RisingTransfers
AI DNA Similarity

Best Alternatives to Marc Guéhi

Players most similar to Marc Guéhi (Defender, €65.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Marc Guéhi

  1. 1.Trevoh Chalobah90% DNA match·Chelsea€40.0M
  2. 2.Ibrahima Konaté89% DNA match·Liverpool€50.0M
  3. 3.Malick Thiaw88% DNA match·Newcastle United€45.0M

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

RT

Intelligence Verdict

Aerials WonTop 11%
???Bottom 4%

A Ball-Playing CB....

See Full Verdict + Share Card →

Playing Style Analysis

Ball-Playing CBAerial

A Ball-Playing CB. Statistically, he stands out as commanding in the air (5.2 clearances/90), meticulous in distribution (85% pass accuracy), wins the physical battle (64% duel success), uses long balls frequently (6.3/90) and active off the ball (2.5 press score/90), contributing to defensive transitions. The three most similar players to Marc Guéhi by playing style are:

  • Trevoh Chalobah(90% match)A Ball-Playing CB. Statistically, he stands out as commanding in the air (5.7 clearances/90), meticulous in distribution (93% pass accuracy), wins the physical battle (59% duel success), heavily involved in possession (74 passes/90), central to possession (87 touches/90) and active off the ball (2.1 press score/90), contributing to defensive transitions.
  • Ibrahima Konaté(89% match)A Ball-Playing CB. Statistically, he stands out as commanding in the air (5.6 clearances/90), meticulous in distribution (90% pass accuracy), wins the physical battle (68% duel success), heavily involved in possession (63 passes/90), central to possession (77 touches/90) and dominant in the air (3.6 aerials won/90, 67%).
  • Malick Thiaw(88% match)Thiaw has quietly become one of the Premier League's most complete defensive profiles — a towering centre-back who doesn't just win his battles, he wins them cleanly. His aerial win rate of 65.1% and duel success of 64.2% both sit in the league's top 20%, but the counterintuitive story is his attacking output: 0.16 goals per 90 and 0.98 shots per 90 place him in the top 10% among defenders, suggesting a genuine threat from set-pieces that opponents routinely underestimate. His pass accuracy of 90.6% reflects a ball-player comfortable in possession-heavy systems, and his above-average delivery into the final third adds genuine build-up value.

Transfer Intelligence

Trevoh Chalobah delivers 90% of the same playing style, at 38% lower cost (€40.0M vs €65.0M), with 1.15 tackles won per 90 at age 26.

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

M
Comparison Base
Marc Guéhi
DefenderEngland€65.0M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
T
Trevoh Chalobah
Chelsea · Premier League
England26yContract 2028
Tkl/901.15
KP/900.16
Ball-Playing CBBall-Playing
Last 5: ↓ Dip
vs Guéhi: €25M cheaper
90% match
€40.0M
#2
I
Ibrahima Konaté
Liverpool · Premier League
France26yContract 2026
Tkl/901.60
KP/900.22
Ball-Playing CBBall-Playing
Last 5: → Stable
vs Guéhi: €15M cheaper
89% match
€50.0M
#3
M
Malick Thiaw
Newcastle United · Premier League
Germany24yContract 2029
Tkl/901.29
KP/900.19
Ball-Playing CBAerial
Last 5: ↑ Hot
vs Guéhi: €20M cheaper
88% match
€45.0M
#4
W
William Saliba
Arsenal · Premier League
France25yContract 2027
Tkl/901.28
KP/900.36
Ball-Playing CBBall-Playing
Last 5: → Stable
88% match
€90.0M
#5
N
Nayef Aguerd
Olympique Marseille · Ligue 1
Morocco30y
Tkl/902.00
KP/900.00
Ball-Playing CBBall-Playing
88% match
€35.0M
#6
S
Sven Botman
Newcastle United · Premier League
Netherlands26yContract 2027
Tkl/901.03
KP/900.43
Ball-Playing CBBall-Playing
Last 5: → Stable
88% match
€35.0M
#7
J
Joachim Andersen
Fulham · Premier League
Denmark29yContract 2029
Tkl/901.41
KP/900.22
Ball-Playing CBBall-Playing
Last 5: → Stable
87% match
€25.0M
#8
L
Levi Colwill
Chelsea · Premier League
England23yContract 2029
Tkl/901.41
KP/900.41
Ball-Playing CBBall-Playing
86% match
€50.0M
#9
J
Jaka Bijol
Leeds United · Premier League
Slovenia27yContract 2030
Tkl/901.30
KP/900.36
Ball-Playing CBAerial
Last 5: ↓ Dip
86% match
€18.0M
#10
J
Jan Paul van Hecke
Brighton & Hove Albion · Premier League
Netherlands25yContract 2027
Tkl/901.54
KP/900.36
Ball-Playing CBBall-Playing
Last 5: → Stable
86% match
€35.0M
#11
J
Joe Rodon
Leeds United · Premier League
Wales28yContract 2028
Tkl/901.14
KP/900.26
Ball-Playing CBAerial
Last 5: → Stable
86% match
€12.0M
#12
S
Sepp van den Berg
Brentford · Premier League
Netherlands24yContract 2029
Tkl/900.64
KP/900.20
Ball-Playing CBAerial
Last 5: → Stable
86% match
€28.0M

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 Marc Guéhi.

Ask AI about Marc Guéhi

Frequently Asked Questions

Who are the best alternatives to Marc Guéhi?
The top alternatives to Marc Guéhi based on AI DNA playing style analysis include: Trevoh Chalobah, Ibrahima Konaté, Malick Thiaw, William Saliba, Nayef Aguerd. 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 Marc Guéhi in 2026?
Players with a similar profile to Marc Guéhi in 2026 include Trevoh Chalobah (€40.0M), Ibrahima Konaté (€50.0M), Malick Thiaw (€45.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Marc Guéhi play and who plays similarly?
Marc Guéhi plays as a Defender. Players with a comparable positional profile include Trevoh Chalobah (England, €40.0M); Ibrahima Konaté (France, €50.0M); Malick Thiaw (Germany, €45.0M); William Saliba (France, €90.0M).
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.