monaco (8 Centre-Backs)
Player Rankings
Ranked by Analytical Strength Index. Click any player to view full profile, or click the chart icon to see value history.
Willian Pacho
Paris Saint-Germain • 24 years old
€60.5M
€70.0M
+15.6%
Expected: €78.0M
94.5
Ilya Zabarnyi
Paris Saint-Germain • 23 years old
€43.2M
€50.0M
+15.6%
Expected: €55.1M
89.9
Marquinhos
Paris Saint-Germain • 32 years old
€38.7M
€30.0M
-22.6%
Expected: €25.1M
80.0
Nayef Aguerd
Olympique Marseille • 30 years old
€28.4M
€22.0M
-22.6%
Expected: €18.4M
75.4
Lucas Beraldo
Paris Saint-Germain • 22 years old
€17.3M
€20.0M
+15.6%
Expected: €22.1M
74.2
Benjamin Pavard
Olympique Marseille • 30 years old
€25.8M
€20.0M
-22.6%
Expected: €16.8M
74.2
Jérémy Jacquet
Stade Rennais FC • 21 years old
€17.3M
€20.0M
+15.6%
Expected: €22.9M
73.6
Leonardo Balerdi
Olympique Marseille • 27 years old
€17.3M
€20.0M
+15.6%
Expected: €20.6M
73.5
Facundo Medina
Olympique Marseille • 27 years old
€17.3M
€20.0M
+15.6%
Expected: €20.6M
73.5
Ismaël Doukouré
RC Strasbourg Alsace • 22 years old
€15.6M
€18.0M
+15.6%
Expected: €19.8M
72.7
Thilo Kehrer
AS Monaco • 29 years old
€23.2M
€18.0M
-22.6%
Expected: €15.9M
72.6
Moussa Niakhaté
Olympique Lyon • 30 years old
€20.7M
€16.0M
-22.6%
Expected: €13.4M
71.4
Charlie Cresswell
FC Toulouse • 23 years old
€13.0M
€15.0M
+15.6%
Expected: €15.9M
70.8
Christian Mawissa
AS Monaco • 21 years old
€13.0M
€15.0M
+15.6%
Expected: €17.2M
70.0
Wout Faes
AS Monaco • 28 years old
€12.7M
€12.0M
-5.4%
Expected: €10.6M
67.2
Arouna Sangante
Le Havre AC • 24 years old
€8.6M
€10.0M
+15.6%
Expected: €10.7M
62.5
Otávio
Paris FC • 24 years old
€8.6M
€10.0M
+15.6%
Expected: €10.7M
62.5
Diego Coppola
Paris FC • 22 years old
€8.6M
€10.0M
+15.6%
Expected: €11.0M
61.7
Lilian Brassier
Stade Rennais FC • 26 years old
€8.6M
€10.0M
+15.6%
Expected: €9.8M
61.6
Mohammed Salisu
AS Monaco • 27 years old
€8.6M
€10.0M
+15.6%
Expected: €10.3M
61.1
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)
Paris Saint-Germain's Ilya Zabarnyi at 23 years old has the highest Pre-Peak Value Efficiency at 33.33×. That means Ilya Zabarnyi is valued 33.33× higher than the median player in the 21-23 age bracket-representing exceptional value before reaching peak age.
In second is Stade Rennais FC's Abdelhamid Ait Boudlal, who is 20 years old, with a 28.57× PPVE. Third is Willian Pacho of Paris Saint-Germain, who is 24 years old with a 23.33× 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 33.33× means the player is worth 3233% 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 | Ilya Zabarnyi Paris Saint-Germain | 23 | 21-23 | €50.0M | €1.5M | 33.33× |
| #2 | Abdelhamid Ait Boudlal Stade Rennais FC | 20 | U21 | €10.0M | €350K | 28.57× |
| #3 | Willian Pacho Paris Saint-Germain | 24 | 24-26 | €70.0M | €3.0M | 23.33× |
| #4 | Jérémy Jacquet Stade Rennais FC | 21 | 21-23 | €20.0M | €1.5M | 13.33× |
| #5 | Lucas Beraldo Paris Saint-Germain | 22 | 21-23 | €20.0M | €1.5M | 13.33× |
| #6 | Ismaël Doukouré RC Strasbourg Alsace | 22 | 21-23 | €18.0M | €1.5M | 12.00× |
| #7 | Christian Mawissa AS Monaco | 21 | 21-23 | €15.0M | €1.5M | 10.00× |
| #8 | Charlie Cresswell FC Toulouse | 23 | 21-23 | €15.0M | €1.5M | 10.00× |
| #9 | Diego Coppola Paris FC | 22 | 21-23 | €10.0M | €1.5M | 6.67× |
| #10 | Soumaïla Coulibaly Stade Brestois 29 | 22 | 21-23 | €7.0M | €1.5M | 4.67× |
