AI DNA Similarity
Best Alternatives to Marcus Rohdén
Players most similar to Marcus Rohdén (Midfielder, €500K) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.
Top 3 Alternatives to Marcus Rohdén
- 1.Maurizio Brenna86% DNA match·Katwijk
- 2.Jeremiah Mensah85% DNA match·Bayer 04 Leverkusen
- 3.Salvador Blopa84% DNA match·Sporting CP
Ranked by AI DNA similarity — 768 dimensions across playing style, pressing intensity, and tactical fit.
RT
Intelligence Verdict
AssistsTop 0%
???Bottom 2%
“Marcus Rohdén is a Midfielder....”
See Full Verdict + Share Card →Playing Style Analysis
Small Sample
Marcus Rohdén is a Midfielder. Solid midfield option. (Limited sample: 339 mins) The three most similar players to Marcus Rohdén by playing style are:
- Maurizio Brenna(86% match) — Maurizio Brenna is a Midfielder. Solid midfield option. (Limited sample: 299 mins)
- Jeremiah Mensah(85% match) — Jeremiah Dennit Mensah is a Midfielder. Solid midfield option. (Limited sample: 327 mins)
- Salvador Blopa(84% 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
M
Maurizio Brenna
Katwijk · Eredivisie
Netherlands27y
KP/900.00
G/900.00
Small Sample
vs Rohdén: 8y younger
86% match
N/A
#2
J
Jeremiah Mensah
Bayer 04 Leverkusen · Bundesliga
Germany18y
KP/900.00
G/900.00
Small Sample
vs Rohdén: 17y younger
85% match
N/A
#3
S
Salvador Blopa
Sporting CP · Liga Portugal
Portugal18y
KP/900.00
G/900.00
Small Sample
vs Rohdén: 17y younger
84% match
N/A
#4
G
Gerry Vlak
Koninklijke HFC · Eredivisie
Netherlands30y
KP/900.00
G/900.00
Small Sample
83% match
N/A
#5
K
Kiano Dyer
FC Volendam · Eredivisie
England19y
KP/900.00
G/900.00
Small Sample
83% match
N/A
#6
Y
Yanis Khafi
Paris Saint Germain · Ligue 1
France20y
KP/901.18
G/900.00
Small Sample
82% match
N/A
#7
D
Daniel Bisgard Haarbo
Fredericia · Superliga
Denmark23y
KP/900.00
G/900.31
Small Sample
82% match
N/A
#8
M
M. Rochester
HB Køge · Superliga
Denmark33y
KP/900.81
G/900.00
Box-to-BoxSmall Sample
82% match
N/A
#9
D
Doni Arifi
SpVgg Greuther Fürth · Bundesliga
Finland24y
KP/901.12
G/900.00
Small Sample
Last 5: ↓ Dip82% match
N/A
#10
E
Emmanuele De Chiara
Napoli · Serie A
Italy20y
KP/900.00
G/900.00
Small Sample
81% match
N/A
#11
Y
Yellu Santiago
Arouca · Liga Portugal
Spain21y
KP/900.29
G/900.00
Small Sample
Last 5: ↓ Dip81% match
N/A
#12
R
Rick van der Meer
Katwijk · Eredivisie
Netherlands28y
KP/900.00
G/900.00
Small Sample
81% 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 Marcus Rohdén.
Ask AI about Marcus Rohdén →Frequently Asked Questions
Who are the best alternatives to Marcus Rohdén?▼
The top alternatives to Marcus Rohdén based on AI DNA playing style analysis include: Maurizio Brenna, Jeremiah Mensah, Salvador Blopa, Gerry Vlak, Kiano Dyer. 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 Marcus Rohdén in 2026?▼
Players with a similar profile to Marcus Rohdén in 2026 include Maurizio Brenna (N/A), Jeremiah Mensah (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 Marcus Rohdén play and who plays similarly?▼
Marcus Rohdén plays as a Midfielder. Players with a comparable positional profile include Maurizio Brenna (Netherlands, N/A); Jeremiah Mensah (Germany, N/A); Salvador Blopa (Portugal, N/A); Gerry Vlak (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.