RisingTransfers
AI DNA Similarity

Best Alternatives to Omar Fayed

Players most similar to Omar Fayed (Defender, N/A) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Omar Fayed

  1. 1.Claudio Kammerknecht99% DNA match·Dynamo Dresden
  2. 2.Dylan Timber99% DNA match·VVV-Venlo
  3. 3.V. Sørensen99% DNA match·HB Køge

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

RT

Intelligence Verdict

Chances MissedTop 0%
???Bottom 0%

A Ball-Playing CB....

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Playing Style Analysis

Ball-Playing CBBall-PlayingAerialSmall Sample

A Ball-Playing CB. Statistically, he stands out as an aggressive ball-winner (3.5 tackles/90), commanding in the air (4.5 clearances/90), reads the game exceptionally (2.0 interceptions/90), meticulous in distribution (88% pass accuracy), wins the physical battle (65% duel success), wins the ball cleanly (2.0 successful tackles/90), central to possession (73 touches/90), uses long balls frequently (7.5/90), a high-intensity presser (press score 3.0/90), constantly disrupting opposition build-up and top 10% tackler in the league. Note: this profile is based on 494 minutes of playing time this season. The three most similar players to Omar Fayed by playing style are:

  • Claudio Kammerknecht(99% match)A Ball-Playing CB. Statistically, he stands out as an aggressive ball-winner (3.2 tackles/90), commanding in the air (6.6 clearances/90), meticulous in distribution (86% pass accuracy), wins the physical battle (71% duel success), heavily involved in possession (73 passes/90), penetrates with forward passing (10.1 final-third passes/90), central to possession (96 touches/90), strong in aerial duels (3.2 aerials won/90), uses long balls frequently (7.3/90), a high-intensity presser (press score 3.2/90), constantly disrupting opposition build-up and top 10% tackler in the league. Note: this profile is based on 533 minutes of playing time this season.
  • Dylan Timber(99% match)A Ball-Playing CB. Statistically, he stands out as an aggressive ball-winner (3.1 tackles/90), commanding in the air (4.1 clearances/90), reads the game exceptionally (2.4 interceptions/90), meticulous in distribution (87% pass accuracy), wins the physical battle (60% duel success) and top 10% tackler in the league. Note: this profile is based on 707 minutes of playing time this season.
  • V. Sørensen(99% match)A Physical Stopper. Statistically, he stands out as an aggressive ball-winner (3.2 tackles/90), reads the game exceptionally (1.6 interceptions/90), wins the physical battle (59% duel success), wins the ball cleanly (1.9 successful tackles/90), uses long balls frequently (6.3/90), a high-intensity presser (press score 3.1/90), constantly disrupting opposition build-up and top 10% tackler in the league.

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

O
Comparison Base
Omar Fayed
DefenderEgyptN/A
Full profile →

Similar Players — Ranked by DNA Similarity

#1
C
Claudio Kammerknecht
Dynamo Dresden · Bundesliga
Germany26yContract 2026
Tkl/903.84
KP/900.27
Ball-Playing CBBall-Playing
vs Fayed: 4y older
99% match
N/A
#2
D
Dylan Timber
VVV-Venlo · Eredivisie
Netherlands26yContract 2026
Tkl/903.14
KP/900.18
Ball-Playing CBBall-Playing
Last 5: ↓ Dip
vs Fayed: 4y older
99% match
N/A
#3
V
V. Sørensen
HB Køge · Superliga
Denmark19y
Tkl/903.77
KP/900.22
Physical Stopper
Last 5: → Stable
vs Fayed: 3y younger
99% match
N/A
#4
M
Magnus Døj
Kolding IF · Superliga
Denmark20y
Tkl/902.36
KP/900.54
Ball-Playing CBAerial
Last 5: → Stable
99% match
N/A
#5
G
Gustav Bjerge
Hobro · Superliga
Denmark20y
Tkl/901.25
KP/900.42
Ball-Playing CBBall-Playing
Last 5: ↑ Hot
99% match
N/A
#6
S
Stephen Acquah
Nordsjælland · Superliga
Ghana20yContract 2029
Tkl/901.67
KP/900.00
Ball-Playing CBBall-Playing
Last 5: ↑ Hot
99% match
N/A
#7
J
João Afonso
Tondela · Liga Portugal
Portugal35yContract 2026
Tkl/901.95
KP/900.00
Physical StopperAerial
Last 5: ↑ Hot
99% match
N/A
#8
T
Tijn Joosten
VVV-Venlo · Eredivisie
Netherlands19y
Tkl/900.45
KP/900.45
Ball-Playing CBBall-Playing
Last 5: ↑ Hot
98% match
N/A
#9
Y
Yaya Bojang
Odense BK · Superliga
Gambia21yContract 2027
Tkl/903.97
KP/900.20
Ball-Playing CBBall-Playing
Last 5: ↓ Dip
98% match
N/A
#10
L
Laurits Bust
HB Køge · Superliga
Denmark27y
Tkl/902.33
KP/901.00
Ball-Playing CBAerial
Last 5: ↓ Dip
98% match
N/A
#11
B
Bahadır Öztürk
Antalyaspor · Super Lig
Turkey30yContract 2026
Tkl/901.06
KP/900.00
Ball-Playing CBAerial
Last 5: → Stable
98% match
N/A
#12
P
Philip Søndergaard
Brøndby IF · Superliga
Denmark19y
Tkl/901.90
KP/900.38
Ball-Playing CBAerial
Last 5: ↑ Hot
98% match
N/A

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 Omar Fayed.

Ask AI about Omar Fayed

Frequently Asked Questions

Who are the best alternatives to Omar Fayed?
The top alternatives to Omar Fayed based on AI DNA playing style analysis include: Claudio Kammerknecht, Dylan Timber, V. Sørensen, Magnus Døj, Gustav Bjerge. 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 Omar Fayed in 2026?
Players with a similar profile to Omar Fayed in 2026 include Claudio Kammerknecht (N/A), Dylan Timber (N/A), V. Sørensen (N/A). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Omar Fayed play and who plays similarly?
Omar Fayed plays as a Defender. Players with a comparable positional profile include Claudio Kammerknecht (Germany, N/A); Dylan Timber (Netherlands, N/A); V. Sørensen (Denmark, N/A); Magnus Døj (Denmark, 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.