AI DNA Similarity
Best Alternatives to Deniz Dilmen
Players most similar to Deniz Dilmen (Goalkeeper, N/A) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.
Top 3 Alternatives to Deniz Dilmen
- 1.Benjamin Uphoff100% DNA match·Hansa Rostock
- 2.Volkan Babacan100% DNA match·İstanbul Başakşehir
- 3.Marcos Felipe99% DNA match·Eyüpspor
Ranked by AI DNA similarity — 768 dimensions across playing style, pressing intensity, and tactical fit.
RT
Intelligence Verdict
Goals ConcededTop 13%
???Bottom 0%
“A Sweeper-Keeper....”
See Full Verdict + Share Card →Playing Style Analysis
Sweeper-Keeper
A Sweeper-Keeper. Statistically, he stands out as dominant in aerial duels (100% success). The three most similar players to Deniz Dilmen by playing style are:
- Benjamin Uphoff(100% match) — A Sweeper-Keeper. Statistically, he stands out as dominant in aerial duels (100% success) and keeps goals out effectively (0.41 conceded/90).
- Volkan Babacan(100% match) — A Sweeper-Keeper. Statistically, he stands out as dominant in aerial duels (88% success) and keeps goals out effectively (0.39 conceded/90).
- Marcos Felipe(99% match) — A Sweeper-Keeper. Statistically, he stands out as dominant in aerial duels (88% success) and reliable in goal (3.2 saves/90).
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
B
Benjamin Uphoff
Hansa Rostock · Bundesliga
Germany32yContract 2026
Tkl/900.00
Sweeper-Keeper
vs Dilmen: 12y older
100% match
N/A
#2
V
Volkan Babacan
İstanbul Başakşehir · Super Lig
Turkey37y
Tkl/900.00
Sweeper-Keeper
vs Dilmen: 17y older
100% match
N/A
#3
M
Marcos Felipe
Eyüpspor · Super Lig
Brazil30y
Tkl/900.00
Sweeper-Keeper
vs Dilmen: 10y older
99% match
N/A
#4
A
Alfonso Herrero
Málaga · La Liga
Spain32yContract 2028
Tkl/900.14
Sweeper-Keeper
99% match
N/A
#5
L
Lazar Carević
Famalicão · Liga Portugal
Montenegro27y
Tkl/900.03
Sweeper-Keeper
99% match
N/A
#6
P
Paul Izzo
Randers FC · Superliga
Australia31yContract 2027
Tkl/900.10
Sweeper-Keeper
99% match
N/A
#7
M
Mory Diaw
Le Havre · Ligue 1
Senegal32yContract 2027
Tkl/900.00
Traditional KeeperSmall Sample
99% match
N/A
#8
N
Nahuel Noll
Hannover 96 · Bundesliga
Germany23yContract 2026
Tkl/900.00
Sweeper-Keeper
99% match
N/A
#9
A
A. Kappenberger
Hillerød · Superliga
Denmark29y
Tkl/900.07
Sweeper-Keeper
99% match
N/A
#10
M
Max Thompson
Ayr United · Premier League
England21yContract 2026
Tkl/900.06
Sweeper-Keeper
99% match
N/A
#11
H
Hans Christian Bernat
Karlsruher SC · Bundesliga
Denmark25y
Tkl/900.00
Sweeper-Keeper
98% match
N/A
#12
T
Timo Jansink
Heracles Almelo · Eredivisie
Netherlands22y
Tkl/900.00
Sweeper-Keeper
98% 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 Deniz Dilmen.
Ask AI about Deniz Dilmen →Frequently Asked Questions
Who are the best alternatives to Deniz Dilmen?▼
The top alternatives to Deniz Dilmen based on AI DNA playing style analysis include: Benjamin Uphoff, Volkan Babacan, Marcos Felipe, Alfonso Herrero, Lazar Carević. 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 Deniz Dilmen in 2026?▼
Players with a similar profile to Deniz Dilmen in 2026 include Benjamin Uphoff (N/A), Volkan Babacan (N/A), Marcos Felipe (N/A). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Deniz Dilmen play and who plays similarly?▼
Deniz Dilmen plays as a Goalkeeper. Players with a comparable positional profile include Benjamin Uphoff (Germany, N/A); Volkan Babacan (Turkey, N/A); Marcos Felipe (Brazil, N/A); Alfonso Herrero (Spain, 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.