Best Alternatives to Žan Jevšenak
Players most similar to Žan Jevšenak (Midfielder, €500K) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.
Top 3 Alternatives to Žan Jevšenak
- 1.Mark Brink99% DNA match·Nordsjælland
- 2.Kai Klefisch99% DNA match·Darmstadt 98
- 3.Magnus Saaby98% DNA match·Kolding IF
Ranked by AI DNA similarity — 768 dimensions across playing style, pressing intensity, and tactical fit.
Intelligence Verdict
“A Metronome....”
See Full Verdict + Share Card →Playing Style Analysis
A Metronome. Statistically, he stands out as meticulous in distribution (91% pass accuracy), wins the physical battle (60% duel success), heavily involved in play (66 touches/90) and active off the ball (2.3 press score/90), contributing to defensive transitions. The three most similar players to Žan Jevšenak by playing style are:
- Mark Brink(99% match) — A Metronome. Statistically, he stands out as meticulous in distribution (91% pass accuracy), heavily involved in possession (72 passes/90), central to possession (81 touches/90) and active off the ball (2.4 press score/90), contributing to defensive transitions.
- Kai Klefisch(99% match) — A Metronome. Statistically, he stands out as active in the tackle (1.9 tackles/90), meticulous in distribution (89% pass accuracy), wins the physical battle (58% duel success), heavily involved in possession (61 passes/90), central to possession (74 touches/90), uses long balls frequently (5.3/90) and active off the ball (2.7 press score/90), contributing to defensive transitions.
- Magnus Saaby(98% match) — A Metronome. Statistically, he stands out as a capable chance creator (1.2 key passes/90), reads the game exceptionally (1.9 interceptions/90), meticulous in distribution (87% pass accuracy), heavily involved in possession (63 passes/90), penetrates with forward passing (9.2 final-third passes/90), central to possession (79 touches/90) and active off the ball (2.6 press score/90), contributing to defensive transitions.
Similarity is calculated using per-90 performance data across multiple playing style dimensions. How Player DNA matching works →
Similar Players — Ranked by DNA Similarity
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