RisingTransfers
AI DNA Similarity

Best Alternatives to Jovan Lukić

Players most similar to Jovan Lukić (Midfielder, €600K) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Jovan Lukić

  1. 1.Rocco Ascone98% DNA match·Nordsjælland
  2. 2.Sabil Hansen97% DNA match·Randers FC
  3. 3.Antonio Vergara97% DNA match·Napoli

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

RT

Intelligence Verdict

Press IntensityTop 12%

A Ball-Winner....

See Full Verdict + Share Card →

Playing Style Analysis

Ball-WinnerDefensiveSmall Sample

A Ball-Winner. Statistically, he stands out as a capable chance creator (1.5 key passes/90), an aggressive ball-winner (2.9 tackles/90), penetrates with forward passing (8.9 final-third passes/90), wins the ball cleanly (1.9 successful tackles/90), heavily involved in play (63 touches/90), active off the ball (2.9 press score/90), contributing to defensive transitions and top 10% tackler in the league. Note: this profile is based on 861 minutes of playing time this season. The three most similar players to Jovan Lukić by playing style are:

  • Rocco Ascone(98% match)A Ball-Winner. Statistically, he stands out as an elite creator (2.2 key passes/90), an aggressive ball-winner (5.5 tackles/90), wins the physical battle (60% duel success), wins the ball cleanly (2.8 successful tackles/90), central to possession (70 touches/90), uses long balls frequently (5.5/90), active off the ball (2.9 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 542 minutes of playing time this season.
  • Sabil Hansen(97% match)A Ball-Winner. Statistically, he stands out as an aggressive ball-winner (3.9 tackles/90), reads the game exceptionally (2.1 interceptions/90), wins the physical battle (56% duel success), wins the ball cleanly (2.1 successful tackles/90), central to possession (71 touches/90), active off the ball (2.9 press score/90), contributing to defensive transitions and top 10% tackler in the league.
  • Antonio Vergara(97% match)A Creator. Statistically, he stands out as a capable chance creator (1.5 key passes/90), a prolific assist provider (0.37 assists/90), active in the tackle (2.0 tackles/90), heavily involved in play (52 touches/90), draws fouls effectively (3.5/90) and active off the ball (2.7 press score/90), contributing to defensive transitions. However, he loses possession under pressure (2.6 dispossessed/90) and prone to committing fouls (2.8/90).

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

J
Comparison Base
Jovan Lukić
MidfielderSerbia€600K
Full profile →

Similar Players — Ranked by DNA Similarity

Ask AI: Why are these players similar?

Our 768-dimension Player DNA model matches playing style, physical profile, pressing intensity, and tactical fit. Ask the AI to explain exactly what makes these players statistically similar to Jovan Lukić.

Ask AI about Jovan Lukić

Frequently Asked Questions

Who are the best alternatives to Jovan Lukić?
The top alternatives to Jovan Lukić based on AI DNA playing style analysis include: Rocco Ascone, Sabil Hansen, Antonio Vergara, Celil Yüksel, Tyler Onyango. These players were matched using Rising Transfers' 768-dimension DNA model across playing style, pressing intensity, and tactical fit — not just position or market value.
Which players are similar to Jovan Lukić in 2026?
Players with a similar profile to Jovan Lukić in 2026 include Rocco Ascone (N/A), Sabil Hansen (N/A), Antonio Vergara (N/A). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Jovan Lukić play and who plays similarly?
Jovan Lukić plays as a Midfielder. Players with a comparable positional profile include Rocco Ascone (France, N/A); Sabil Hansen (Denmark, N/A); Antonio Vergara (Italy, N/A); Celil Yüksel (Turkey, N/A).
How does Rising Transfers find similar players?
Rising Transfers uses a proprietary 768-dimension Player DNA model trained on 3.2 million match events. Each player is represented as a vector across 35+ per-90 metrics including pressing intensity, passing footprint, dribbling profile, and defensive contribution. Similarity is measured using cosine distance — the same technique used in state-of-the-art AI systems — making it the most precise player comparison tool available publicly.