RisingTransfers
AI DNA Similarity

Best Alternatives to Benjamin Pavard

Players most similar to Benjamin Pavard (Defender, €15.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Benjamin Pavard

  1. 1.Min-jae Kim87% DNA match·FC Bayern München€25.0M
  2. 2.Jonathan Tah87% DNA match·FC Bayern München€30.0M
  3. 3.Jules Koundé86% DNA match·FC Barcelona€65.0M

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

RT

Intelligence Verdict

Aerials WonTop 14%
???Bottom 7%

A Ball-Playing CB....

See Full Verdict + Share Card →

Playing Style Analysis

Ball-Playing CBBall-Playing

A Ball-Playing CB. Statistically, he stands out as meticulous in distribution (92% pass accuracy), wins the physical battle (67% duel success), heavily involved in possession (63 passes/90) and central to possession (75 touches/90). The three most similar players to Benjamin Pavard by playing style are:

  • Min-jae Kim(87% match)A Ball-Playing CB. Statistically, he stands out as commanding in the air (4.6 clearances/90), reads the game exceptionally (2.1 interceptions/90), meticulous in distribution (95% pass accuracy), wins the physical battle (64% duel success), heavily involved in possession (88 passes/90), penetrates with forward passing (9.0 final-third passes/90), central to possession (101 touches/90) and a high-intensity presser (press score 3.1/90), constantly disrupting opposition build-up.
  • Jonathan Tah(87% match)A Ball-Playing CB. Statistically, he stands out as commanding in the air (5.4 clearances/90), meticulous in distribution (96% pass accuracy), wins the physical battle (60% duel success), heavily involved in possession (86 passes/90), penetrates with forward passing (8.1 final-third passes/90), central to possession (98 touches/90) and active off the ball (2.2 press score/90), contributing to defensive transitions.
  • Jules Koundé(86% match)A Active Full-Back. Statistically, he stands out as active in the tackle (1.9 tackles/90), meticulous in distribution (91% pass accuracy), heavily involved in possession (74 passes/90) and central to possession (95 touches/90).

Transfer Intelligence

Min-jae Kim delivers 87% of the same playing style, at a 67% premium over Benjamin Pavard, with 1.07 tackles won per 90 at age 29.

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

B
Comparison Base
Benjamin Pavard
DefenderFrance€15.0M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
M
Min-jae Kim
FC Bayern München · Bundesliga
South Korea29yContract 2028
Tkl/901.07
KP/900.27
Ball-Playing CBBall-Playing
Last 5: ↑ Hot
vs Pavard: €10M more expensive
87% match
€25.0M
#2
J
Jonathan Tah
FC Bayern München · Bundesliga
Germany30yContract 2029
Tkl/901.28
KP/900.24
Ball-Playing CBBall-Playing
Last 5: ↓ Dip
vs Pavard: €15M more expensive
87% match
€30.0M
#3
J
Jules Koundé
FC Barcelona · La Liga
France27yContract 2027
Tkl/901.95
KP/900.69
Active Full-BackBall-Playing
Last 5: → Stable
vs Pavard: €50M more expensive · 3y younger
86% match
€65.0M
#4
T
Tobias Müller
Magdeburg · Bundesliga
Germany31y
Tkl/901.65
KP/900.35
Ball-Playing CBBall-Playing
Last 5: → Stable
86% match
€5.0M
#5
W
Willian Pacho
Paris Saint Germain · Ligue 1
Ecuador24yContract 2029
Tkl/901.88
KP/900.25
Ball-Playing CBBall-Playing
Last 5: → Stable
85% match
€70.0M
#6
L
Loïc Badé
Bayer 04 Leverkusen · Bundesliga
France26yContract 2030
Tkl/902.37
KP/900.59
Ball-Playing CBBall-Playing
85% match
€25.0M
#7
A
Arthur Theate
Eintracht Frankfurt · Bundesliga
Belgium25yContract 2029
Tkl/902.42
KP/900.70
Ball-Playing CBBall-Playing
84% match
€20.0M
#8
A
Antoine Mendy
Nice · Ligue 1
France21yContract 2028
Tkl/903.14
KP/900.00
Ball-Playing CBAerial
Last 5: → Stable
84% match
€4.0M
#9
D
Dayot Upamecano
FC Bayern München · Bundesliga
France27yContract 2026
Tkl/902.13
KP/900.44
Ball-Playing CBBall-Playing
Last 5: ↑ Hot
85% match
€70.0M
#10
T
Thilo Kehrer
Germany · Ligue 1
Germany29yContract 2028
Tkl/901.70
KP/900.13
Ball-Playing CBBall-Playing
Last 5: ↑ Hot
85% match
€18.0M
#11
M
Manuel Akanji
Inter · Serie A
Switzerland30yContract 2026
Tkl/901.47
KP/900.20
Ball-Playing CBBall-Playing
Last 5: ↓ Dip
84% match
€22.0M
#12
I
Ibrahima Konaté
Liverpool · Premier League
France26yContract 2026
Tkl/901.60
KP/900.22
Ball-Playing CBBall-Playing
Last 5: → Stable
84% match
€50.0M

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 Benjamin Pavard.

Ask AI about Benjamin Pavard

Frequently Asked Questions

Who are the best alternatives to Benjamin Pavard?
The top alternatives to Benjamin Pavard based on AI DNA playing style analysis include: Min-jae Kim, Jonathan Tah, Jules Koundé, Tobias Müller, Willian Pacho. 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 Benjamin Pavard in 2026?
Players with a similar profile to Benjamin Pavard in 2026 include Min-jae Kim (€25.0M), Jonathan Tah (€30.0M), Jules Koundé (€65.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Benjamin Pavard play and who plays similarly?
Benjamin Pavard plays as a Defender. Players with a comparable positional profile include Min-jae Kim (South Korea, €25.0M); Jonathan Tah (Germany, €30.0M); Jules Koundé (France, €65.0M); Tobias Müller (Germany, €5.0M).
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.