| #11 | Mikayil Faye Stade Rennais FC | 22 | 21-23 | €6.0M | €1.5M | 4.00× |
| #12 | Naoufel El Hannach Paris Saint-Germain | 19 | U21 | €1.2M | €350K | 3.43× |
| #13 | Abdoul Koné Stade Reims | 21 | 21-23 | €5.0M | €1.5M | 3.33× |
| #14 | Arouna Sangante Le Havre AC | 24 | 24-26 | €10.0M | €3.0M | 3.33× |
| #15 | Otávio Paris FC | 24 | 24-26 | €10.0M | €3.0M | 3.33× |
| #16 | Anthony Rouault Stade Rennais FC | 25 | 24-26 | €9.0M | €3.0M | 3.00× |
| #17 | Noham Kamara Paris Saint-Germain | 19 | U21 | €1.0M | €350K | 2.86× |
| #18 | Nidal Celik RC Lens | 20 | U21 | €1.0M | €350K | 2.86× |
| #19 | Clément Akpa AJ Auxerre | 24 | 24-26 | €8.0M | €3.0M | 2.67× |
| #20 | Antoine Mendy OGC Nice | 22 | 21-23 | €4.0M | €1.5M | 2.67× |
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)
OGC Nice's Amidou Doumbouya at 18 years old has the highest Return-to-Peak Potential at +48%. That means Kyllian Antonio is projected to appreciate 48% as they reach their peak age in 8 years-representing significant upside before entering their prime.
In second is RC Lens's Kyllian Antonio, who is 18 years old, with a +48% RPP (8 years to peak). Third is Isaac Cossier of LOSC Lille, who is 19 years old with a +44% 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 48% RPP means the player is expected to gain 48% 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 | Amidou Doumbouya OGC Nice | 18 | 8 | €200K | €384K | +48% |
| #2 | Kyllian Antonio RC Lens | 18 | 8 | €250K | €480K | +48% |
| #3 | Isaac Cossier LOSC Lille | 19 | 7 | €200K | €357K | +44% |
| #4 | Naoufel El Hannach Paris Saint-Germain | 19 | 7 | €1.2M | €2.1M | +44% |
| #5 | Noham Kamara Paris Saint-Germain | 19 | 7 | €1.0M | €1.8M | +44% |
| #6 | Nidal Celik RC Lens | 20 | 6 | €1.0M | €1.7M | +40% |
| #7 | Yoni Gomis RC Strasbourg Alsace | 20 | 6 | €350K | €582K | +40% |
| #8 | Anthony Khelifa AC Ajaccio | 20 | 6 | €150K | €249K | +40% |
| #9 | Abdelhamid Ait Boudlal Stade Rennais FC | 20 | 6 | €10.0M | €16.6M | +40% |
| #10 | Ismaëlo Ganiou RC Lens | 21 | 5 | €3.0M | €4.6M | +35% |
| #11 | Jérémy Jacquet Stade Rennais FC | 21 | 5 | €20.0M | €30.9M | +35% |
| #12 | Christian Mawissa AS Monaco | 21 | 5 | €15.0M | €23.2M | +35% |
| #13 | Telli Siwe AJ Auxerre | 21 | 5 | €1.0M | €1.5M | +35% |
| #14 | Abdoul Koné Stade Reims | 21 | 5 | €5.0M | €7.7M | +35% |
| #15 | Nehemiah Fernandez Paris Saint-Germain | 21 | 5 | €250K | €386K | +35% |
| #16 | Souleymane Sagnan RC Lens | 21 | 5 | €400K | €618K | +35% |
| #17 | Rony Mimb Baheng Olympique Marseille | 21 | 5 | €300K | €464K | +35% |
| #18 | Ritchy Valme AS Monaco | 21 | 5 | €200K | €309K | +35% |
| #19 | Franci Bouebari RC Strasbourg Alsace | 22 | 4 | €250K | €359K | +30% |
| #20 | Ismaël Doukouré RC Strasbourg Alsace | 22 | 4 | €18.0M | €25.9M | +30% |
Risk-Adjusted Upside (RAU)
Upside potential weighted against forecast uncertainty. Higher RAU = better risk-reward profile.
Understanding Risk-Adjusted Upside (RAU)
RC Lens's Kyllian Antonio has the highest Risk-Adjusted Upside at 94.8. That means Kyllian Antonio has 28% upside potential with only 0% forecast uncertainty-representing excellent risk-reward for value appreciation.
In second is OGC Nice's Amidou Doumbouya with a 94.8 RAU (28% upside, 0% uncertainty). Third is Naoufel El Hannach of Paris Saint-Germain with a 82.7 RAU (23% upside, 0% uncertainty).
