Best Alternatives to Lukas Mai

Top 3 Alternatives to Lukas Mai

1. 1.Maximilian Wöber87% DNA match·Werder Bremen€3.0M
2. 2.Mats Köhlert87% DNA match·Brøndby IF
3. 3.Mads Bech Sørensen87% DNA match·FC Midtjylland

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

Playing Style Analysis

Lars Lukas Mai is a Ball-Playing CB. Progressive defender comfortable on the ball. Statistically, he stands out as an aggressive ball-winner (3.3 tackles/90), commanding in the air (4.6 clearances/90), meticulous in distribution (88% pass accuracy), wins the physical battle (68% duel success), heavily involved in possession (60 passes/90), central to possession (74 touches/90), dominant in the air (3.6 aerials won/90, 71%), uses long balls frequently (6.2/90) and top 10% tackler in the league. The three most similar players to Lukas Mai by playing style are:

• Maximilian Wöber(87% match) — A Ball-Playing CB. Statistically, he stands out as naturally left-footed, an aggressive ball-winner (2.9 tackles/90), commanding in the air (4.7 clearances/90), reads the game exceptionally (1.6 interceptions/90), wins the physical battle (60% duel success), heavily involved in possession (61 passes/90) and top 10% tackler in the league.
• Mats Köhlert(87% match) — A Ball-Playing CB. Statistically, he stands out as an elite creator (1.8 key passes/90), active in the tackle (2.3 tackles/90), meticulous in distribution (90% pass accuracy), wins the physical battle (59% duel success), central to possession (78 touches/90) and active off the ball (2.6 press score/90), contributing to defensive transitions.
• Mads Bech Sørensen(87% match) — Mads Bech Sørensen is a Ball-Playing CB. Progressive defender comfortable on the ball. Statistically, he stands out as commanding in the air (4.8 clearances/90), meticulous in distribution (88% pass accuracy), wins the physical battle (69% duel success), central to possession (72 touches/90) and uses long balls frequently (7.9/90).

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