AI DNA Similarity
Best Alternatives to Heo Yong-Jun
Players most similar to Heo Yong-Jun (Attacker, €393K) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.
Top 3 Alternatives to Heo Yong-Jun
- 1.Stefano Lilipaly99% DNA match·SC Cambuur
- 2.Bryan Limbombe96% DNA match·Heracles Almelo
- 3.Jacob Ambaek96% DNA match·Brøndby IF
Ranked by AI DNA similarity — 768 dimensions across playing style, pressing intensity, and tactical fit.
RT
Intelligence Verdict
AssistsTop 25%
???Bottom 0%
“A Forward....”
See Full Verdict + Share Card →Playing Style Analysis
A Forward. Statistically, he stands out as a regular goalscorer (0.21 goals/90) and a reliable supplier (0.21 assists/90). The three most similar players to Heo Yong-Jun by playing style are:
- Stefano Lilipaly(99% match) — A Forward. Statistically, he stands out as a regular goalscorer (0.22 goals/90) and a reliable supplier (0.22 assists/90).
- Bryan Limbombe(96% match) — A Forward. Statistically, he stands out as a capable chance creator (1.3 key passes/90) and a reliable supplier (0.21 assists/90).
- Jacob Ambaek(96% 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
S
Stefano Lilipaly
SC Cambuur · Eredivisie
Indonesia36y
G/900.22
A/900.22
vs Yong-Jun: 3y older
99% match
N/A
#2
B
Bryan Limbombe
Heracles Almelo · Eredivisie
Belgium24y
G/900.07
A/900.21
vs Yong-Jun: 9y younger · -0.14 G/90
96% match
N/A
#3
J
Jacob Ambaek
Brøndby IF · Superliga
Denmark18yContract 2027
G/900.46
A/900.00
Complete Forward
Last 5: ↑ Hotvs Yong-Jun: 15y younger · +0.25 G/90
96% match
N/A
#4
D
Delano Ladan
Koninklijke HFC · Eredivisie
Netherlands26y
G/900.20
A/900.00
96% match
N/A
#5
J
Jeffrey Adjei-Broni
Hvidovre · Superliga
Denmark22y
G/900.00
A/900.00
96% match
N/A
#6
M
Marco Matias
Farense · Liga Portugal
Portugal37y
G/900.21
A/900.21
96% match
N/A
#7
A
Anders Jacobsen
Vejle Boldklub · Superliga
Denmark36y
G/900.37
A/900.00
Small Sample
96% match
N/A
#8
G
Gavin Vlijter
De Treffers · Eredivisie
Netherlands29y
G/900.18
A/900.30
95% match
N/A
#9
G
Gustav Ølsted Marcussen
Fredericia · Superliga
Denmark27y
G/900.26
A/900.09
95% match
N/A
#10
J
Joshua Zimmerman
Livingston · Eredivisie
Netherlands24y
G/900.00
A/900.15
95% match
N/A
#11
A
Alessio Besio
Verl · Bundesliga
Switzerland22y
G/900.09
A/900.17
95% match
N/A
#12
C
Christian Gammelgaard
Vejle Boldklub · Superliga
Denmark23y
G/900.35
A/900.00
Complete Forward
Last 5: ↓ Dip95% 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 Heo Yong-Jun.
Ask AI about Heo Yong-Jun →Frequently Asked Questions
Who are the best alternatives to Heo Yong-Jun?▼
The top alternatives to Heo Yong-Jun based on AI DNA playing style analysis include: Stefano Lilipaly, Bryan Limbombe, Jacob Ambaek, Delano Ladan, Jeffrey Adjei-Broni. 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 Heo Yong-Jun in 2026?▼
Players with a similar profile to Heo Yong-Jun in 2026 include Stefano Lilipaly (N/A), Bryan Limbombe (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 Heo Yong-Jun play and who plays similarly?▼
Heo Yong-Jun plays as a Attacker. Players with a comparable positional profile include Stefano Lilipaly (Indonesia, N/A); Bryan Limbombe (Belgium, N/A); Jacob Ambaek (Denmark, N/A); Delano Ladan (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.