⬡ AI DNA · Live season

FC Volendam· 2025/2026 · Eredivisie · FULL

Best Alternatives to Gibson Yah

Defensive MidfieldNetherlands22yN/AFull profile →

Ball-WinnerDefensive

0.65KP/90

0.00G/90

0.16A/90

Based on 1,666 min · 2025/2026 · Eredivisie · FULL

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 Gibson Yah

Nick Fichtinger98% match
PEC Zwolle · Eredivisie
Jaygo van Ommeren97% match
FC Utrecht · Eredivisie
Sem Scheperman97% 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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Intelligence Verdict

Chances MissedTop 1%

???Bottom 25%

“A Ball-Winner....”

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Playing Style Analysis

Ball-WinnerDefensive

A Ball-Winner. Statistically, he stands out as a reliable supplier (0.16 assists/90), an aggressive ball-winner (3.6 tackles/90), reads the game exceptionally (1.7 interceptions/90), wins the physical battle (62% duel success), wins the ball cleanly (2.3 successful tackles/90), heavily involved in play (67 touches/90), a high-intensity presser (press score 3.5/90), constantly disrupting opposition build-up and top 10% tackler in the league. The three closest DNA matches to Gibson Yah:

Nick Fichtinger(98% match) — A Ball-Winner. Statistically, he stands out as an aggressive ball-winner (4.8 tackles/90), reads the game exceptionally (2.1 interceptions/90), wins the physical battle (58% duel success), wins the ball cleanly (2.9 successful tackles/90), heavily involved in play (57 touches/90), active off the ball (2.8 press score/90), contributing to defensive transitions and top 10% tackler in the league.
Jaygo van Ommeren(97% match) — A Ball-Winner. Statistically, he stands out as an aggressive ball-winner (3.3 tackles/90), reads the game exceptionally (1.9 interceptions/90), wins the ball cleanly (2.0 successful tackles/90), heavily involved in play (59 touches/90) and a high-intensity presser (press score 3.4/90), constantly disrupting opposition build-up.
Sem Scheperman(97% 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

Nick Fichtinger

PEC Zwolle · Eredivisie

Netherlands22yContract 2028

KP/900.36

G/900.00

Ball-WinnerDefensiveOut of form ↓

98% match

N/A

Compare Yah vs Fichtinger →

Ask about replacements for Yah

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 Gibson Yah?▼

The top alternatives to Gibson Yah based on AI DNA playing style analysis include: Nick Fichtinger, Jaygo van Ommeren, Sem Scheperman, Alonzo Engwanda, Dennis Dressel. 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 Gibson Yah in 2026?▼

Players with a similar profile to Gibson Yah in 2026 include Nick Fichtinger (N/A), Jaygo van Ommeren (N/A), 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 Gibson Yah play and who plays similarly?▼

Gibson Yah plays as a Midfielder. Players with a comparable positional profile include Nick Fichtinger (Netherlands, N/A); Jaygo van Ommeren (Netherlands, N/A); Sem Scheperman (Netherlands, N/A); Alonzo Engwanda (Belgium, 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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