AI DNA Similarity
Best Alternatives to Ivan Nevistic
Players most similar to Ivan Nevistic (Goalkeeper, €3.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.
Top 3 Alternatives to Ivan Nevistic
- 1.Mark De Vries85% DNA match·Katwijk
- 2.David Spinelli84% DNA match·Napoli
- 3.D. Dönmezer83% DNA match·Kayserispor
Ranked by AI DNA similarity — 768 dimensions across playing style, pressing intensity, and tactical fit.
RT
Intelligence Verdict
Goals ConcededTop 11%
???Bottom 0%
“Ivan Nevistić is a Traditional Keeper....”
See Full Verdict + Share Card →Playing Style Analysis
Traditional Keeper
Ivan Nevistić is a Traditional Keeper. Line-focused shot-stopper. The three most similar players to Ivan Nevistic by playing style are:
- Mark De Vries(85% match) — Mark de Vries is a Traditional Keeper. Line-focused shot-stopper. (Limited sample: 330 mins)
- David Spinelli(84% match) — David Spinelli is a Traditional Keeper. Line-focused shot-stopper. (Limited sample: 270 mins)
- D. Dönmezer(83% match) — A Traditional Keeper. Statistically, he stands out as dominant in aerial duels (84% success) and exceptionally busy shot-stopper (4.5 saves/90). However, he concedes frequently (2.74/90).
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
M
Mark De Vries
Katwijk · Eredivisie
Netherlands39y
Tkl/900.00
Traditional KeeperSmall Sample
vs Nevistic: 12y older
85% match
N/A
#2
D
David Spinelli
Napoli · Serie A
Italy18y
Tkl/900.00
Traditional KeeperSmall Sample
vs Nevistic: 9y younger
84% match
N/A
#3
D
D. Dönmezer
Kayserispor · Super Lig
17y
Tkl/901.00
Traditional Keeper
vs Nevistic: 10y younger
83% match
N/A
#4
T
Tim Coremans
FC Dordrecht · Eredivisie
Netherlands35y
Tkl/900.00
Traditional KeeperSmall Sample
83% match
N/A
#5
O
Okan Kocuk
Samsunspor · Super Lig
Turkey30yContract 2028
Tkl/900.07
Traditional Keeper
82% match
N/A
#6
J
Joey Kesting
Katwijk · Eredivisie
Netherlands25y
Tkl/900.00
Traditional KeeperSmall Sample
83% match
N/A
#7
K
Koen Bucker
FC Emmen · Eredivisie
Netherlands29y
Tkl/900.08
Reliable Keeper
82% match
N/A
#8
Z
Ziga Frelih
Spartak Trnava · Liga Portugal
Slovenia28y
Tkl/900.23
Reliable Keeper
82% match
N/A
#9
O
Oskar Snorre Olsen
Lyngby Boldklub · Superliga
Denmark27y
Tkl/900.00
Traditional Keeper
82% match
N/A
#10
A
Andrés Prieto
Ponferradina · La Liga
Spain32y
Tkl/900.00
Traditional KeeperSmall Sample
82% match
N/A
#11
M
Mateus Pasinato
Cuiabá · Liga Portugal
Brazil33y
Tkl/900.00
Reliable Keeper
81% match
N/A
#12
J
Juan Pérez
Huesca · La Liga
Spain29yContract 2026
Tkl/900.00
Traditional KeeperSmall Sample
82% 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 Ivan Nevistic.
Ask AI about Ivan Nevistic →Frequently Asked Questions
Who are the best alternatives to Ivan Nevistic?▼
The top alternatives to Ivan Nevistic based on AI DNA playing style analysis include: Mark De Vries, David Spinelli, D. Dönmezer, Tim Coremans, Okan Kocuk. 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 Ivan Nevistic in 2026?▼
Players with a similar profile to Ivan Nevistic in 2026 include Mark De Vries (N/A), David Spinelli (N/A), D. Dönmezer (N/A). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Ivan Nevistic play and who plays similarly?▼
Ivan Nevistic plays as a Goalkeeper. Players with a comparable positional profile include Mark De Vries (Netherlands, N/A); David Spinelli (Italy, N/A); D. Dönmezer (, N/A); Tim Coremans (Netherlands, 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.