Best Alternatives to Lorenzo Pellegrini

Top 3 Alternatives to Lorenzo Pellegrini

1. 1.Nicolò Zaniolo85% DNA match·Udinese€13.0M
2. 2.Sandi Lovrić85% DNA match·Hellas Verona€6.0M
3. 3.Adrián Bernabé84% DNA match·Parma€15.0M

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

Playing Style Analysis

Pellegrini remains one of Serie A's most frustrating paradoxes: a midfielder who consistently breaks into the top 20% for both key passes and shots per 90, yet somehow still divides opinion at the highest level. His 1.71 key passes and 0.21 goals per 90 aren't volume illusions—they reflect a genuine capacity to hurt teams in ways most central midfielders simply can't. Here's the counterintuitive part: his below-average pass accuracy of 76.8% likely reflects ambition rather than sloppiness—he's attempting the difficult ball, the penetrating pass into the final third where he ranks in the top 30%. The three most similar players to Lorenzo Pellegrini by playing style are:

• Nicolò Zaniolo(85% match) — A Creator. Statistically, he stands out as an elite creator (2.7 key passes/90), a constant goal threat (2.9 shots/90), a regular goalscorer (0.21 goals/90), a reliable supplier (0.21 assists/90), heavily involved in play (50 touches/90), draws fouls effectively (2.3/90), active off the ball (2.0 press score/90), contributing to defensive transitions and top 10% creator in the league. However, he loses possession under pressure (2.5 dispossessed/90).
• Sandi Lovrić(85% match) — A Creator. Statistically, he stands out as a capable chance creator (1.2 key passes/90), active in the tackle (1.9 tackles/90), meticulous in distribution (85% pass accuracy), heavily involved in play (52 touches/90) and active off the ball (2.3 press score/90), contributing to defensive transitions.
• Adrián Bernabé(84% match) — A Creator. Statistically, he stands out as naturally left-footed, an elite creator (2.2 key passes/90), heavily involved in play (58 touches/90), draws fouls effectively (2.0/90) and top 10% creator in the league.

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