How RAU is calculated: RAU divides upside potential by forecast uncertainty (RAU = Upside % ÷ Uncertainty %). A RAU of 94.8 means the upside is 94.8× 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 | Kyllian Antonio RC Lens | €320K | €283K-356K | +28% | 94.8 |
| #2 | Amidou Doumbouya OGC Nice | €256K | €226K-285K | +28% | 94.8 |
| #3 | Naoufel El Hannach Paris Saint-Germain | €1.5M | €1.3M-1.7M | +23% | 82.7 |
| #4 | Isaac Cossier LOSC Lille | €247K | €219K-275K | +23% | 82.7 |
| #5 | Noham Kamara Paris Saint-Germain | €1.2M | €1.1M-1.4M | +23% | 82.7 |
| #6 | Yoni Gomis RC Strasbourg Alsace | €417K | €369K-465K | +19% | 69.6 |
| #7 | Nidal Celik RC Lens | €1.2M | €1.1M-1.3M | +19% | 69.6 |
| #8 | Anthony Khelifa AC Ajaccio | €179K | €158K-199K | +19% | 69.6 |
| #9 | Abdelhamid Ait Boudlal Stade Rennais FC | €11.9M | €10.5M-13.3M | +19% | 69.6 |
| #10 | Christian Mawissa AS Monaco | €17.2M | €15.2M-19.2M | +15% | 55.6 |
| #11 | Souleymane Sagnan RC Lens | €459K | €406K-511K | +15% | 55.6 |
| #12 | Ritchy Valme AS Monaco | €229K | €203K-256K | +15% | 55.6 |
| #13 | Ismaëlo Ganiou RC Lens | €3.4M | €3.0M-3.8M | +15% | 55.6 |
| #14 | Telli Siwe AJ Auxerre | €1.1M | €1.0M-1.3M | +15% | 55.6 |
| #15 | Nehemiah Fernandez Paris Saint-Germain | €287K | €254K-320K | +15% | 55.6 |
| #16 | Jérémy Jacquet Stade Rennais FC | €22.9M | €20.3M-25.6M | +15% | 55.6 |
| #17 | Abdoul Koné Stade Reims | €5.7M | €5.1M-6.4M | +15% | 55.6 |
| #18 | Rony Mimb Baheng Olympique Marseille | €344K | €304K-384K | +15% | 55.6 |
| #19 | Willian Pacho Paris Saint-Germain | €78.0M | €70.2M-85.8M | +11% | 51.3 |
| #20 | Soumaïla Coulibaly Stade Brestois 29 | €7.7M | €6.9M-8.5M | +10% | 46.5 |
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 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)
Thonon Évian Grand Genève FC's Cédric Cambon in the 30+ age bracket has the highest Age-Share Concentration at +-27.5%. That means Marquinhos captures 25.3% of total market value while representing only 52.8% of players in their age group-showing dominant elite status.
In second is Montpellier HSC's Nikola Maksimović with a +-27.5% ASC (25.3% value share vs 52.8% player share in 30+ bracket). Third is Samuel Umtiti of LOSC Lille with a +-27.5% ASC (25.3% value vs 52.8% players in 30+ bracket).
How ASC is calculated: ASC = (% of total value) - (% of total players) in age bracket. A +-27.5% ASC means the player captures -27.5% 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 | Cédric Cambon Thonon Évian Grand Genève FC | 30+ | 25.3% | 52.8% | -27.5% |
| #2 | Nikola Maksimović Montpellier HSC | 30+ | 25.3% | 52.8% | -27.5% |
| #3 | Samuel Umtiti LOSC Lille | 30+ | 25.3% | 52.8% | -27.5% |
| #4 | Jonathan Gradit RC Lens | 30+ | 25.3% | 52.8% | -27.5% |
| #5 | Mickaël Firmin FC Toulouse | 30+ | 25.3% | 52.8% | -27.5% |
| #6 | Zakaria Diallo RC Lens | 30+ | 25.3% | 52.8% | -27.5% |
| #7 | Julien Berthomier OGC Nice | 30+ | 25.3% | 52.8% | -27.5% |
| #8 | Nicolas Pallois FC Nantes | 30+ | 25.3% | 52.8% | -27.5% |
| #9 | Cheick Touré FC Lorient | 30+ | 25.3% | 52.8% | -27.5% |
| #10 | Kara Mbodj FC Nantes | 30+ | 25.3% | 52.8% | -27.5% |
| #11 | Léo Lacroix AS Saint-Étienne | 30+ | 25.3% | 52.8% | -27.5% |
| #12 | Wesley Lautoa Dijon FCO | 30+ | 25.3% | 52.8% | -27.5% |
| #13 | Mory Koné ESTAC Troyes | 30+ | 25.3% | 52.8% | -27.5% |
| #14 | Ádám Lang Dijon FCO | 30+ | 25.3% | 52.8% | -27.5% |
| #15 | Uros Radakovic FC Nantes | 30+ | 25.3% | 52.8% | -27.5% |
| #16 | Josué Albert Clermont Foot 63 | 30+ | 25.3% | 52.8% | -27.5% |
| #17 | Nicolas Saint-Ruf SC Bastia | 30+ | 25.3% | 52.8% | -27.5% |
| #18 | Prince Gouano Amiens SC | 30+ | 25.3% | 52.8% | -27.5% |
| #19 | Gaël Vena FC Toulouse | 30+ | 25.3% | 52.8% | -27.5% |
| #20 | Eric Dier AS Monaco | 30+ | 25.3% | 52.8% | -27.5% |
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: 9 immediate targets, 52 standard acquisitions, 0 watch-list prospects, 42 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 €500K. 0 undervalued, 35 premium.
