Best Alternatives to Mauricio Lemos

Top 3 Alternatives to Mauricio Lemos

1. 1.Leonardo Lelo85% DNA match·Sporting Braga€8.0M
2. 2.Carlos Domínguez85% DNA match·Celta de Vigo€3.0M
3. 3.Gaspar84% DNA match·Lecce€3.5M

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

Playing Style Analysis

Lemos is a ball-dominant defensive sentinel whose elite spatial awareness allows him to dismantle opposition attacks before they materialize. While operating in a Tier C side, he manages to dictate tempo with 55.3 passes per 90—placing him in the league’s top 20% for volume—yet it is his defensive anticipation that defines his profile. His 1.97 interceptions per 90 rank him in the top 10% of Serie A defenders, proving he is a proactive reader of the game rather than a reactive tackler. The three most similar players to Mauricio Lemos by playing style are:

• Leonardo Lelo(85% match) — A Active Full-Back. Statistically, he stands out as naturally left-footed, an elite creator (2.0 key passes/90), a reliable supplier (0.21 assists/90), wins the physical battle (55% duel success), central to possession (78 touches/90) and active off the ball (2.2 press score/90), contributing to defensive transitions.
• Carlos Domínguez(85% match) — A Ball-Playing CB. Statistically, he stands out as naturally left-footed, active in the tackle (2.2 tackles/90), commanding in the air (6.5 clearances/90), meticulous in distribution (91% pass accuracy), wins the physical battle (66% duel success), heavily involved in possession (65 passes/90), central to possession (80 touches/90), uses long balls frequently (5.8/90) and active off the ball (2.2 press score/90), contributing to defensive transitions. Note: this profile is based on 524 minutes of playing time this season.
• Gaspar(84% match) — A Ball-Playing CB. Statistically, he stands out as commanding in the air (7.3 clearances/90), meticulous in distribution (85% pass accuracy) and wins the physical battle (60% duel success).

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