Best Defensive Midfielders in the Ligue 1 (Jun 2026)
Ranked by Analytical Strength Score
Market Overview: Ligue 1 Defensive Midfielders 2023-24
Our database tracked 32 Ligue 1 Defensive Midfielders in the 2023-24 season, representing 17 clubs with a combined market value of €316.6M. The average market value for Ligue 1 Defensive Midfielders was €9.9M, with the average age at 27.1 years old.
The most valuable defensive midfielder in the Ligue 1 was Vitinha, worth €110.0M and played for Paris Saint-Germain at 26 years old. The top 5 Defensive Midfielders averaged €39.8M in market value, including Arthur Vermeeren and Denis Zakaria.
Age distribution showed the youngest tracked defensive midfielder was Hamidou Makalou (19 years, Stade Brestois 29, €800K), while the oldest was Benjamin André (35 years, LOSC Lille, €4.0M). Research shows Defensive Midfielders typically peak at age 26-27.
Historical analysis showed 15 Defensive Midfielders (47%) increased in market value over the following 12 months based on age-curve trajectories, then-current performance trends, and playing time analysis. The Ligue 1 market for Defensive Midfielders remained actively developing with emerging talent in the 2023-24 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 Ligue 1
Interactive bubble chart showing predicted 2-year growth vs current age for all Ligue 1 Defensive Midfielders. Identify undervalued assets and track market momentum across 17 clubs with €316.6M combined value.
Age Distribution: Ligue 1 Defensive Midfielders
The Ligue 1 CDM market shows 5 distinct age segments, with the largest cohort in the 30+ bracket (9 players, 28% of market). The 24-26 age group holds the most value at €139.3M, averaging €23.2M per player.
Top Defensive Midfielders by Age Bracket
U21 Years (2 players)
21-23 Years (7 players)
24-26 Years (6 players)
27-29 Years (8 players)
Market Value Distribution
Elite Tier Concentration
The top 4 Defensive Midfielders (13% of players) control €181.0M
Market Tiers
Market structure shows distributed value with elite (€50m+) tier representing 3% of the Ligue 1 CDM pool.
Elite (€50M+)
High (€15-30M)
Mid (€5-15M)
Club Distribution: Ligue 1 Defensive Midfielders
Among 17 Ligue 1 clubs, Paris Saint-Germain leads with 1 Defensive Midfielders worth €110.0M (averaging €110.0M per player). The top 10 clubs account for 66% of tracked Defensive Midfielders.
Paris Saint-Germain (1 Defensive Midfielders)
Olympique Marseille (3 Defensive Midfielders)
Olympique Lyon (3 Defensive Midfielders)
AS Monaco (1 Defensive Midfielders)
Player Rankings
Ranked by APE Strength Score. Click any player to view full profile, or click the chart icon to see value history.
Vitinha
Paris Saint-Germain • 26 years old
€95.1M
€110.0M
+15.6%
Expected: €111.9M
95.5
Arthur Vermeeren
Olympique Marseille • 21 years old
€24.2M
€28.0M
+15.6%
Expected: €32.1M
77.9
Denis Zakaria
AS Monaco • 29 years old
€32.3M
€25.0M
-22.6%
Expected: €22.0M
76.7
Tyler Morton
Olympique Lyon • 23 years old
€15.6M
€18.0M
+15.6%
Expected: €19.1M
73.1
Pierre-Emile Højbjerg
Olympique Marseille • 30 years old
€23.2M
€18.0M
-22.6%
Expected: €15.0M
72.7
Tanner Tessmann
