Best Alternatives to Bartosz Salamon

Top 3 Alternatives to Bartosz Salamon

1. 1.Roland Sallai83% DNA match·Galatasaray€12.0M
2. 2.Sebastian Walukiewicz83% DNA match·Sassuolo€4.5M
3. 3.Attila Szalai84% DNA match·TSG Hoffenheim€12.3M

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

Playing Style Analysis

Salamon is the Ekstraklasa’s quintessential high-volume progressive hub, a towering presence who dictates play with the frequency of a deep-lying playmaker despite occupying the heart of the defense. Ranking in the top 5% for passes per 90 (65.4), he is the undisputed gravitational center of his team's build-up, though his efficiency is a paradox; he sits in the elite 5% for aerials won per 90 (3.70) yet maintains a surprisingly low win percentage in those duels, suggesting he is a magnet for long balls rather than a dominant physical force. This high-activity, low-efficiency profile is his primary risk, as his below-average pass accuracy often negates the tactical advantage of his league-leading volume. The three most similar players to Bartosz Salamon by playing style are:

• Roland Sallai(83% 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.
• Sebastian Walukiewicz(83% match) — A Defender.
• Attila Szalai(84% match) — 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).

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