⬡ AI DNA · Live season

Borussia Dortmund· 2025/2026 · Bundesliga · PARTIAL

Best Alternatives to Emre Can

Centre BackGermany32y€4.0MFull profile →

Ball-Playing CBBall-PlayingAerial

1.88Tkl/90

0.00KP/90

Based on 622 min · 2025/2026 · Bundesliga · PARTIAL

Ranked by AI DNA similarity — playing style, pressing, and tactical fit. Below: the closest replacements with per-90 stats and form.

DNA matchPrioritizes Bundesliga & top-tier peers

Top 3 alternatives to Emre Can

Ramy Bensebaini86% match
Borussia Dortmund · Bundesliga · €7.0M
Matthias Ginter85% match
SC Freiburg · Bundesliga · €6.0M
Eric Smith85% match
St. Pauli · Bundesliga · €5.0M

Ranked by RT Player DNA + league/value credibility. Scroll for full list, per-90 stats, and share cards.

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Playing Style Analysis

Ball-Playing CBBall-PlayingAerialSmall Sample

A Ball-Playing CB. Statistically, he stands out as a proven goalscorer (0.43 goals/90), active in the tackle (1.9 tackles/90), commanding in the air (5.2 clearances/90), reads the game exceptionally (2.3 interceptions/90), meticulous in distribution (86% pass accuracy), heavily involved in possession (65 passes/90), penetrates with forward passing (9.4 final-third passes/90), central to possession (84 touches/90), uses long balls frequently (7.1/90) and a high-intensity presser (press score 3.5/90), constantly disrupting opposition build-up. Note: this profile is based on 622 minutes of playing time this season. The three closest DNA matches to Emre Can:

Ramy Bensebaini(86% match) — A Ball-Playing CB. Statistically, he stands out as naturally left-footed, a regular goalscorer (0.29 goals/90), commanding in the air (5.0 clearances/90), meticulous in distribution (87% pass accuracy), wins the physical battle (55% duel success), heavily involved in possession (69 passes/90), penetrates with forward passing (12.0 final-third passes/90), central to possession (87 touches/90), uses long balls frequently (6.4/90) and active off the ball (2.5 press score/90), contributing to defensive transitions.
Matthias Ginter(85% match) — A Ball-Playing CB. Statistically, he stands out as commanding in the air (6.1 clearances/90), meticulous in distribution (88% pass accuracy), wins the physical battle (63% duel success), dominant in the air (3.4 aerials won/90, 62%) and uses long balls frequently (6.6/90).
Eric Smith(85% match) — A Ball-Playing CB. Statistically, he stands out as commanding in the air (4.1 clearances/90), wins the physical battle (58% duel success), penetrates with forward passing (9.5 final-third passes/90), central to possession (73 touches/90), uses long balls frequently (8.0/90) and active off the ball (2.6 press score/90), contributing to defensive transitions.

Similarity uses per-90 performance across playing-style dimensions. How Player DNA matching works →

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Similar Players — Ranked by DNA Similarity

Ramy Bensebaini

Borussia Dortmund · Bundesliga

Algeria31yContract 2027

Tkl/901.71

KP/900.59

Ball-Playing CBBall-PlayingIn form ↑

86% match

€7.0M

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Frequently Asked Questions

Who are the best alternatives to Emre Can?▼

The top alternatives to Emre Can based on AI DNA playing style analysis include: Ramy Bensebaini, Matthias Ginter, Eric Smith, Jan Elvedi, Ozan Kabak. 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 Emre Can in 2026?▼

Players with a similar profile to Emre Can in 2026 include Ramy Bensebaini (€7.0M), Matthias Ginter (€6.0M), Eric Smith (€5.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.

What position does Emre Can play and who plays similarly?▼

Emre Can plays as a Defender. Players with a comparable positional profile include Ramy Bensebaini (Algeria, €7.0M); Matthias Ginter (Germany, €6.0M); Eric Smith (Sweden, €5.0M); Jan Elvedi (Switzerland, €8.0M).

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.

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