Value Positioning vs Peers
| Player | Market Value | Position Median | Z-Score | Assessment |
|---|---|---|---|---|
Rasmus Nicolaisen FC Toulouse | €5.0M | €500K | -1.33 | Good Value |
Eric Dier AS Monaco | €7.0M | €500K | -1.00 | Good Value |
Thilo Kehrer AS Monaco | €18.0M | €500K | -1.00 | Good Value |
Mark McKenzie FC Toulouse | €6.0M | €500K | -1.00 | Good Value |
Christopher Wooh Stade Rennais FC | €5.0M | €500K | -1.00 | Good Value |
Moussa Niakhaté Olympique Lyon | €16.0M | €500K | -0.67 | Good Value |
Montassar Talbi FC Lorient | €7.0M | €500K | -0.67 | Good Value |
Alidu Seidu Stade Rennais FC | €6.0M | €500K | -0.67 | Good Value |
Christian Mawissa AS Monaco | €15.0M | €500K | -0.60 | Good Value |
Charlie Cresswell FC Toulouse | €15.0M | €500K | -0.60 | Good Value |
Maxime Wackers FC Lorient | €150K | €500K | -0.58 | Good Value |
Vincent Peugnet FC Metz | €175K | €500K | -0.57 | Good Value |
Abdoul Koné Stade Reims | €5.0M | €500K | -0.50 | Fair Value |
Ryan Bidounga AS Nancy-Lorraine | €300K | €500K | -0.50 | Fair Value |
Thomas Basila FC Nantes | €300K | €500K | -0.50 | Fair Value |
Abdel Medioub FC Girondins Bordeaux | €350K | €500K | -0.47 | Fair Value |
Félix Eboa Eboa EA Guingamp | €400K | €500K | -0.44 | Fair Value |
Saad Agouzoul AJ Auxerre | €500K | €500K | -0.39 | Fair Value |
Julien Berthomier OGC Nice | €150K | €500K | -0.38 | Fair Value |
Cheick Touré FC Lorient | €150K | €500K | -0.38 | Fair Value |
How We Rank Ligue 1 Centre-Backs
Our Analytical Strength Index is calibrated specifically for centre-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 CB
Historical Achievement Index (35%)
Peak career market value for Ligue 1 centre-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 Ligue 1 centre-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%)
Ligue 1 receives Top 5 European league premium for competitive intensity and quality of opposition.
Performance Expectations Multiplier (2%)
Players at clubs with Champions League pedigree face higher performance standards and tactical complexity, contributing to development and market validation.
CB 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 centre-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 Ligue 1 Centre-Backs in the 2025-26 season
Who are the most valuable Centre-Backs in the Ligue 1 in 2025-26?
The most valuable centre-back in the Ligue 1 in 2025-26 is Willian Pacho, who is worth €70.0M and plays for Paris Saint-Germain. The second most valuable is Ilya Zabarnyi (€50.0M, Paris Saint-Germain), followed by Marquinhos (€30.0M, Paris Saint-Germain). Our database tracks 235 Ligue 1 Centre-Backs with comprehensive market valuations updated for the 2025-26 season.
How are Ligue 1 Centre-Backs ranked?
Ligue 1 Centre-Backs are ranked by our proprietary Analytical Strength Index, which is specifically calibrated for Centre-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 Ligue 1 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 Centre-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 centre-back from the Ligue 1?
Transfer fees for Ligue 1 Centre-Backs vary significantly based on market value, contract length, and club bargaining position. For the top-ranked centre-back Willian Pacho (market value: €70.0M), estimated transfer fees would range from €56.0M to €98.0M 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 Ligue 1 transactions.
What is the value forecast for Ligue 1 Centre-Backs?
Our 1-year forecast model projects market value changes for Ligue 1 Centre-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 Ligue 1 centre-back data come from?
Our Ligue 1 centre-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 Ligue 1 sources and updated monthly for the 2025-26 season to ensure accuracy for recruitment and investment decisions.