AI DNA Similarity
Best Alternatives to Mark Zabukovnik
Players most similar to Mark Zabukovnik (Midfielder, €150K) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.
Top 3 Alternatives to Mark Zabukovnik
- 1.Gerry Vlak86% DNA match·Koninklijke HFC
- 2.Maurizio Brenna84% DNA match·Katwijk
- 3.Salvador Blopa83% DNA match·Sporting CP
Ranked by AI DNA similarity — 768 dimensions across playing style, pressing intensity, and tactical fit.
RT
Intelligence Verdict
Chances MissedTop 0%
???Bottom 0%
“Mark Zabukovnik is a Midfielder....”
See Full Verdict + Share Card →Playing Style Analysis
Small Sample
Mark Zabukovnik is a Midfielder. Solid midfield option. (Limited sample: 389 mins) The three most similar players to Mark Zabukovnik by playing style are:
- Gerry Vlak(86% match) — Gerry Vlak is a Midfielder. Solid midfield option. (Limited sample: 378 mins)
- Maurizio Brenna(84% match) — Maurizio Brenna is a Midfielder. Solid midfield option. (Limited sample: 299 mins)
- Salvador Blopa(83% match) — Salvador Blopa is a Midfielder. Solid midfield option. (Limited sample: 270 mins)
Similarity is calculated using per-90 performance data across multiple playing style dimensions. How Player DNA matching works →
Similar Players — Ranked by DNA Similarity
#1
G
Gerry Vlak
Koninklijke HFC · Eredivisie
Netherlands30y
KP/900.00
G/900.00
Small Sample
vs Zabukovnik: 5y older
86% match
N/A
#2
M
Maurizio Brenna
Katwijk · Eredivisie
Netherlands27y
KP/900.00
G/900.00
Small Sample
vs Zabukovnik: 2y older
84% match
N/A
#3
S
Salvador Blopa
Sporting CP · Liga Portugal
Portugal18y
KP/900.00
G/900.00
Small Sample
vs Zabukovnik: 7y younger
83% match
N/A
#4
J
Jeremiah Mensah
Bayer 04 Leverkusen · Bundesliga
Germany18y
KP/900.00
G/900.00
Small Sample
83% match
N/A
#5
D
Doni Arifi
SpVgg Greuther Fürth · Bundesliga
Finland24y
KP/901.12
G/900.00
Small Sample
Last 5: ↓ Dip82% match
N/A
#6
K
Kiano Dyer
FC Volendam · Eredivisie
England19y
KP/900.00
G/900.00
Small Sample
82% match
N/A
#7
Y
Yanis Khafi
Paris Saint Germain · Ligue 1
France20y
KP/901.18
G/900.00
Small Sample
81% match
N/A
#8
J
Joseph Nduquidi
Metz · Ligue 1
France21y
KP/900.15
G/900.00
Balanced MidfielderSmall Sample
Last 5: ↓ Dip81% match
N/A
#9
N
Noah Fenyö
Eintracht Frankfurt · Bundesliga
Hungary20yContract 2029
KP/900.26
G/900.52
Small Sample
81% match
N/A
#10
D
Daniel Bisgard Haarbo
Fredericia · Superliga
Denmark23y
KP/900.00
G/900.31
Small Sample
81% match
N/A
#11
R
Rick van der Meer
Katwijk · Eredivisie
Netherlands28y
KP/900.00
G/900.00
Small Sample
81% match
N/A
#12
U
Ulrich Taffertshofer
Atlético Baleares · La Liga
Germany34yContract 2026
KP/900.00
G/900.00
80% match
N/A
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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 Mark Zabukovnik.
Ask AI about Mark Zabukovnik →Frequently Asked Questions
Who are the best alternatives to Mark Zabukovnik?▼
The top alternatives to Mark Zabukovnik based on AI DNA playing style analysis include: Gerry Vlak, Maurizio Brenna, Salvador Blopa, Jeremiah Mensah, Doni Arifi. 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 Mark Zabukovnik in 2026?▼
Players with a similar profile to Mark Zabukovnik in 2026 include Gerry Vlak (N/A), Maurizio Brenna (N/A), Salvador Blopa (N/A). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Mark Zabukovnik play and who plays similarly?▼
Mark Zabukovnik plays as a Midfielder. Players with a comparable positional profile include Gerry Vlak (Netherlands, N/A); Maurizio Brenna (Netherlands, N/A); Salvador Blopa (Portugal, N/A); Jeremiah Mensah (Germany, N/A).
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.