Olympique Lyon • 24 years old
€10.4M
€12.0M
+15.6%
Expected: €12.8M
68.4
Ngal'ayel Mukau
LOSC Lille • 21 years old
€10.4M
€12.0M
+15.6%
Expected: €13.8M
67.2
Orel Mangala
Olympique Lyon • 28 years old
€10.6M
€10.0M
-5.4%
Expected: €8.8M
61.3
Johann Lepenant
FC Nantes • 23 years old
€6.1M
€7.0M
+15.6%
Expected: €7.4M
57.6
Junior Mwanga
RC Strasbourg Alsace • 23 years old
€6.1M
€7.0M
+15.6%
Expected: €7.4M
57.6
Charles Vanhoutte
OGC Nice • 27 years old
€6.1M
€7.0M
+15.6%
Expected: €7.2M
56.6
Joris Chotard
Stade Brestois 29 • 24 years old
€5.2M
€6.0M
+15.6%
Expected: €6.4M
56.0
Maxime Lopez
Paris FC • 28 years old
€6.3M
€6.0M
-5.4%
Expected: €5.3M
54.8
Boubacar Traoré
FC Metz • 24 years old
€4.3M
€5.0M
+15.6%
Expected: €5.4M
53.7
Geoffrey Kondogbia
Olympique Marseille • 33 years old
€6.5M
€5.0M
-22.6%
Expected: €4.4M
53.4
Pierre Lees-Melou
Paris FC • 33 years old
€6.5M
€5.0M
-22.6%
Expected: €4.4M
53.4
Nabil Bentaleb
LOSC Lille • 31 years old
€6.5M
€5.0M
-22.6%
Expected: €4.2M
53.0
Salis Abdul Samed
OGC Nice • 26 years old
€3.9M
€4.5M
+15.6%
Expected: €4.4M
51.4
Benjamin André
LOSC Lille • 35 years old
€5.2M
€4.0M
-22.6%
Expected: €3.5M
50.9
Lucas Gourna-Douath
Le Havre AC • 22 years old
€3.5M
€4.0M
+15.6%
Expected: €4.4M
50.1
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)
Olympique Marseille's Arthur Vermeeren at 21 years old has the highest Pre-Peak Value Efficiency at 4.00×. That means Arthur Vermeeren is valued 4.00× higher than the median player in the 21-23 age bracket—representing exceptional value before reaching peak age.
In second is Olympique Lyon's Tyler Morton, who is 23 years old, with a 2.57× PPVE. Third is Tanner Tessmann of Olympique Lyon, who is 24 years old with a 2.00× 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 4.00× means the player is worth 300% 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 | Arthur Vermeeren Olympique Marseille | 21 | 21-23 | €28.0M | €7.0M | 4.00× |
| #2 | Tyler Morton Olympique Lyon | 23 | 21-23 | €18.0M | €7.0M | 2.57× |
| #3 | Tanner Tessmann Olympique Lyon | 24 | 24-26 | €12.0M | €6.0M | 2.00× |
| #4 | Ngal'ayel Mukau LOSC Lille | 21 | 21-23 | €12.0M | €7.0M | 1.71× |
| #5 | Junior Mwanga RC Strasbourg Alsace | 23 | 21-23 | €7.0M | €7.0M | 1.00× |
| #6 | Johann Lepenant FC Nantes | 23 | 21-23 | €7.0M | €7.0M | 1.00× |
| #7 | Joris Chotard Stade Brestois 29 | 24 | 24-26 | €6.0M | €6.0M | 1.00× |
| #8 | Fodé Sylla RC Lens | 20 | U21 | €1.0M | €1.0M | 1.00× |
| #9 | Boubacar Traoré FC Metz | 24 | 24-26 | €5.0M | €6.0M | 0.83× |
| #10 | Hamidou Makalou Stade Brestois 29 | 19 | U21 | €800K | €1.0M | 0.80× |
| #11 | Lucas Gourna-Douath Le Havre AC | 22 | 21-23 | €4.0M | €7.0M | 0.57× |
| #12 | Oussama El Azzouzi AJ Auxerre | 25 | 24-26 | €1.8M | €6.0M | 0.30× |
| #13 | Cedrik Gbo Etoile Sportive du Sahel | 23 | 21-23 | €400K | €7.0M | 0.06× |
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)
Stade Brestois 29's Hamidou Makalou at 19 years old has the highest Return-to-Peak Potential at +44%. That means Hamidou Makalou is projected to appreciate 44% as they reach their peak age in 7 years—representing significant upside before entering their prime.
