⬡ AI DNA · Live season

Borussia Mönchengladbach· 2025/2026 · Bundesliga · PARTIAL

Best Alternatives to Kevin Stöger

Attacking MidfieldAustria32y€3.0MFull profile →

CreatorCreativeDefensive

1.84KP/90

0.07G/90

0.07A/90

Based on 1,323 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 Kevin Stöger

Danel Sinani85% match
St. Pauli · Bundesliga · €3.0M
Andrej Kramaric84% match
TSG Hoffenheim · Bundesliga · €3.0M
Christian Eriksen84% match
VfL Wolfsburg · Bundesliga · €3.0M

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

CreatorCreativeDefensive

A Creator. Statistically, he stands out as naturally left-footed, an elite creator (1.8 key passes/90), an aggressive ball-winner (2.5 tackles/90), penetrates with forward passing (8.5 final-third passes/90), central to possession (74 touches/90), active off the ball (2.4 press score/90), contributing to defensive transitions, top 20% creator in the league and top 10% tackler in the league. The three closest DNA matches to Kevin Stöger:

Danel Sinani(85% match) — A Creator. Statistically, he stands out as naturally left-footed, an elite creator (2.0 key passes/90), a regular goalscorer (0.22 goals/90), heavily involved in play (61 touches/90), active off the ball (2.2 press score/90), contributing to defensive transitions and top 10% creator in the league.
Andrej Kramaric(84% match) — A Creator. Statistically, he stands out as a capable chance creator (1.5 key passes/90), a constant goal threat (2.6 shots/90), a proven goalscorer (0.57 goals/90), a reliable supplier (0.24 assists/90), meticulous in distribution (85% pass accuracy) and heavily involved in play (54 touches/90).
Christian Eriksen(84% match) — A Creator. Statistically, he stands out as an elite creator (2.4 key passes/90), a prolific assist provider (0.35 assists/90), creates high-quality scoring opportunities (0.58 big chances/90), penetrates with forward passing (8.0 final-third passes/90), heavily involved in play (61 touches/90), active off the ball (2.2 press score/90), contributing to defensive transitions and top 10% creator 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

Danel Sinani

St. Pauli · Bundesliga

Luxembourg29yContract 2026

KP/902.04

G/900.22

CreatorCreativeIn form ↑

vs Stöger: 3y younger

85% match

€3.0M

Compare Stöger vs Sinani →

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Same DNA shortlist as above — budget fit, who to avoid, or why the top match works.

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Frequently Asked Questions

Who are the best alternatives to Kevin Stöger?▼

The top alternatives to Kevin Stöger based on AI DNA playing style analysis include: Danel Sinani, Andrej Kramaric, Christian Eriksen, Jamal Musiala, Can Uzun. 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 Kevin Stöger in 2026?▼

Players with a similar profile to Kevin Stöger in 2026 include Danel Sinani (€3.0M), Andrej Kramaric (€3.0M), Christian Eriksen (€3.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.

What position does Kevin Stöger play and who plays similarly?▼

Kevin Stöger plays as a Midfielder. Players with a comparable positional profile include Danel Sinani (Luxembourg, €3.0M); Andrej Kramaric (Croatia, €3.0M); Christian Eriksen (Denmark, €3.0M); Jamal Musiala (Germany, €130.0M).

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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