AI DNA Similarity
Best Alternatives to Jorginho
Players most similar to Jorginho (Attacker, €100K) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.
Top 3 Alternatives to Jorginho
- 1.Kanga Akalé99% DNA match·Middelfart
- 2.Soufiane Hetli97% DNA match·Telstar
- 3.Jacob Ambaek97% DNA match·Brøndby IF
Ranked by AI DNA similarity — 768 dimensions across playing style, pressing intensity, and tactical fit.
RT
Intelligence Verdict
Press IntensityTop 15%
“A Forward....”
See Full Verdict + Share Card →Playing Style Analysis
A Forward. Statistically, he stands out as a regular goalscorer (0.21 goals/90). The three most similar players to Jorginho by playing style are:
- Kanga Akalé(99% match) — A Complete Forward. Statistically, he stands out as a constant goal threat (2.9 shots/90) and a regular goalscorer (0.27 goals/90).
- Soufiane Hetli(97% match) — A Forward. Statistically, he stands out as a constant goal threat (2.9 shots/90) and draws fouls effectively (2.1/90). However, he loses possession under pressure (2.6 dispossessed/90).
- Jacob Ambaek(97% match) — A Complete Forward. Statistically, he stands out as a constant goal threat (2.7 shots/90) and a regular goalscorer (0.37 goals/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
K
Kanga Akalé
Middelfart · Superliga
France21y
G/900.32
A/900.11
Complete Forward
Last 5: ↑ Hotvs Jorginho: 7y younger · +0.11 G/90
99% match
N/A
#2
S
Soufiane Hetli
Telstar · Eredivisie
Netherlands24yContract 2026
G/900.17
A/900.06
vs Jorginho: 4y younger
97% match
N/A
#3
J
Jacob Ambaek
Brøndby IF · Superliga
Denmark18yContract 2027
G/900.46
A/900.00
Complete Forward
Last 5: ↑ Hotvs Jorginho: 10y younger · +0.25 G/90
97% match
N/A
#4
D
Dan Agyei
Kocaelispor · Super Lig
England28y
G/900.22
A/900.00
97% match
N/A
#5
E
Emmanuel Iyoha
Fortuna Düsseldorf · Bundesliga
Germany28yContract 2026
G/900.00
A/900.00
96% match
N/A
#6
G
Gustav Ølsted Marcussen
Fredericia · Superliga
Denmark27y
G/900.26
A/900.09
96% match
N/A
#7
W
William Martin
Odense BK · Superliga
Republic of Ireland19yContract 2027
G/900.25
A/900.08
Complete Forward
Last 5: ↑ Hot96% match
N/A
#8
D
Delano Ladan
Koninklijke HFC · Eredivisie
Netherlands26y
G/900.20
A/900.00
95% match
N/A
#9
F
Fabrício Garcia
Alverca · Liga Portugal
Cape Verde25yContract 2028
G/900.00
A/900.00
95% match
N/A
#10
J
Joshua Zimmerman
Livingston · Eredivisie
Netherlands24y
G/900.00
A/900.15
95% match
N/A
#11
N
Naïm Matoug
VVV-Venlo · Eredivisie
Netherlands23yContract 2026
G/900.18
A/900.09
95% match
N/A
#12
K
Kevin Csoboth
Gençlerbirliği · Super Lig
Hungary25y
G/900.07
A/900.07
95% 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 Jorginho.
Ask AI about Jorginho →Frequently Asked Questions
Who are the best alternatives to Jorginho?▼
The top alternatives to Jorginho based on AI DNA playing style analysis include: Kanga Akalé, Soufiane Hetli, Jacob Ambaek, Dan Agyei, Emmanuel Iyoha. 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 Jorginho in 2026?▼
Players with a similar profile to Jorginho in 2026 include Kanga Akalé (N/A), Soufiane Hetli (N/A), Jacob Ambaek (N/A). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Jorginho play and who plays similarly?▼
Jorginho plays as a Attacker. Players with a comparable positional profile include Kanga Akalé (France, N/A); Soufiane Hetli (Netherlands, N/A); Jacob Ambaek (Denmark, N/A); Dan Agyei (England, 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.