⬡ AI DNA · Live season

Werder Bremen· 2025/2026 · Bundesliga · PARTIAL

Best Alternatives to Marco Friedl

Centre BackAustria28y€12.0MFull profile →

Ball-Playing CBBall-PlayingAerial

1.55Tkl/90

0.18KP/90

Based on 2,548 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 Marco Friedl

Jonathan Tah80% match
FC Bayern München · Bundesliga · €30.0M
Min-jae Kim80% match
FC Bayern München · Bundesliga · €25.0M
Stefan Posch88% match
FSV Mainz 05 · Bundesliga · €5.5M

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-PlayingAerial

A Ball-Playing CB. Statistically, he stands out as naturally left-footed, commanding in the air (5.5 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 (8.8 final-third passes/90), central to possession (79 touches/90), uses long balls frequently (7.6/90) and active off the ball (2.3 press score/90), contributing to defensive transitions. The three closest DNA matches to Marco Friedl:

Jonathan Tah(80% match) — A Ball-Playing CB. Statistically, he stands out as commanding in the air (5.5 clearances/90), meticulous in distribution (96% pass accuracy), wins the physical battle (61% duel success), heavily involved in possession (85 passes/90), penetrates with forward passing (8.1 final-third passes/90), central to possession (97 touches/90) and active off the ball (2.2 press score/90), contributing to defensive transitions.
Min-jae Kim(80% match) — A Ball-Playing CB. Statistically, he stands out as commanding in the air (4.5 clearances/90), reads the game exceptionally (2.2 interceptions/90), meticulous in distribution (95% pass accuracy), wins the physical battle (63% duel success), heavily involved in possession (89 passes/90), penetrates with forward passing (9.4 final-third passes/90), central to possession (101 touches/90) and a high-intensity presser (press score 3.0/90), constantly disrupting opposition build-up.
Stefan Posch(88% match) — A Physical Stopper. Statistically, he stands out as an aggressive ball-winner (3.0 tackles/90), commanding in the air (5.7 clearances/90), wins the physical battle (64% duel success), penetrates with forward passing (8.1 final-third passes/90), uses long balls frequently (8.1/90), active off the ball (2.6 press score/90), contributing to defensive transitions and top 10% tackler in the league.

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

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Similar Players — Ranked by DNA Similarity

Jonathan Tah

FC Bayern München · Bundesliga

Germany30yContract 2029

Tkl/901.11

KP/900.22

Ball-Playing CBBall-PlayingOut of form ↓

vs Friedl: €18M more expensive · 2y older

80% match

€30.0M

Ask about replacements for Friedl

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Frequently Asked Questions

Who are the best alternatives to Marco Friedl?▼

The top alternatives to Marco Friedl based on AI DNA playing style analysis include: Jonathan Tah, Min-jae Kim, Stefan Posch, Finn Jeltsch, Daniel Elfadli. 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 Marco Friedl in 2026?▼

Players with a similar profile to Marco Friedl in 2026 include Jonathan Tah (€30.0M), Min-jae Kim (€25.0M), Stefan Posch (€5.5M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.

What position does Marco Friedl play and who plays similarly?▼

Marco Friedl plays as a Defender. Players with a comparable positional profile include Jonathan Tah (Germany, €30.0M); Min-jae Kim (South Korea, €25.0M); Stefan Posch (Austria, €5.5M); Finn Jeltsch (Germany, €25.0M).

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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