RisingTransfers
AI DNA Similarity

Best Alternatives to Semih Kılıçsoy

Players most similar to Semih Kılıçsoy (Attacker, €13.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Semih Kılıçsoy

  1. 1.Kenan Yıldız88% DNA match·Juventus€75.0M
  2. 2.Nikola Krstović85% DNA match·Atalanta€20.0M
  3. 3.Sandro Kulenovic85% DNA match·Torino€4.0M

Ranked by AI DNA similarity — 768 dimensions across playing style, pressing intensity, and tactical fit.

RT

Intelligence Verdict

Dribbled PastTop 0%
???Bottom 0%

A Poacher....

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Playing Style Analysis

PoacherProlificSmall Sample

A Poacher. Statistically, he stands out as a capable chance creator (1.1 key passes/90), a proven goalscorer (0.53 goals/90) and top 10% scorer in the league. However, he loses possession under pressure (2.7 dispossessed/90). The three most similar players to Semih Kılıçsoy by playing style are:

  • Kenan Yıldız(88% match)Yıldız has quietly become one of Serie A's most complete young attackers — a Turkish-German hybrid talent who combines the technical elegance of a playmaker with the directness of a genuine goalscorer. His 2.53 key passes per 90 rank top 10% among Serie A forwards, yet the number undersells him: he's also completing 38.4 passes per 90, suggesting a player who doesn't just create in bursts but sustains possession rhythms that most attackers simply ignore. His dribble rate sits in the top 5% of the division — counterintuitively, this isn't a flashy winger doing step-overs; it's a player beating defenders in tight spaces to manufacture better angles.
  • Nikola Krstović(85% match)Krstović has quietly become one of Serie A's most dangerous forwards this season, combining a striker's ruthlessness with a surprisingly complete technical game. His 0.63 goals per 90 places him in the top 10% of the league, but the more telling figure is his shot volume—top 5% in Serie A—suggesting a player who doesn't wait for perfect chances, he manufactures them. The counterintuitive story here is his passing: 79.9% accuracy and 1.49 key passes per 90 mark him as someone who links play intelligently, not just a poacher lurking on the last shoulder.
  • Sandro Kulenovic(85% match)A Complete Forward. Statistically, he stands out as a constant goal threat (3.7 shots/90), a proven goalscorer (1.07 goals/90), wins the physical battle (56% duel success), strong in aerial duels (3.0 aerials won/90) and top 10% scorer in the league. Note: this profile is based on 505 minutes of playing time this season.

Transfer Intelligence

Kenan Yıldız delivers 88% of the same playing style, at a 477% premium over Semih Kılıçsoy, with 0.18 goals per 90 at age 21. That's 33% of Semih Kılıçsoy's output in goals per 90 — a credible like-for-like option.

Similarity is calculated using per-90 performance data across multiple playing style dimensions. How Player DNA matching works →

S
Comparison Base
Semih Kılıçsoy
AttackerTurkey€13.0M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
K
Kenan Yıldız
Juventus · Serie A
Germany21yContract 2029
G/900.18
A/900.09
Link-Up Forward
Last 5: ↓ Dip
vs Kılıçsoy: €62M more expensive · -0.36 G/90
88% match
€75.0M
#2
N
Nikola Krstović
Atalanta · Serie A
Montenegro26yContract 2030
G/900.47
A/900.24
Goal ScorerHigh Volume Shooter
Last 5: ↓ Dip
vs Kılıçsoy: €7M more expensive · 6y older · -0.06 G/90
85% match
€20.0M
#3
S
Sandro Kulenovic
Torino · Serie A
Croatia26yContract 2027
G/900.37
A/900.37
Complete ForwardProlific
vs Kılıçsoy: €9M cheaper · 6y older · -0.17 G/90
85% match
€4.0M
#4
A
Ahmed Kutucu
Galatasaray · Super Lig
Turkey26yContract 2028
G/900.49
A/900.37
Inside ForwardProlific
83% match
€4.0M
#5
S
Santiago Castro
Bologna · Serie A
Argentina21yContract 2028
G/900.43
A/900.09
Last 5: ↓ Dip
84% match
€35.0M
#6
A
Anastasios Douvikas 
Como · Serie A
Greece26yContract 2029
G/900.67
A/900.00
PoacherProlific
Last 5: → Stable
84% match
€10.0M
#7
E
Ermedin Demirovic
VfB Stuttgart · Bundesliga
Bosnia and Herzegovina28yContract 2028
G/900.17
A/900.00
Target ManProlific
Last 5: ↑ Hot
83% match
€22.0M
#8
A
Ademola Lookman
Atlético Madrid · Serie A
Nigeria28yContract 2027
G/900.15
A/900.00
Inside ForwardSmall Sample
Last 5: ↑ Hot
84% match
€35.0M
#9
D
Donyell Malen
Roma · Serie A
Netherlands27yContract 2026
G/900.89
A/900.11
PoacherProlific
Last 5: → Stable
84% match
€25.0M
#10
E
Evan Ferguson
Roma · Serie A
Republic of Ireland21yContract 2026
G/900.34
A/900.17
Complete ForwardSmall Sample
83% match
€25.0M
#11
B
Benjamin Sesko
Manchester United · Premier League
Slovenia22yContract 2030
G/900.60
A/900.06
Target ManProlific
Last 5: → Stable
83% match
€65.0M
#12
K
Kamaldeen Sulemana
Atalanta · Serie A
Ghana24yContract 2029
G/900.21
A/900.21
Dynamic ForwardDribbler
Last 5: ↓ Dip
83% match
€18.0M

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 Semih Kılıçsoy.

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Frequently Asked Questions

Who are the best alternatives to Semih Kılıçsoy?
The top alternatives to Semih Kılıçsoy based on AI DNA playing style analysis include: Kenan Yıldız, Nikola Krstović, Sandro Kulenovic, Ahmed Kutucu, Santiago Castro. 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 Semih Kılıçsoy in 2026?
Players with a similar profile to Semih Kılıçsoy in 2026 include Kenan Yıldız (€75.0M), Nikola Krstović (€20.0M), Sandro Kulenovic (€4.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Semih Kılıçsoy play and who plays similarly?
Semih Kılıçsoy plays as a Attacker. Players with a comparable positional profile include Kenan Yıldız (Germany, €75.0M); Nikola Krstović (Montenegro, €20.0M); Sandro Kulenovic (Croatia, €4.0M); Ahmed Kutucu (Turkey, €4.0M).
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.