Best Alternatives to Samed Onur

Top 3 Alternatives to Samed Onur

1. 1.Onur Ergün92% DNA match·İstanbul Başakşehir
2. 2.Kaan Caliskaner88% DNA match·Saarbrücken
3. 3.Ömer Beyaz89% DNA match·İstanbul Başakşehir

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

Playing Style Analysis

A Ball-Winner. Statistically, he stands out as an elite creator (1.8 key passes/90), a reliable supplier (0.15 assists/90), active in the tackle (2.4 tackles/90), reads the game exceptionally (1.7 interceptions/90), penetrates with forward passing (10.3 final-third passes/90), central to possession (70 touches/90), draws fouls effectively (3.2/90), switches play with precision (6.1 long balls/90, 69% accuracy), a high-intensity presser (press score 3.1/90), constantly disrupting opposition build-up and top 20% creator in the league. Note: this profile is based on 594 minutes of playing time this season. The three most similar players to Samed Onur by playing style are:

• Onur Ergün(92% match) — A Ball-Winner. Statistically, he stands out as an aggressive ball-winner (2.8 tackles/90), reads the game exceptionally (1.9 interceptions/90), wins the physical battle (73% duel success), creates high-quality scoring opportunities (0.56 big chances/90) and heavily involved in play (56 touches/90).
• Kaan Caliskaner(88% match) — Kaan Caliskaner is a Ball-Winner. Aggressive midfielder who disrupts opponents. Statistically, he stands out as an elite creator (2.0 key passes/90), a reliable supplier (0.22 assists/90), active in the tackle (2.2 tackles/90), creates high-quality scoring opportunities (1.08 big chances/90) and top 20% creator in the league.
• Ömer Beyaz(89% match) — Ömer Faruk Beyaz is a Ball-Winner. Aggressive midfielder who disrupts opponents. Statistically, he stands out as a regular goalscorer (0.30 goals/90), a dynamic dribbler (2.1/90), an aggressive ball-winner (4.8 tackles/90), heavily involved in play (65 touches/90) and top 10% tackler in the league.

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