RisingTransfers
AI DNA Similarity

Best Alternatives to Ifet Djakovac

Players most similar to Ifet Djakovac (Midfielder, €1.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Ifet Djakovac

  1. 1.Kristijan Jakic87% DNA match·FC Augsburg€6.0M
  2. 2.Martin Baturina84% DNA match·Como€18.0M
  3. 3.Alexandru Maxim84% DNA match·Gaziantep F.K.€3.0M

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

RT

Intelligence Verdict

Press IntensityTop 0%
???Bottom 0%

A Balanced Midfielder....

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Playing Style Analysis

Balanced Midfielder

A Balanced Midfielder. Statistically, he stands out as a prolific assist provider (0.28 assists/90), active in the tackle (2.0 tackles/90), reads the game exceptionally (1.8 interceptions/90) and a high-intensity presser (press score 3.2/90), constantly disrupting opposition build-up. The three most similar players to Ifet Djakovac by playing style are:

  • Kristijan Jakic(87% 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.
  • Martin Baturina(84% match)A Creator. Statistically, he stands out as an elite creator (4.1 key passes/90), a proven goalscorer (0.51 goals/90), a prolific assist provider (0.31 assists/90), meticulous in distribution (88% pass accuracy), creates high-quality scoring opportunities (0.72 big chances/90), heavily involved in play (70 touches/90), draws fouls effectively (2.4/90), active off the ball (2.2 press score/90), contributing to defensive transitions and top 10% creator in the league. However, he loses possession under pressure (1.6 dispossessed/90).
  • Alexandru Maxim(84% match)Maxim is the quintessential Super Lig puppet master, a high-volume creator who thrives on the edge of chaos for a Tier C side where he is the undisputed offensive heartbeat. While his team struggles for dominance, Maxim operates in a different stratosphere, ranking in the top 5% of the league for both key passes (3.15/90) and assists, proving he is not just a facilitator but a primary architect. His 7.43 passes into the final third place him in the elite bracket of progressive distributors, yet the counterintuitive reality of his profile lies in his physicality; despite a low volume of aerial duels, his 50% win rate suggests a player with high tactical intelligence in positioning rather than raw power.

Transfer Intelligence

Kristijan Jakic delivers 87% of the same playing style, at a 500% premium over Ifet Djakovac, with 0.77 key passes per 90 at age 28.

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

I
Comparison Base
Ifet Djakovac
MidfielderSerbia€1.0M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
K
Kristijan Jakic
FC Augsburg · Bundesliga
Croatia28yContract 2028
KP/900.77
G/900.15
Ball-WinnerDefensive
Last 5: → Stable
87% match
€6.0M
#2
M
Martin Baturina
Como · Serie A
Croatia23yContract 2030
KP/904.11
G/900.51
CreatorCreative
Last 5: → Stable
vs Djakovac: €17M more expensive · 5y younger
84% match
€18.0M
#3
A
Alexandru Maxim
Gaziantep F.K. · Super Lig
Romania35y
KP/903.31
G/900.17
Box-to-BoxCreative
Last 5: → Stable
vs Djakovac: 7y older
84% match
€3.0M
#4
S
Sandi Lovrić
Hellas Verona · Serie A
Slovenia28yContract 2027
KP/900.94
G/900.00
Creator
83% match
€6.0M
#5
F
Florent Hadergjonaj
Alanyaspor · Super Lig
Kosovo31yContract 2027
KP/901.78
G/900.25
CreatorCreative
Last 5: → Stable
84% match
€5.0M
#6
T
Tomas Suslov
Hellas Verona · Serie A
Slovakia23yContract 2027
KP/900.48
G/900.00
Creator
Last 5: → Stable
83% match
€5.0M
#7
D
Danel Sinani
St. Pauli · Bundesliga
Luxembourg29y
KP/902.13
G/900.43
CreatorCreative
84% match
€3.0M
#8
I
Ilia Gruev
Leeds United · Premier League
Bulgaria26yContract 2027
KP/900.75
G/900.00
Ball-Winner
Last 5: ↓ Dip
83% match
€9.0M
#9
A
Alex Freeman
Villarreal · La Liga
United States21yContract 2025
Tkl/902.69
KP/900.00
Active Full-Back
Last 5: → Stable
82% match
€3.5M
#10
S
Saša Lukić
Fulham · Premier League
Serbia29yContract 2027
KP/901.48
G/900.06
Box-to-Box
Last 5: → Stable
83% match
€12.0M
#11
D
Diogo Gonçalves
Konyaspor · Super Lig
Portugal29yContract 2026
G/900.81
A/900.00
Left WingCreator
Last 5: → Stable
82% match
€3.0M
#12
Y
Yegor Yarmolyuk
Brentford · Premier League
Ukraine22yContract 2031
KP/900.56
G/900.04
Box-to-Box
Last 5: ↓ Dip
82% match
€25.0M

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 Ifet Djakovac.

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Frequently Asked Questions

Who are the best alternatives to Ifet Djakovac?
The top alternatives to Ifet Djakovac based on AI DNA playing style analysis include: Kristijan Jakic, Martin Baturina, Alexandru Maxim, Sandi Lovrić, Florent Hadergjonaj. 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 Ifet Djakovac in 2026?
Players with a similar profile to Ifet Djakovac in 2026 include Kristijan Jakic (€6.0M), Martin Baturina (€18.0M), Alexandru Maxim (€3.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Ifet Djakovac play and who plays similarly?
Ifet Djakovac plays as a Midfielder. Players with a comparable positional profile include Kristijan Jakic (Croatia, €6.0M); Martin Baturina (Croatia, €18.0M); Alexandru Maxim (Romania, €3.0M); Sandi Lovrić (Slovenia, €6.0M).
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.