RisingTransfers
AI DNA Similarity

Best Alternatives to Lewis Dunk

Players most similar to Lewis Dunk (Defender, €4.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Lewis Dunk

  1. 1.Tyrone Mings85% DNA match·Aston Villa€4.0M
  2. 2.Adam Webster84% DNA match·Brighton & Hove Albion€7.0M
  3. 3.Jorge Cuenca85% DNA match·Fulham€8.0M

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

RT

Intelligence Verdict

Chances MissedTop 0%
???Bottom 22%

A Ball-Playing CB....

See Full Verdict + Share Card →

Playing Style Analysis

Ball-Playing CBBall-PlayingAerial

A Ball-Playing CB. Statistically, he stands out as commanding in the air (4.5 clearances/90), meticulous in distribution (92% pass accuracy), wins the physical battle (60% duel success), heavily involved in possession (79 passes/90), central to possession (90 touches/90), uses long balls frequently (5.5/90) and active off the ball (2.2 press score/90), contributing to defensive transitions. The three most similar players to Lewis Dunk by playing style are:

  • Tyrone Mings(85% match)A Ball-Playing CB. Statistically, he stands out as naturally left-footed, commanding in the air (5.5 clearances/90), meticulous in distribution (89% pass accuracy), wins the physical battle (56% duel success), heavily involved in possession (62 passes/90), central to possession (74 touches/90) and uses long balls frequently (6.1/90).
  • Adam Webster(84% match)A Ball-Playing CB. Statistically, he stands out as commanding in the air (4.0 clearances/90), reads the game exceptionally (2.0 interceptions/90), meticulous in distribution (88% pass accuracy), wins the physical battle (64% duel success), heavily involved in possession (72 passes/90), penetrates with forward passing (10.8 final-third passes/90), central to possession (85 touches/90), uses long balls frequently (8.5/90) and active off the ball (2.3 press score/90), contributing to defensive transitions. Note: this profile is based on 888 minutes of playing time this season.
  • Jorge Cuenca(85% match)A Ball-Playing CB. Statistically, he stands out as naturally left-footed, commanding in the air (7.1 clearances/90), reads the game exceptionally (1.6 interceptions/90), meticulous in distribution (88% pass accuracy), heavily involved in possession (60 passes/90), central to possession (74 touches/90), uses long balls frequently (7.1/90) and active off the ball (2.3 press score/90), contributing to defensive transitions.

Transfer Intelligence

Tyrone Mings delivers 85% of the same playing style, with 0.29 tackles won per 90 at age 33.

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

L
Comparison Base
Lewis Dunk
DefenderEngland€4.0M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
T
Tyrone Mings
Aston Villa · Premier League
England33yContract 2027
Tkl/900.29
KP/900.36
Ball-Playing CBBall-Playing
Last 5: ↓ Dip
85% match
€4.0M
#2
A
Adam Webster
Brighton & Hove Albion · Premier League
England31yContract 2026
Tkl/901.11
KP/900.30
Ball-Playing CBBall-Playing
vs Dunk: 3y younger
84% match
€7.0M
#3
J
Jorge Cuenca
Fulham · Premier League
Spain26yContract 2028
Tkl/901.64
KP/900.29
Ball-Playing CBBall-Playing
Last 5: ↓ Dip
vs Dunk: 8y younger
85% match
€8.0M
#4
M
Marcos Senesi
AFC Bournemouth · Premier League
Argentina29yContract 2026
Tkl/901.71
KP/900.69
Ball-Playing CBBall-Playing
Last 5: → Stable
84% match
€22.0M
#5
M
Marc Guéhi
Manchester City · Premier League
England25yContract 2026
Tkl/901.55
KP/900.45
Ball-Playing CBAerial
Last 5: → Stable
84% match
€65.0M
#6
M
Michael Keane
Everton · Premier League
England33yContract 2026
Tkl/901.27
KP/900.04
Ball-Playing CBAerial
Last 5: ↑ Hot
83% match
€4.0M
#7
C
Calvin Verdonk
LOSC Lille · Ligue 1
Netherlands29yContract 2028
Tkl/903.05
KP/901.22
Active Full-BackBall-Playing
Last 5: ↓ Dip
84% match
€3.0M
#8
J
James Hill
AFC Bournemouth · Premier League
England24yContract 2026
Tkl/901.77
KP/900.61
Physical StopperAerial
Last 5: → Stable
84% match
€15.0M
#9
K
Kristoffer Ajer
Brentford · Premier League
Norway28yContract 2028
Tkl/901.87
KP/900.26
Physical StopperAerial
Last 5: ↓ Dip
83% match
€18.0M
#10
E
Ezri Konsa
Aston Villa · Premier League
England28yContract 2028
Tkl/900.67
KP/900.15
Ball-Playing CBBall-Playing
Last 5: → Stable
82% match
€40.0M
#11
V
Virgil van Dijk
Liverpool · Premier League
Netherlands34yContract 2027
Tkl/900.61
KP/900.31
Ball-Playing CBBall-Playing
Last 5: ↓ Dip
82% match
€18.0M
#12
J
Joachim Andersen
Fulham · Premier League
Denmark29yContract 2029
Tkl/901.41
KP/900.22
Ball-Playing CBBall-Playing
Last 5: → Stable
82% match
€25.0M

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 Lewis Dunk.

Ask AI about Lewis Dunk

Frequently Asked Questions

Who are the best alternatives to Lewis Dunk?
The top alternatives to Lewis Dunk based on AI DNA playing style analysis include: Tyrone Mings, Adam Webster, Jorge Cuenca, Marcos Senesi, Marc Guéhi. 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 Lewis Dunk in 2026?
Players with a similar profile to Lewis Dunk in 2026 include Tyrone Mings (€4.0M), Adam Webster (€7.0M), Jorge Cuenca (€8.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Lewis Dunk play and who plays similarly?
Lewis Dunk plays as a Defender. Players with a comparable positional profile include Tyrone Mings (England, €4.0M); Adam Webster (England, €7.0M); Jorge Cuenca (Spain, €8.0M); Marcos Senesi (Argentina, €22.0M).
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.