Best Alternatives to Mateusz Legowski

Top 3 Alternatives to Mateusz Legowski

1. 1.Alexandru Maxim86% DNA match·Gaziantep F.K.€3.0M
2. 2.Diogo Gonçalves85% DNA match·Konyaspor€3.0M
3. 3.Kacper Kozlowski85% DNA match·Gaziantep F.K.€5.0M

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

Playing Style Analysis

A Ball-Winner. The three most similar players to Mateusz Legowski by playing style are:

• Alexandru Maxim(86% match) — Maxim is the quintessential Super Lig puppet master, a high-volume creator who thrives on the edge of chaos for a Tier C side where he is the undisputed offensive heartbeat. While his team struggles for dominance, Maxim operates in a different stratosphere, ranking in the top 5% of the league for both key passes (3.15/90) and assists, proving he is not just a facilitator but a primary architect. His 7.43 passes into the final third place him in the elite bracket of progressive distributors, yet the counterintuitive reality of his profile lies in his physicality; despite a low volume of aerial duels, his 50% win rate suggests a player with high tactical intelligence in positioning rather than raw power.
• Diogo Gonçalves(85% match) — Gonçalves is a high-volume trigger-man operating as a sophisticated creative hub within a Tier-C Super Lig side that often struggles to match his vision. While his 83.3% pass accuracy suggests a safe distributor, the reality is far more aggressive; he ranks in the top 5% of the league for shots (2.69/90) and the top 20% for key passes, proving he is the primary engine of chance creation rather than a mere passenger. The counterintuitive insight lies in his dribbling: despite a modest 0.79/90, he is above the league average, suggesting he uses the carry to buy space for a killer ball rather than to beat a man for the sake of it.
• Kacper Kozlowski(85% match) — A Creator. Statistically, he stands out as a capable chance creator (1.2 key passes/90), a regular goalscorer (0.21 goals/90), draws fouls effectively (3.1/90) and active off the ball (2.0 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 →