In second is RC Lens's Fodé Sylla, who is 20 years old, with a +40% RPP (6 years to peak). Third is Ngal'ayel Mukau of LOSC Lille, who is 21 years old with a +35% 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 44% RPP means the player is expected to gain 44% 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 | Hamidou Makalou Stade Brestois 29 | 19 | 7 | €800K | €1.4M | +44% |
| #2 | Fodé Sylla RC Lens | 20 | 6 | €1.0M | €1.7M | +40% |
| #3 | Ngal'ayel Mukau LOSC Lille | 21 | 5 | €12.0M | €18.5M | +35% |
| #4 | Arthur Vermeeren Olympique Marseille | 21 | 5 | €28.0M | €43.3M | +35% |
| #5 | Lucas Gourna-Douath Le Havre AC | 22 | 4 | €4.0M | €5.7M | +30% |
| #6 | Junior Mwanga RC Strasbourg Alsace | 23 | 3 | €7.0M | €9.4M | +25% |
| #7 | Johann Lepenant FC Nantes | 23 | 3 | €7.0M | €9.4M | +25% |
| #8 | Tyler Morton Olympique Lyon | 23 | 3 | €18.0M | €24.1M | +25% |
| #9 | Cedrik Gbo Etoile Sportive du Sahel | 23 | 3 | €400K | €535K | +25% |
| #10 | Joris Chotard Stade Brestois 29 | 24 | 2 | €6.0M | €7.5M | +20% |
| #11 | Tanner Tessmann Olympique Lyon | 24 | 2 | €12.0M | €14.9M | +20% |
| #12 | Boubacar Traoré FC Metz | 24 | 2 | €5.0M | €6.2M | +20% |
| #13 | Oussama El Azzouzi AJ Auxerre | 25 | 1 | €1.8M | €2.1M | +14% |
Risk-Adjusted Upside (RAU)
Upside potential weighted against forecast uncertainty. Higher RAU = better risk-reward profile.
Understanding Risk-Adjusted Upside (RAU)
Stade Brestois 29's Hamidou Makalou has the highest Risk-Adjusted Upside at 68.9. That means Hamidou Makalou has 23% upside potential with only 0% forecast uncertainty—representing excellent risk-reward for value appreciation.
In second is RC Lens's Fodé Sylla with a 58.0 RAU (19% upside, 0% uncertainty). Third is Ngal'ayel Mukau of LOSC Lille 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 68.9 means the upside is 68.9× 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 | Hamidou Makalou Stade Brestois 29 | €988K | €852K-1.1M | +23% | 68.9 |
| #2 | Fodé Sylla RC Lens | €1.2M | €1.0M-1.4M | +19% | 58.0 |
| #3 | Ngal'ayel Mukau LOSC Lille | €13.8M | €11.9M-15.7M | +15% | 46.3 |
| #4 | Arthur Vermeeren Olympique Marseille | €32.1M | €27.7M-36.5M | +15% | 46.3 |
| #5 | Lucas Gourna-Douath Le Havre AC | €4.4M | €3.9M-4.9M | +10% | 38.7 |
| #6 | Boubacar Traoré FC Metz | €5.4M | €4.7M-6.0M | +7% | 27.5 |
| #7 | Joris Chotard Stade Brestois 29 | €6.4M | €5.7M-7.2M | +7% | 27.5 |
| #8 | Tanner Tessmann Olympique Lyon | €12.8M | €11.3M-14.4M | +7% | 27.5 |
| #9 | Tyler Morton Olympique Lyon | €19.1M | €16.8M-21.3M | +6% | 23.0 |
| #10 | Junior Mwanga RC Strasbourg Alsace | €7.4M | €6.5M-8.3M | +6% | 23.0 |
| #11 | Johann Lepenant FC Nantes | €7.4M | €6.5M-8.3M | +6% | 23.0 |
| #12 | Cedrik Gbo Etoile Sportive du Sahel | €423K | €373K-474K | +6% | 23.0 |
| #13 | Charles Vanhoutte OGC Nice | €7.2M | €6.3M-8.1M | +3% | 12.0 |
| #14 | Oussama El Azzouzi AJ Auxerre | €1.8M | €1.6M-2.1M | +2% | 9.8 |
| #15 | Vitinha Paris Saint-Germain | €111.9M | €98.5M-125.3M | +2% | 7.1 |
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: defensive midfielder 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)
Paris Saint-Germain's Vitinha in the 24-26 age bracket has the highest Age-Share Concentration at +25.3%. That means Vitinha captures 44.0% of total market value while representing only 18.8% of players in their age group—showing dominant elite status.
In second is AJ Auxerre's Oussama El Azzouzi with a +25.3% ASC (44.0% value share vs 18.8% player share in 24-26 bracket). Third is Joris Chotard of Stade Brestois 29 with a +25.3% ASC (44.0% value vs 18.8% players in 24-26 bracket).
