AI DNA Similarity
Best Alternatives to Clé
Players most similar to Clé (Attacker, €138K) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.
Top 3 Alternatives to Clé
- 1.Noah Jose Saviolo97% DNA match·Vitória Guimarães
- 2.Kyliane Dong97% DNA match·FC Augsburg
- 3.Marco Matias97% DNA match·Farense
Ranked by AI DNA similarity — 768 dimensions across playing style, pressing intensity, and tactical fit.
Playing Style Analysis
A Forward. Statistically, he stands out as a regular goalscorer (0.20 goals/90), a reliable supplier (0.24 assists/90) and draws fouls effectively (2.0/90). The three most similar players to Clé by playing style are:
- Noah Jose Saviolo(97% match) — A Forward. Statistically, he stands out as a reliable supplier (0.21 assists/90) and draws fouls effectively (2.8/90).
- Kyliane Dong(97% match) — A Inside Forward. Statistically, he stands out as a capable chance creator (1.1 key passes/90), a regular goalscorer (0.35 goals/90), a reliable supplier (0.18 assists/90) and draws fouls effectively (2.1/90).
- Marco Matias(97% match) — A Forward. Statistically, he stands out as an elite creator (1.6 key passes/90), a regular goalscorer (0.21 goals/90), a reliable supplier (0.21 assists/90), creates high-quality scoring opportunities (1.00 big chances/90) and draws fouls effectively (2.9/90).
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
N
Noah Jose Saviolo
Vitória Guimarães · Liga Portugal
Belgium22y
G/900.10
A/900.20
vs Clé: 6y younger
97% match
N/A
#2
K
Kyliane Dong
FC Augsburg · Bundesliga
France21y
G/900.00
A/900.00
Inside Forward
vs Clé: 7y younger
97% match
N/A
#3
M
Marco Matias
Farense · Liga Portugal
Portugal37y
G/900.21
A/900.21
vs Clé: 9y older · +0.07 G/90
97% match
N/A
#4
S
Stefano Lilipaly
SC Cambuur · Eredivisie
Indonesia36y
G/900.22
A/900.22
97% match
N/A
#5
G
Gavin Vlijter
De Treffers · Eredivisie
Netherlands29y
G/900.18
A/900.30
96% match
N/A
#6
G
Gabriel Strefezza
Parma · Serie A
Brazil29yContract 2029
G/900.14
A/900.14
Small Sample
96% match
€7.0M
#7
L
Landerson
Moreirense · Liga Portugal
Brazil19y
G/900.00
A/900.15
96% match
N/A
#8
D
Delano Ladan
Koninklijke HFC · Eredivisie
Netherlands26y
G/900.20
A/900.00
96% match
N/A
#9
J
Jacob Ambaek
Brøndby IF · Superliga
Denmark18yContract 2027
G/900.46
A/900.00
Complete Forward
Last 5: ↑ Hot96% match
N/A
#10
A
Anders Jacobsen
Vejle Boldklub · Superliga
Denmark36y
G/900.37
A/900.00
Small Sample
95% match
N/A
#11
B
Bryan Limbombe
Heracles Almelo · Eredivisie
Belgium24y
G/900.07
A/900.21
95% match
N/A
#12
G
Gustav Ølsted Marcussen
Fredericia · Superliga
Denmark27y
G/900.26
A/900.09
95% 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 Clé.
Ask AI about Clé →Frequently Asked Questions
Who are the best alternatives to Clé?▼
The top alternatives to Clé based on AI DNA playing style analysis include: Noah Jose Saviolo, Kyliane Dong, Marco Matias, Stefano Lilipaly, Gavin Vlijter. 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 Clé in 2026?▼
Players with a similar profile to Clé in 2026 include Noah Jose Saviolo (N/A), Kyliane Dong (N/A), Marco Matias (N/A). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Clé play and who plays similarly?▼
Clé plays as a Attacker. Players with a comparable positional profile include Noah Jose Saviolo (Belgium, N/A); Kyliane Dong (France, N/A); Marco Matias (Portugal, N/A); Stefano Lilipaly (Indonesia, 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.