RisingTransfers
AI DNA Similarity

Best Alternatives to Johann Lepenant

Players most similar to Johann Lepenant (Midfielder, €7.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Johann Lepenant

  1. 1.Lamine Camara86% DNA match·Monaco€35.0M
  2. 2.Samir El Mourabet86% DNA match·Strasbourg€18.0M
  3. 3.Mahdi Camara86% DNA match·Rennes€10.0M

Ranked by AI DNA similarity — 768 dimensions across playing style, pressing intensity, and tactical fit.

RT

Intelligence Verdict

Chances MissedTop 0%
???Bottom 1%

A Ball-Winner....

See Full Verdict + Share Card →

Playing Style Analysis

Ball-WinnerCreativeDefensiveSmall Sample

A Ball-Winner. Statistically, he stands out as an elite creator (2.1 key passes/90), an aggressive ball-winner (3.3 tackles/90), wins the physical battle (58% duel success), wins the ball cleanly (2.3 successful tackles/90), heavily involved in play (56 touches/90), draws fouls effectively (2.1/90), a high-intensity presser (press score 4.0/90), constantly disrupting opposition build-up and top 20% creator in the league. Note: this profile is based on 633 minutes of playing time this season. The three most similar players to Johann Lepenant by playing style are:

  • Lamine Camara(86% match)A Metronome. Statistically, he stands out as an elite creator (1.7 key passes/90), a reliable supplier (0.24 assists/90), active in the tackle (2.5 tackles/90), reads the game exceptionally (2.2 interceptions/90), meticulous in distribution (86% pass accuracy), wins the physical battle (58% duel success), central to possession (82 touches/90), draws fouls effectively (2.5/90), a high-intensity presser (press score 4.3/90), constantly disrupting opposition build-up and top 20% creator in the league.
  • Samir El Mourabet(86% match)A Ball-Winner. Statistically, he stands out as naturally left-footed, a capable chance creator (1.4 key passes/90), an aggressive ball-winner (3.9 tackles/90), meticulous in distribution (90% pass accuracy), wins the physical battle (66% duel success), wins the ball cleanly (2.1 successful tackles/90), heavily involved in play (69 touches/90), active off the ball (2.4 press score/90), contributing to defensive transitions and top 10% tackler in the league. Note: this profile is based on 461 minutes of playing time this season.
  • Mahdi Camara(86% match)A Box-to-Box. Statistically, he stands out as active in the tackle (1.9 tackles/90), meticulous in distribution (86% pass accuracy) and heavily involved in play (54 touches/90).

Transfer Intelligence

Lamine Camara delivers 86% of the same playing style, at a 400% premium over Johann Lepenant, with 1.40 key passes per 90 at age 22.

Similarity is calculated using per-90 performance data across multiple playing style dimensions. How Player DNA matching works →

J
Comparison Base
Johann Lepenant
MidfielderFrance€7.0M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
L
Lamine Camara
Monaco · Ligue 1
Senegal22yContract 2029
KP/901.40
G/900.00
MetronomeCreative
Last 5: → Stable
vs Lepenant: €28M more expensive
86% match
€35.0M
#2
S
Samir El Mourabet
Strasbourg · Ligue 1
France20yContract 2030
KP/900.52
G/900.13
Ball-WinnerDefensive
Last 5: ↓ Dip
vs Lepenant: €11M more expensive · 3y younger
86% match
€18.0M
#3
M
Mahdi Camara
Rennes · Ligue 1
France27yContract 2029
KP/900.97
G/900.00
Box-to-Box
Last 5: ↓ Dip
vs Lepenant: 4y older
86% match
€10.0M
#4
E
Enzo Le Fée
Sunderland · Premier League
France26yContract 2029
KP/901.57
G/900.13
CreatorCreative
Last 5: ↑ Hot
85% match
€25.0M
#5
J
Joris Chotard
Brest · Ligue 1
France24yContract 2029
KP/900.44
G/900.00
Ball-WinnerSmall Sample
Last 5: ↑ Hot
86% match
€6.0M
#6
M
Mamadou Sangaré
Lens · Ligue 1
Mali23yContract 2030
KP/902.24
G/900.00
CreatorCreative
Last 5: → Stable
85% match
€15.0M
#7
P
Pape Demba Diop
Toulouse · Ligue 1
Senegal22yContract 2026
KP/900.92
G/900.00
Box-to-BoxSmall Sample
85% match
€4.0M
#8
A
Abdoul Ouattara
Strasbourg · Ligue 1
France20yContract 2029
KP/900.79
G/900.32
Last 5: ↓ Dip
85% match
€9.0M
#9
K
Kévin Danois
Auxerre · Ligue 1
France21yContract 2029
KP/901.64
G/900.07
Box-to-BoxCreative
Last 5: ↓ Dip
84% match
€10.0M
#10
A
Arthur Vermeeren
Olympique Marseille · Ligue 1
Belgium21y
KP/901.10
G/900.00
Ball-WinnerDefensive
85% match
€20.0M
#11
C
Charles Vanhoutte
Nice · Ligue 1
Belgium27yContract 2029
KP/902.40
G/900.00
Box-to-Box
85% match
€7.0M
#12
C
Cristian Cásseres Jr.
Toulouse · Ligue 1
Venezuela26yContract 2027
KP/901.98
G/900.10
Ball-WinnerCreative
Last 5: → Stable
84% match
€7.0M

Ask AI: Why are these players similar?

Our 768-dimension Player DNA model matches playing style, physical profile, pressing intensity, and tactical fit. Ask the AI to explain exactly what makes these players statistically similar to Johann Lepenant.

Ask AI about Johann Lepenant

Frequently Asked Questions

Who are the best alternatives to Johann Lepenant?
The top alternatives to Johann Lepenant based on AI DNA playing style analysis include: Lamine Camara, Samir El Mourabet, Mahdi Camara, Enzo Le Fée, Joris Chotard. These players were matched using Rising Transfers' 768-dimension DNA model across playing style, pressing intensity, and tactical fit — not just position or market value.
Which players are similar to Johann Lepenant in 2026?
Players with a similar profile to Johann Lepenant in 2026 include Lamine Camara (€35.0M), Samir El Mourabet (€18.0M), Mahdi Camara (€10.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Johann Lepenant play and who plays similarly?
Johann Lepenant plays as a Midfielder. Players with a comparable positional profile include Lamine Camara (Senegal, €35.0M); Samir El Mourabet (France, €18.0M); Mahdi Camara (France, €10.0M); Enzo Le Fée (France, €25.0M).
How does Rising Transfers find similar players?
Rising Transfers uses a proprietary 768-dimension Player DNA model trained on 3.2 million match events. Each player is represented as a vector across 35+ per-90 metrics including pressing intensity, passing footprint, dribbling profile, and defensive contribution. Similarity is measured using cosine distance — the same technique used in state-of-the-art AI systems — making it the most precise player comparison tool available publicly.