Best Alternatives to Mijat Gacinovic

Top 3 Alternatives to Mijat Gacinovic

1. 1.Sandi Lovrić84% DNA match·Hellas Verona€6.0M
2. 2.Filip Kostić85% DNA match·Juventus€3.5M
3. 3.Tomas Suslov83% DNA match·Hellas Verona€5.0M

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

Playing Style Analysis

Gacinovic functions as a disruptive defensive outlier trapped in the body of a struggling playmaker. While his 82.2% pass accuracy and low volume of distribution suggest a player out of his depth in possession, the data reveals a high-intensity ball-winner who reads the game with elite anticipation. His 1.58 interceptions per 90 place him in the top 10% of the league, a remarkable feat for a midfielder in a Tier C side, proving his spatial awareness far outstrips his technical execution. The three most similar players to Mijat Gacinovic by playing style are:

• Sandi Lovrić(84% 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.
• Filip Kostić(85% match) — A Creator. Statistically, he stands out as naturally left-footed, an elite creator (1.9 key passes/90), a proven goalscorer (0.59 goals/90), a reliable supplier (0.20 assists/90), an aggressive ball-winner (3.3 tackles/90), wins the physical battle (58% duel success), wins the ball cleanly (1.9 successful tackles/90), central to possession (77 touches/90), active off the ball (3.0 press score/90), contributing to defensive transitions, top 10% creator in the league and top 10% tackler in the league. Note: this profile is based on 461 minutes of playing time this season.
• Tomas Suslov(83% match) — A Creator. Statistically, he stands out as naturally left-footed, a capable chance creator (1.2 key passes/90), active in the tackle (2.4 tackles/90), draws fouls effectively (2.8/90) and active off the ball (2.0 press score/90), contributing to defensive transitions.

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