⬡ AI DNA · Live season

FC Eindhoven· 2025/2026 · Eredivisie · PARTIAL

Best Alternatives to Dyon Dorenbosch

Central MidfieldNetherlands23yN/AFull profile →

Ball-WinnerDefensiveSmall Sample

0.67KP/90

0.00G/90

0.00A/90

Based on 884 min · 2025/2026 · Eredivisie · PARTIAL

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

DNA matchPrioritizes Eredivisie & top-tier peers

Top 3 alternatives to Dyon Dorenbosch

Merveille Papela99% match
Darmstadt 98 · Bundesliga
Obed Vargas99% match
Atlético Madrid · La Liga · €10.0M
Sem Scheperman98% match
Heracles Almelo · Eredivisie

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-WinnerDefensiveSmall Sample

A Ball-Winner. Statistically, he stands out as an aggressive ball-winner (3.2 tackles/90), wins the ball cleanly (1.8 successful tackles/90), heavily involved in play (52 touches/90), active off the ball (2.3 press score/90), contributing to defensive transitions and top 10% tackler in the league. Note: this profile is based on 884 minutes of playing time this season. The three closest DNA matches to Dyon Dorenbosch:

Merveille Papela(99% match) — A Balanced Midfielder. Statistically, he stands out as an aggressive ball-winner (2.8 tackles/90), heavily involved in play (52 touches/90), active off the ball (2.3 press score/90), contributing to defensive transitions and top 10% tackler in the league.
Obed Vargas(99% match) — A Ball-Winner. Statistically, he stands out as an aggressive ball-winner (3.2 tackles/90), wins the physical battle (68% duel success), wins the ball cleanly (1.9 successful tackles/90), heavily involved in play (54 touches/90), active off the ball (2.2 press score/90), contributing to defensive transitions and top 10% tackler in the league.
Sem Scheperman(98% match) — A Ball-Winner. Statistically, he stands out as an aggressive ball-winner (3.5 tackles/90), meticulous in distribution (86% pass accuracy), wins the physical battle (63% duel success), wins the ball cleanly (2.1 successful tackles/90), active off the ball (2.1 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

Merveille Papela

Darmstadt 98 · Bundesliga

Germany25y

KP/900.70

G/900.23

Balanced MidfielderDefensive

vs Dorenbosch: 2y older

99% match

N/A

Compare Dorenbosch vs Papela →

Ask about replacements for Dorenbosch

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

Knows 56,883 players. Knows 3,481 clubs.

Frequently Asked Questions

Who are the best alternatives to Dyon Dorenbosch?▼

The top alternatives to Dyon Dorenbosch based on AI DNA playing style analysis include: Merveille Papela, Obed Vargas, Sem Scheperman, Nick Fichtinger, Mohamed Fofana. 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 Dyon Dorenbosch in 2026?▼

Players with a similar profile to Dyon Dorenbosch in 2026 include Merveille Papela (N/A), Obed Vargas (€10.0M), Sem Scheperman (N/A). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.

What position does Dyon Dorenbosch play and who plays similarly?▼

Dyon Dorenbosch plays as a Midfielder. Players with a comparable positional profile include Merveille Papela (Germany, N/A); Obed Vargas (United States, €10.0M); Sem Scheperman (Netherlands, N/A); Nick Fichtinger (Netherlands, N/A).

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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