RisingTransfers
AI DNA Similarity

Best Alternatives to Attila Szalai

Players most similar to Attila Szalai (Defender, €12.3M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Attila Szalai

  1. 1.Roland Sallai90% DNA match·Galatasaray€12.0M
  2. 2.Tiago Djaló86% DNA match·Beşiktaş€7.0M
  3. 3.Arseniy Batagov85% DNA match·Trabzonspor€11.0M

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

RT

Intelligence Verdict

ShotsTop 19%
???Bottom 5%

A Ball-Playing CB....

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Playing Style Analysis

Ball-Playing CBAerial

A Ball-Playing CB. Statistically, he stands out as commanding in the air (6.0 clearances/90), wins the physical battle (57% duel success), penetrates with forward passing (8.1 final-third passes/90) and uses long balls frequently (9.1/90). The three most similar players to Attila Szalai by playing style are:

  • Roland Sallai(90% match)Sallai is the rare defensive profile who makes opposing coaches nervous not because of what he stops, but because of what he starts. Playing in the Super Lig for a mid-tier side, he ranks in the top 10% for key passes among defenders—a number that quietly reframes his role entirely. His aerial dominance is genuine and elite, landing in the top 5% of the league, and his shot volume per 90 matches that same tier, suggesting a player who treats set-piece situations as offensive opportunities rather than survival exercises.
  • Tiago Djaló(86% match)Djaló has carved out a quietly compelling identity in the Super Lig: a centre-back who wins headers, reads danger, and occasionally finds the net—without ever pretending to be a ball-playing quarterback. His aerial numbers place him in the top 20% of defenders in the league, and his interception rate tells a similar story about positional intelligence rather than reactive scrambling. Here's the counterintuitive part: his low dribble and key pass figures look like limitations, but they actually reflect discipline—he doesn't force situations that aren't his to own.
  • Arseniy Batagov(85% match)A Ball-Playing CB. Statistically, he stands out as active in the tackle (1.8 tackles/90), commanding in the air (4.9 clearances/90), meticulous in distribution (89% pass accuracy), wins the physical battle (62% duel success), heavily involved in possession (63 passes/90), penetrates with forward passing (8.0 final-third passes/90), central to possession (77 touches/90), switches play with precision (8.8 long balls/90, 63% accuracy) and active off the ball (2.4 press score/90), contributing to defensive transitions.

Transfer Intelligence

Roland Sallai delivers 90% of the same playing style, with 1.79 tackles won per 90 at age 28.

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

A
Comparison Base
Attila Szalai
DefenderHungary€12.3M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
R
Roland Sallai
Galatasaray · Super Lig
Hungary28yContract 2028
Tkl/901.79
KP/900.88
Active Full-Back
Last 5: → Stable
90% match
€12.0M
#2
T
Tiago Djaló
Beşiktaş · Super Lig
Portugal26yContract 2028
Tkl/901.48
KP/900.25
Ball-Playing CBAerial
Last 5: ↑ Hot
vs Szalai: €5M cheaper · 2y younger
86% match
€7.0M
#3
A
Arseniy Batagov
Trabzonspor · Super Lig
Ukraine24yContract 2028
Tkl/901.82
KP/900.62
Ball-Playing CBBall-Playing
Last 5: ↓ Dip
vs Szalai: 4y younger
85% match
€11.0M
#4
M
Mateusz Wieteska
Kocaelispor · Super Lig
Poland29y
Tkl/901.50
KP/900.10
Ball-Playing CBBall-Playing
84% match
€5.0M
#5
A
Abdülkerim Bardakcı
Galatasaray · Super Lig
Turkey31yContract 2027
Tkl/901.45
KP/900.56
Ball-Playing CBBall-Playing
Last 5: ↓ Dip
84% match
€6.5M
#6
W
Willi Orbán
RB Leipzig · Bundesliga
Hungary33yContract 2027
Tkl/901.29
KP/900.39
Ball-Playing CBBall-Playing
Last 5: ↑ Hot
85% match
€6.0M
#7
M
Milan Škriniar
Fenerbahçe · Super Lig
Slovakia31yContract 2025
Tkl/901.74
KP/900.04
Ball-Playing CBBall-Playing
Last 5: ↓ Dip
84% match
€11.0M
#8
J
Josip Sutalo
Ajax · Eredivisie
Croatia26yContract 2028
Tkl/900.65
KP/900.05
Ball-Playing CBBall-Playing
Last 5: ↓ Dip
85% match
€17.0M
#9
K
Kike Salas
Sevilla · La Liga
Spain24yContract 2029
Tkl/902.08
KP/900.22
Ball-Playing CBBall-Playing
Last 5: → Stable
84% match
€6.0M
#10
Ü
Ümit Akdağ
Alanyaspor · Super Lig
Romania22yContract 2028
Tkl/901.24
KP/900.62
Ball-Playing CBAerial
Last 5: ↑ Hot
84% match
€4.0M
#11
D
Danilho Doekhi
FC Union Berlin · Bundesliga
Netherlands27yContract 2026
Tkl/901.00
KP/900.29
Physical StopperAerial
83% match
€13.0M
#12
M
Modibo Sagnan
Rizespor · Super Lig
France27y
Tkl/902.29
KP/900.25
Reading DefenderAerial Defender
Last 5: ↑ Hot
84% match
€3.2M

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 Attila Szalai.

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Frequently Asked Questions

Who are the best alternatives to Attila Szalai?
The top alternatives to Attila Szalai based on AI DNA playing style analysis include: Roland Sallai, Tiago Djaló, Arseniy Batagov, Mateusz Wieteska, Abdülkerim Bardakcı. 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 Attila Szalai in 2026?
Players with a similar profile to Attila Szalai in 2026 include Roland Sallai (€12.0M), Tiago Djaló (€7.0M), Arseniy Batagov (€11.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Attila Szalai play and who plays similarly?
Attila Szalai plays as a Defender. Players with a comparable positional profile include Roland Sallai (Hungary, €12.0M); Tiago Djaló (Portugal, €7.0M); Arseniy Batagov (Ukraine, €11.0M); Mateusz Wieteska (Poland, €5.0M).
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.