How ASC is calculated: ASC = (% of total value) - (% of total players) in age bracket. A +25.3% ASC means the player captures 25.3% 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 | Vitinha Paris Saint-Germain | 24-26 | 44.0% | 18.8% | +25.3% |
| #2 | Oussama El Azzouzi AJ Auxerre | 24-26 | 44.0% | 18.8% | +25.3% |
| #3 | Joris Chotard Stade Brestois 29 | 24-26 | 44.0% | 18.8% | +25.3% |
| #4 | Boubacar Traoré FC Metz | 24-26 | 44.0% | 18.8% | +25.3% |
| #5 | Tanner Tessmann Olympique Lyon | 24-26 | 44.0% | 18.8% | +25.3% |
| #6 | Salis Abdul Samed OGC Nice | 24-26 | 44.0% | 18.8% | +25.3% |
| #7 | Benjamin Stambouli FC Metz | 30+ | 13.6% | 28.1% | -14.5% |
| #8 | Geoffrey Kondogbia Olympique Marseille | 30+ | 13.6% | 28.1% | -14.5% |
| #9 | Pierre-Emile Højbjerg Olympique Marseille | 30+ | 13.6% | 28.1% | -14.5% |
| #10 | Abdoulaye Touré Le Havre AC | 30+ | 13.6% | 28.1% | -14.5% |
| #11 | Laurent Abergel FC Lorient | 30+ | 13.6% | 28.1% | -14.5% |
| #12 | Nabil Bentaleb LOSC Lille | 30+ | 13.6% | 28.1% | -14.5% |
| #13 | Pierre Lees-Melou Paris FC | 30+ | 13.6% | 28.1% | -14.5% |
| #14 | Francis Coquelin FC Nantes | 30+ | 13.6% | 28.1% | -14.5% |
| #15 | Benjamin André LOSC Lille | 30+ | 13.6% | 28.1% | -14.5% |
| #16 | Assane Dioussé AJ Auxerre | 27-29 | 17.7% | 25.0% | -7.3% |
| #17 | Orel Mangala Olympique Lyon | 27-29 | 17.7% | 25.0% | -7.3% |
| #18 | Maxime Lopez Paris FC | 27-29 | 17.7% | 25.0% | -7.3% |
| #19 | Denis Zakaria AS Monaco | 27-29 | 17.7% | 25.0% | -7.3% |
| #20 | Ibrahima Sissoko FC Nantes | 27-29 | 17.7% | 25.0% | -7.3% |
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: 2 immediate targets, 10 standard acquisitions, 0 watch-list prospects, 9 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 €110.0M. 0 undervalued, 0 premium.
Value Positioning vs Peers
| Player | Market Value | Position Median | Z-Score | Assessment |
|---|---|---|---|---|
Hamidou Makalou Stade Brestois 29 | €800K | €5.0M | -1.00 | Good Value |
Oussama El Azzouzi AJ Auxerre | €1.8M | €5.0M | -1.00 | Good Value |
Tyler Morton Olympique Lyon | €18.0M | €5.0M | -1.00 | Good Value |
Cedrik Gbo Etoile Sportive du Sahel | €400K | €5.0M | -1.00 | Good Value |
Assane Dioussé AJ Auxerre | €600K | €5.0M | -0.91 | Good Value |
Djihad Bizimana CS Constantine | €850K | €5.0M | -0.81 | Good Value |
Benjamin Stambouli FC Metz | €300K | €5.0M | -0.77 | Good Value |
Francis Coquelin FC Nantes | €800K | €5.0M | -0.55 | Good Value |
Maxime Lopez Paris FC | €6.0M | €5.0M | -0.25 | Fair Value |
Boubacar Traoré FC Metz | €5.0M | €5.0M | -0.14 | Fair Value |
Junior Mwanga RC Strasbourg Alsace | €7.0M | €5.0M | 0.00 | Fair Value |
Geoffrey Kondogbia Olympique Marseille | €5.0M | €5.0M | 0.00 | Fair Value |
Pierre-Emile Højbjerg Olympique Marseille | €18.0M | €5.0M | 0.00 | Fair Value |
Laurent Abergel FC Lorient | €2.0M | €5.0M | 0.00 | Fair Value |
Nabil Bentaleb LOSC Lille | €5.0M | €5.0M | 0.00 | Fair Value |
Denis Zakaria AS Monaco | €25.0M | €5.0M | 0.00 | Fair Value |
Ibrahima Sissoko FC Nantes | €3.0M | €5.0M | 0.00 | Fair Value |
Pierre Lees-Melou Paris FC | €5.0M | €5.0M | 0.00 | Fair Value |
Vitinha Paris Saint-Germain | €110.0M | €5.0M | 0.00 | Fair Value |
Charles Vanhoutte OGC Nice | €7.0M | €5.0M | 0.00 | Fair Value |