Best Alternatives to Petar Stanic

Top 3 Alternatives to Petar Stanic

1. 1.Danel Sinani87% DNA match·St. Pauli€3.0M
2. 2.Kristijan Jakic85% DNA match·FC Augsburg€6.0M
3. 3.Saša Lukić85% DNA match·Fulham€12.0M

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

Playing Style Analysis

A Creator. Statistically, he stands out as an elite creator (2.3 key passes/90), a constant goal threat (2.6 shots/90), a proven goalscorer (0.64 goals/90), a reliable supplier (0.18 assists/90), meticulous in distribution (86% pass accuracy), heavily involved in play (51 touches/90), draws fouls effectively (2.1/90) and top 10% creator in the league. The three most similar players to Petar Stanic by playing style are:

• Danel Sinani(87% match) — A Creator. Statistically, he stands out as naturally left-footed, an elite creator (2.0 key passes/90), a regular goalscorer (0.25 goals/90), heavily involved in play (61 touches/90), active off the ball (2.1 press score/90), contributing to defensive transitions and top 10% creator in the league. However, he loses possession under pressure (1.6 dispossessed/90).
• Kristijan Jakic(85% match) — A Ball-Winner. Statistically, he stands out as an aggressive ball-winner (3.1 tackles/90), penetrates with forward passing (8.6 final-third passes/90), wins the ball cleanly (2.3 successful tackles/90), heavily involved in play (67 touches/90), uses long balls frequently (6.3/90), a high-intensity presser (press score 3.6/90), constantly disrupting opposition build-up and top 10% tackler in the league. Note: this profile is based on 470 minutes of playing time this season.
• Saša Lukić(85% match) — A Box-to-Box. Statistically, he stands out as a capable chance creator (1.5 key passes/90), active in the tackle (2.4 tackles/90), meticulous in distribution (85% pass accuracy), heavily involved in play (54 touches/90) and active off the ball (2.1 press score/90), contributing to defensive transitions. However, he prone to committing fouls (2.7/90).

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