Best Alternatives to Kobbie Mainoo

Top 3 Alternatives to Kobbie Mainoo

1. 1.Manuel Ugarte86% DNA match·Manchester United€30.0M
2. 2.Oscar Højlund85% DNA match·Eintracht Frankfurt€7.5M
3. 3.Hannibal85% DNA match·Burnley€16.0M

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

Playing Style Analysis

A Metronome. Statistically, he stands out as a capable chance creator (1.2 key passes/90), active in the tackle (2.1 tackles/90), meticulous in distribution (90% pass accuracy), central to possession (74 touches/90) and active off the ball (2.8 press score/90), contributing to defensive transitions. However, he loses possession under pressure (1.6 dispossessed/90). The three most similar players to Kobbie Mainoo by playing style are:

• Manuel Ugarte(86% match) — A Ball-Winner. Statistically, he stands out as an aggressive ball-winner (4.7 tackles/90), reads the game exceptionally (2.2 interceptions/90), meticulous in distribution (85% pass accuracy), wins the physical battle (56% duel success), wins the ball cleanly (3.0 successful tackles/90), central to possession (71 touches/90), a high-intensity presser (press score 3.6/90), constantly disrupting opposition build-up and top 10% tackler in the league. Note: this profile is based on 887 minutes of playing time this season.
• Oscar Højlund(85% match) — A Balanced Midfielder. Statistically, he stands out as an aggressive ball-winner (2.6 tackles/90), meticulous in distribution (89% pass accuracy) and heavily involved in play (60 touches/90).
• Hannibal(85% match) — A Creator. Statistically, he stands out as an elite creator (1.6 key passes/90), a prolific assist provider (0.33 assists/90), active in the tackle (2.2 tackles/90), heavily involved in play (60 touches/90), draws fouls effectively (3.5/90), active off the ball (2.6 press score/90), contributing to defensive transitions and top 20% creator in the league. However, he loses possession under pressure (2.5 dispossessed/90).

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