Best Alternatives to Khalis Merah

Top 3 Alternatives to Khalis Merah

1. 1.Diego Moreira85% DNA match·Strasbourg€18.0M
2. 2.Mahdi Camara86% DNA match·Rennes€10.0M
3. 3.Bilal Nadir85% DNA match·Olympique Marseille€9.0M

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

Playing Style Analysis

A Box-to-Box. Statistically, he stands out as an aggressive ball-winner (2.6 tackles/90), wins the physical battle (59% duel success), wins the ball cleanly (2.2 successful tackles/90), heavily involved in play (54 touches/90), draws fouls effectively (2.2/90) and active off the ball (2.1 press score/90), contributing to defensive transitions. However, he loses possession under pressure (1.9 dispossessed/90). The three most similar players to Khalis Merah by playing style are:

• Diego Moreira(85% match) — A Box-to-Box. Statistically, he stands out as naturally left-footed, an elite creator (1.7 key passes/90), a reliable supplier (0.21 assists/90), active in the tackle (2.1 tackles/90), creates high-quality scoring opportunities (0.53 big chances/90), heavily involved in play (65 touches/90), active off the ball (2.1 press score/90), contributing to defensive transitions and top 20% creator in the league.
• Mahdi Camara(86% match) — A Box-to-Box. Statistically, he stands out as active in the tackle (1.9 tackles/90), meticulous in distribution (86% pass accuracy) and heavily involved in play (54 touches/90).
• Bilal Nadir(85% match) — A Metronome. Statistically, he stands out as naturally left-footed, an elite creator (1.9 key passes/90), a prolific assist provider (0.70 assists/90), active in the tackle (2.5 tackles/90), meticulous in distribution (90% pass accuracy), creates high-quality scoring opportunities (0.53 big chances/90), central to possession (73 touches/90), active off the ball (2.6 press score/90), contributing to defensive transitions and top 10% creator in the league. However, he prone to committing fouls (3.9/90).

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