Best Alternatives to Giovanni Di Lorenzo 

Top 3 Alternatives to Giovanni Di Lorenzo 

1. 1.Alessandro Zanoli87% DNA match·Udinese€5.0M
2. 2.Mathías Olivera87% DNA match·Napoli€15.0M
3. 3.Luca Ranieri85% DNA match·Fiorentina€7.0M

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

Playing Style Analysis

Di Lorenzo is the rare full-back who makes a back four feel like a possession unit—a defender whose passing range does more damage than most midfielders. Playing for a mid-table Serie A side, he sits in the top 10% of his position for both passes into the final third and shots per 90, numbers that reveal an attacking output quietly outpacing his surroundings. His 85.8% pass accuracy and 58.1 passes per 90 confirm he's the engine of build-up, not just a participant. The three most similar players to Giovanni Di Lorenzo  by playing style are:

• Alessandro Zanoli(87% match) — A Active Full-Back. Statistically, he stands out as a capable chance creator (1.1 key passes/90) and a reliable supplier (0.17 assists/90).
• Mathías Olivera(87% match) — A Active Full-Back. Statistically, he stands out as naturally left-footed, an aggressive ball-winner (2.9 tackles/90), meticulous in distribution (90% pass accuracy), wins the physical battle (65% duel success), heavily involved in possession (66 passes/90), central to possession (82 touches/90), active off the ball (2.5 press score/90), contributing to defensive transitions and top 10% tackler in the league.
• Luca Ranieri(85% match) — Ranieri is the kind of defender whose most dangerous weapon isn't a tackle or a header—it's a pass. Operating for a mid-tier Serie A side, he ranks in the top 5% of all defenders in the league for passes into the final third, averaging nearly eight per 90 minutes—a number that belongs to a playmaking midfielder, not a backline operator. His duel and tackle numbers sit above average, suggesting he's no passenger defensively, and his shots per 90 place him in the top 20%, hinting at genuine set-piece threat.

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