AI DNA Similarity
Best Alternatives to Aviel Zargari
Players most similar to Aviel Zargari (Midfielder, €485K) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.
Top 3 Alternatives to Aviel Zargari
- 1.Ivan Franjic98% DNA match·Wehen Wiesbaden
- 2.Michael Laffey98% DNA match·Liverpool
- 3.M. Rasmussen98% DNA match·HB Køge
Ranked by AI DNA similarity — 768 dimensions across playing style, pressing intensity, and tactical fit.
RT
Intelligence Verdict
???Bottom 0%
“A Midfielder....”
See Full Verdict + Share Card →Playing Style Analysis
Small Sample
A Midfielder. Note: this profile is based on 506 minutes of playing time this season. The three most similar players to Aviel Zargari by playing style are:
- Ivan Franjic(98% match) — A Midfielder. Note: this profile is based on 540 minutes of playing time this season.
- Michael Laffey(98% match) — A Midfielder. Note: this profile is based on 562 minutes of playing time this season.
- M. Rasmussen(98% match) — A Midfielder. Note: this profile is based on 882 minutes of playing time this season.
Similarity is calculated using per-90 performance data across multiple playing style dimensions. How Player DNA matching works →
Similar Players — Ranked by DNA Similarity
#1
I
Ivan Franjic
Wehen Wiesbaden · Bundesliga
Germany28y
KP/900.00
G/900.00
Small Sample
vs Zargari: 5y older
98% match
N/A
#2
M
Michael Laffey
Liverpool · Premier League
England20y
KP/900.19
G/900.00
Small Sample
vs Zargari: 3y younger
98% match
N/A
#3
M
M. Rasmussen
HB Køge · Superliga
Denmark20y
KP/900.71
G/900.00
Small Sample
vs Zargari: 3y younger
98% match
N/A
#4
L
Loret Sadiku
Kasımpaşa · Super Lig
34y
KP/900.39
G/900.00
Balanced MidfielderSmall Sample
96% match
N/A
#5
G
George Lawrence Hemmings
Aston Villa · Premier League
England19y
KP/900.80
G/900.00
Balanced MidfielderSmall Sample
96% match
N/A
#6
F
Frederik Brinch Møller
Kolding IF · Superliga
Denmark20y
KP/900.64
G/900.14
Balanced MidfielderSmall Sample
Last 5: → Stable95% match
N/A
#7
H
Hjalte Toftegaard
Hillerød · Superliga
Denmark19y
KP/903.52
G/900.00
Small Sample
95% match
N/A
#8
M
Mitchel Van Rosmalen
Blauw Geel '38 · Eredivisie
Netherlands24y
KP/900.72
G/900.00
Small Sample
95% match
N/A
#9
M
Marcel Wenig
Ulm · Bundesliga
Germany22yContract 2027
KP/900.00
G/900.17
Small Sample
94% match
N/A
#10
D
Diogo Ferreira Prioste
Benfica · Liga Portugal
Portugal22y
KP/901.18
G/900.00
Small Sample
94% match
N/A
#11
C
Callum Olusesi
Tottenham Hotspur · Premier League
England19y
KP/900.00
G/900.36
Small Sample
93% match
N/A
#12
J
Jakob Vester
Viborg FF · Superliga
Denmark21yContract 2027
KP/900.81
G/900.54
Small Sample
Last 5: ↑ Hot93% match
N/A
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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 Aviel Zargari.
Ask AI about Aviel Zargari →Frequently Asked Questions
Who are the best alternatives to Aviel Zargari?▼
The top alternatives to Aviel Zargari based on AI DNA playing style analysis include: Ivan Franjic, Michael Laffey, M. Rasmussen, Loret Sadiku, George Lawrence Hemmings. 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 Aviel Zargari in 2026?▼
Players with a similar profile to Aviel Zargari in 2026 include Ivan Franjic (N/A), Michael Laffey (N/A), M. Rasmussen (N/A). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Aviel Zargari play and who plays similarly?▼
Aviel Zargari plays as a Midfielder. Players with a comparable positional profile include Ivan Franjic (Germany, N/A); Michael Laffey (England, N/A); M. Rasmussen (Denmark, N/A); Loret Sadiku (, 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.