AI DNA Similarity
Best Alternatives to Marcos Felipe
Players most similar to Marcos Felipe (Goalkeeper, N/A) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.
Top 3 Alternatives to Marcos Felipe
- 1.Paul Izzo100% DNA match·Randers FC
- 2.Lazar Carević100% DNA match·Famalicão
- 3.Alfonso Herrero100% DNA match·Málaga
Ranked by AI DNA similarity — 768 dimensions across playing style, pressing intensity, and tactical fit.
RT
Intelligence Verdict
Key PassesTop 9%
???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 (88% success) and reliable in goal (3.2 saves/90). The three most similar players to Marcos Felipe by playing style are:
- Paul Izzo(100% match) — A Sweeper-Keeper. Statistically, he stands out as dominant in aerial duels (93% success) and reliable in goal (3.3 saves/90).
- Lazar Carević(100% match) — A Sweeper-Keeper. Statistically, he stands out as dominant in aerial duels (94% success).
- Alfonso Herrero(100% match) — A Sweeper-Keeper. Statistically, he stands out as dominant in aerial duels (86% 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
P
Paul Izzo
Randers FC · Superliga
Australia31yContract 2027
Tkl/900.10
Sweeper-Keeper
100% match
N/A
#2
L
Lazar Carević
Famalicão · Liga Portugal
Montenegro27y
Tkl/900.03
Sweeper-Keeper
vs Felipe: 3y younger
100% match
N/A
#3
A
Alfonso Herrero
Málaga · La Liga
Spain32yContract 2028
Tkl/900.14
Sweeper-Keeper
vs Felipe: 2y older
100% match
N/A
#4
V
Volkan Babacan
İstanbul Başakşehir · Super Lig
Turkey37y
Tkl/900.00
Sweeper-Keeper
99% match
N/A
#5
B
Benjamin Uphoff
Hansa Rostock · Bundesliga
Germany32yContract 2026
Tkl/900.00
Sweeper-Keeper
99% match
N/A
#6
D
Deniz Dilmen
İstanbul Başakşehir · Super Lig
Turkey20y
Tkl/900.03
Sweeper-Keeper
99% match
N/A
#7
H
Hans Christian Bernat
Karlsruher SC · Bundesliga
Denmark25y
Tkl/900.00
Sweeper-Keeper
99% match
N/A
#8
T
Timo Jansink
Heracles Almelo · Eredivisie
Netherlands22y
Tkl/900.00
Sweeper-Keeper
99% match
N/A
#9
M
Mory Diaw
Le Havre · Ligue 1
Senegal32yContract 2027
Tkl/900.00
Traditional KeeperSmall Sample
99% match
N/A
#10
N
Nahuel Noll
Hannover 96 · Bundesliga
Germany23yContract 2026
Tkl/900.00
Sweeper-Keeper
99% match
N/A
#11
A
A. Kappenberger
Hillerød · Superliga
Denmark29y
Tkl/900.07
Sweeper-Keeper
99% match
N/A
#12
M
Max Thompson
Ayr United · Premier League
England21yContract 2026
Tkl/900.06
Sweeper-Keeper
98% match
N/A
⬡
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 Marcos Felipe.
Ask AI about Marcos Felipe →Frequently Asked Questions
Who are the best alternatives to Marcos Felipe?▼
The top alternatives to Marcos Felipe based on AI DNA playing style analysis include: Paul Izzo, Lazar Carević, Alfonso Herrero, Volkan Babacan, Benjamin Uphoff. 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 Marcos Felipe in 2026?▼
Players with a similar profile to Marcos Felipe in 2026 include Paul Izzo (N/A), Lazar Carević (N/A), Alfonso Herrero (N/A). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Marcos Felipe play and who plays similarly?▼
Marcos Felipe plays as a Goalkeeper. Players with a comparable positional profile include Paul Izzo (Australia, N/A); Lazar Carević (Montenegro, N/A); Alfonso Herrero (Spain, N/A); Volkan Babacan (Turkey, 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.