AI DNA Similarity
Best Alternatives to Emad El-Sayed
Players most similar to Emad El-Sayed (Goalkeeper, €130K) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.
Top 3 Alternatives to Emad El-Sayed
- 1.Tommy Setford84% DNA match·Arsenal
- 2.Koen Bucker83% DNA match·FC Emmen
- 3.David Spinelli83% DNA match·Napoli
Ranked by AI DNA similarity — 768 dimensions across playing style, pressing intensity, and tactical fit.
RT
Intelligence Verdict
Goals ConcededTop 18%
???Bottom 0%
“Emad El Sayed is a Traditional Keeper....”
See Full Verdict + Share Card →Playing Style Analysis
Traditional Keeper
Emad El Sayed is a Traditional Keeper. Line-focused shot-stopper. The three most similar players to Emad El-Sayed by playing style are:
- Tommy Setford(84% match) — Tommy Hogan Setford is a Traditional Keeper. Line-focused shot-stopper. (Limited sample: 270 mins)
- Koen Bucker(83% match) — Koen Bucker is a Reliable Keeper. Consistent goalkeeper with a solid record. Statistically, he stands out as dominant in aerial duels (71% success) and keeps goals out effectively (0.33 conceded/90).
- David Spinelli(83% match) — David Spinelli is a Traditional Keeper. Line-focused shot-stopper. (Limited sample: 270 mins)
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
T
Tommy Setford
Arsenal · Premier League
England20y
Tkl/900.00
Traditional KeeperSmall Sample
vs El-Sayed: 20y younger
84% match
N/A
#2
K
Koen Bucker
FC Emmen · Eredivisie
Netherlands29y
Tkl/900.08
Reliable Keeper
vs El-Sayed: 11y younger
83% match
N/A
#3
D
David Spinelli
Napoli · Serie A
Italy18y
Tkl/900.00
Traditional KeeperSmall Sample
vs El-Sayed: 22y younger
83% match
N/A
#4
D
D. Dönmezer
Kayserispor · Super Lig
17y
Tkl/901.00
Traditional Keeper
82% match
N/A
#5
E
Edgar Badia
Cultural Leonesa · La Liga
Spain34y
Tkl/900.00
Reliable Keeper
82% match
N/A
#6
M
Mateus Pasinato
Cuiabá · Liga Portugal
Brazil33y
Tkl/900.00
Reliable Keeper
82% match
N/A
#7
T
Tim Coremans
FC Dordrecht · Eredivisie
Netherlands35y
Tkl/900.00
Traditional KeeperSmall Sample
83% match
N/A
#8
O
Okan Kocuk
Samsunspor · Super Lig
Turkey30yContract 2028
Tkl/900.07
Traditional Keeper
82% match
N/A
#9
U
Ubeyd Adiyaman
Ümraniyespor · Super Lig
Turkey28yContract 2025
Tkl/900.33
Traditional KeeperSmall Sample
82% match
N/A
#10
J
Joey Kesting
Katwijk · Eredivisie
Netherlands25y
Tkl/900.00
Traditional KeeperSmall Sample
82% match
N/A
#11
M
Mark De Vries
Katwijk · Eredivisie
Netherlands39y
Tkl/900.00
Traditional KeeperSmall Sample
82% match
N/A
#12
O
Oskar Snorre Olsen
Lyngby Boldklub · Superliga
Denmark27y
Tkl/900.00
Traditional Keeper
81% 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 Emad El-Sayed.
Ask AI about Emad El-Sayed →Frequently Asked Questions
Who are the best alternatives to Emad El-Sayed?▼
The top alternatives to Emad El-Sayed based on AI DNA playing style analysis include: Tommy Setford, Koen Bucker, David Spinelli, D. Dönmezer, Edgar Badia. 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 Emad El-Sayed in 2026?▼
Players with a similar profile to Emad El-Sayed in 2026 include Tommy Setford (N/A), Koen Bucker (N/A), David Spinelli (N/A). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Emad El-Sayed play and who plays similarly?▼
Emad El-Sayed plays as a Goalkeeper. Players with a comparable positional profile include Tommy Setford (England, N/A); Koen Bucker (Netherlands, N/A); David Spinelli (Italy, N/A); D. Dönmezer (, 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.