⬡ AI DNA · Live season

FC Volendam· 2025/2026 · Eredivisie · FULL

Best Alternatives to Nordin Bukala

Central MidfieldNetherlands20yN/AFull profile →

Ball-WinnerDefensive

0.41KP/90

0.10G/90

0.05A/90

Based on 1,751 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 Nordin Bukala

Philip Brittijn99% match
Fortuna Sittard · Eredivisie
Marcelencio Esajas99% match
TOP Oss · Eredivisie
Alonzo Engwanda98% match
FC Utrecht · 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

Tackles WonTop 11%

???Bottom 16%

“A Ball-Winner....”

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Playing Style Analysis

Ball-WinnerDefensive

A Ball-Winner. Statistically, he stands out as an aggressive ball-winner (3.1 tackles/90), reads the game exceptionally (1.6 interceptions/90), wins the physical battle (56% duel success), wins the ball cleanly (1.9 successful tackles/90), active off the ball (2.6 press score/90), contributing to defensive transitions and top 10% tackler in the league. The three closest DNA matches to Nordin Bukala:

Philip Brittijn(99% match) — A Balanced Midfielder. Statistically, he stands out as an aggressive ball-winner (2.6 tackles/90), reads the game exceptionally (1.7 interceptions/90) and active off the ball (2.7 press score/90), contributing to defensive transitions.
Marcelencio Esajas(99% match) — A Ball-Winner. Statistically, he stands out as an aggressive ball-winner (2.8 tackles/90), reads the game exceptionally (2.3 interceptions/90), wins the ball cleanly (2.0 successful tackles/90), heavily involved in play (51 touches/90), active off the ball (2.9 press score/90), contributing to defensive transitions and top 10% tackler in the league.
Alonzo Engwanda(98% match) — A Ball-Winner. Statistically, he stands out as an aggressive ball-winner (2.9 tackles/90), reads the game exceptionally (1.8 interceptions/90), meticulous in distribution (87% pass accuracy), wins the physical battle (60% duel success), wins the ball cleanly (1.9 successful tackles/90), heavily involved in play (51 touches/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

Philip Brittijn

Fortuna Sittard · Eredivisie

Netherlands22yContract 2028

KP/900.49

G/900.15

Balanced MidfielderDefensiveIn form ↑

vs Bukala: 2y older

99% match

N/A

Ask about replacements for Bukala

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 Nordin Bukala?▼

The top alternatives to Nordin Bukala based on AI DNA playing style analysis include: Philip Brittijn, Marcelencio Esajas, Alonzo Engwanda, Jaygo van Ommeren, Adam Carlén. 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 Nordin Bukala in 2026?▼

Players with a similar profile to Nordin Bukala in 2026 include Philip Brittijn (N/A), Marcelencio Esajas (N/A), Alonzo Engwanda (N/A). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.

What position does Nordin Bukala play and who plays similarly?▼

Nordin Bukala plays as a Midfielder. Players with a comparable positional profile include Philip Brittijn (Netherlands, N/A); Marcelencio Esajas (Netherlands, N/A); Alonzo Engwanda (Belgium, N/A); Jaygo van Ommeren (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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