Best Alternatives to Federico Gatti

Top 3 Alternatives to Federico Gatti

1. 1.Bremer88% DNA match·Juventus€35.0M
2. 2.Giorgio Scalvini86% DNA match·Atalanta€25.0M
3. 3.Federico Baschirotto85% DNA match·Cremonese€4.0M

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

Playing Style Analysis

A Ball-Playing CB. Statistically, he stands out as a regular goalscorer (0.20 goals/90), commanding in the air (5.2 clearances/90), meticulous in distribution (91% pass accuracy), wins the physical battle (58% duel success), switches play with precision (5.2 long balls/90, 60% accuracy) and active off the ball (2.1 press score/90), contributing to defensive transitions. Note: this profile is based on 885 minutes of playing time this season. The three most similar players to Federico Gatti by playing style are:

• Bremer(88% match) — A Ball-Playing CB. Statistically, he stands out as a regular goalscorer (0.21 goals/90), meticulous in distribution (89% pass accuracy), wins the physical battle (61% duel success), dominant in the air (3.3 aerials won/90, 60%), uses long balls frequently (5.9/90) and active off the ball (2.2 press score/90), contributing to defensive transitions. Note: this profile is based on 875 minutes of playing time this season.
• Giorgio Scalvini(86% match) — A Ball-Playing CB. Statistically, he stands out as active in the tackle (2.1 tackles/90), commanding in the air (4.0 clearances/90), reads the game exceptionally (2.5 interceptions/90), meticulous in distribution (89% pass accuracy), central to possession (74 touches/90) and a high-intensity presser (press score 3.2/90), constantly disrupting opposition build-up. Note: this profile is based on 873 minutes of playing time this season.
• Federico Baschirotto(85% match) — A Ball-Playing CB. Statistically, he stands out as commanding in the air (6.8 clearances/90), meticulous in distribution (85% pass accuracy) and uses long balls frequently (6.0/90).

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