RisingTransfers
AI DNA Similarity

Best Alternatives to Martin Vitík

Players most similar to Martin Vitík (Defender, €10.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Martin Vitík

  1. 1.Nicolò Bertola86% DNA match·Udinese€6.0M
  2. 2.Jacobo Ramón85% DNA match·Como€18.0M
  3. 3.Tarik Muharemović85% DNA match·Sassuolo€20.0M

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

RT

Intelligence Verdict

InterceptionsTop 3%
???Bottom 8%

Vitík has quietly built a case as one of Serie A's more composed defensive presences this season—a...

See Full Verdict + Share Card →

Playing Style Analysis

Aerial Defender

Vitík has quietly built a case as one of Serie A's more composed defensive presences this season—a centre-back who wins his battles on the ground before they become aerial problems. His duel win rate sits in the top 20% of the league, which tells you something important: this isn't a defender who scrambles, he positions himself to make duels winnable. The counterintuitive read on his below-average interception numbers is that they may reflect conservative, disciplined positioning rather than passive defending—his tackle success rate in the top 30% suggests he's not missing challenges, just not gambling on them. The three most similar players to Martin Vitík by playing style are:

  • Nicolò Bertola(86% match)A Solid Defender. Statistically, he stands out as commanding in the air (4.4 clearances/90), uses long balls frequently (6.7/90) and active off the ball (2.1 press score/90), contributing to defensive transitions.
  • Jacobo Ramón(85% match)A Ball-Playing CB. Statistically, he stands out as active in the tackle (1.9 tackles/90), meticulous in distribution (91% pass accuracy), wins the physical battle (63% duel success), heavily involved in possession (73 passes/90), central to possession (87 touches/90), dominant in the air (3.7 aerials won/90, 70%) and active off the ball (2.4 press score/90), contributing to defensive transitions.
  • Tarik Muharemović(85% match)A Ball-Playing CB. Statistically, he stands out as naturally left-footed, commanding in the air (6.9 clearances/90), meticulous in distribution (86% pass accuracy), wins the physical battle (76% duel success) and uses long balls frequently (5.5/90).

Transfer Intelligence

Nicolò Bertola delivers 86% of the same playing style, at 40% lower cost (€6.0M vs €10.0M), with 1.78 tackles won per 90 at age 23.

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

M
Comparison Base
Martin Vitík
DefenderCzech Republic€10.0M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
N
Nicolò Bertola
Udinese · Serie A
Italy23yContract 2030
Tkl/901.78
KP/900.49
Solid DefenderAerial
86% match
€6.0M
#2
J
Jacobo Ramón
Como · Serie A
Spain21yContract 2030
Tkl/901.95
KP/900.43
Ball-Playing CBBall-Playing
Last 5: ↓ Dip
vs Vitík: €8M more expensive · 2y younger
85% match
€18.0M
#3
T
Tarik Muharemović
Sassuolo · Serie A
Bosnia and Herzegovina23yContract 2031
Tkl/901.36
KP/900.09
Ball-Playing CBAerial
Last 5: → Stable
vs Vitík: €10M more expensive
85% match
€20.0M
#4
O
Oumar Solet
Udinese · Serie A
France26yContract 2027
Tkl/902.13
KP/900.67
Ball-Playing CBBall-Playing
Last 5: ↑ Hot
85% match
€20.0M
#5
I
Isak Hien
Atalanta · Serie A
Sweden27yContract 2028
Tkl/902.44
KP/900.23
Ball-Playing CBAerial
Last 5: → Stable
85% match
€22.0M
#6
A
Alessandro Circati
Parma · Serie A
Australia22yContract 2029
Tkl/901.67
KP/900.17
Ball-Playing CBAerial
Last 5: → Stable
86% match
€8.0M
#7
T
Thomas Kristensen
Udinese · Serie A
Denmark24yContract 2028
Tkl/901.08
KP/900.08
Physical StopperAerial
Last 5: ↓ Dip
86% match
€12.0M
#8
J
Johan Vásquez
Genoa · Serie A
Mexico27yContract 2027
Tkl/901.67
KP/900.17
Ball-Playing CBBall-Playing
Last 5: → Stable
85% match
€13.0M
#9
O
Odilon Kossounou
Atalanta · Serie A
Ivory Coast25yContract 2029
Tkl/901.33
KP/900.11
Ball-Playing CBBall-Playing
Last 5: → Stable
85% match
€22.0M
#10
D
Diego Carlos
Como · Serie A
Brazil33yContract 2026
Tkl/901.47
KP/900.22
Ball-Playing CBBall-Playing
Last 5: → Stable
85% match
€8.5M
#11
L
Lloyd Kelly
Juventus · Serie A
England27yContract 2029
Tkl/901.77
KP/900.11
Ball-Playing CBBall-Playing
Last 5: → Stable
84% match
€20.0M
#12
E
Evan Ndicka
Roma · Serie A
France26yContract 2028
Tkl/900.85
KP/900.18
Ball-Playing CBBall-Playing
Last 5: → Stable
84% match
€30.0M

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 Martin Vitík.

Ask AI about Martin Vitík

Frequently Asked Questions

Who are the best alternatives to Martin Vitík?
The top alternatives to Martin Vitík based on AI DNA playing style analysis include: Nicolò Bertola, Jacobo Ramón, Tarik Muharemović, Oumar Solet, Isak Hien. 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 Martin Vitík in 2026?
Players with a similar profile to Martin Vitík in 2026 include Nicolò Bertola (€6.0M), Jacobo Ramón (€18.0M), Tarik Muharemović (€20.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Martin Vitík play and who plays similarly?
Martin Vitík plays as a Defender. Players with a comparable positional profile include Nicolò Bertola (Italy, €6.0M); Jacobo Ramón (Spain, €18.0M); Tarik Muharemović (Bosnia and Herzegovina, €20.0M); Oumar Solet (France, €20.0M).
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.