⬡ AI DNA · Live season

Feyenoord· 2025/2026 · Eredivisie · PARTIAL

Best Alternatives to In-beom Hwang

Defensive MidfieldSouth Korea29y€8.0MFull profile →

Box-to-BoxCreative

2.17KP/90

0.09G/90

0.27A/90

Based on 994 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 In-beom Hwang

Peer Koopmeiners84% match
AZ · Eredivisie · €10.0M
Ramiz Zerrouki83% match
FC Twente · Eredivisie · €7.2M
Youri Regeer82% match
Ajax · Eredivisie · €5.0M

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

Box-to-BoxCreative

A Box-to-Box. Statistically, he stands out as comfortable with both feet, an elite creator (2.2 key passes/90), a prolific assist provider (0.27 assists/90), wins the physical battle (57% duel success), creates high-quality scoring opportunities (0.54 big chances/90), heavily involved in play (67 touches/90), active off the ball (2.8 press score/90), contributing to defensive transitions and top 10% creator in the league. The three closest DNA matches to In-beom Hwang:

Peer Koopmeiners(84% match) — A Ball-Winner. Statistically, he stands out as a capable chance creator (1.0 key passes/90), an aggressive ball-winner (3.3 tackles/90), wins the ball cleanly (2.0 successful tackles/90), heavily involved in play (61 touches/90), active off the ball (2.6 press score/90), contributing to defensive transitions and top 10% tackler in the league.
Ramiz Zerrouki(83% match) — A Metronome. Statistically, he stands out as an elite creator (1.5 key passes/90), active in the tackle (2.2 tackles/90), penetrates with forward passing (11.6 final-third passes/90), central to possession (73 touches/90), switches play with precision (7.6 long balls/90, 63% accuracy) and active off the ball (2.8 press score/90), contributing to defensive transitions.
Youri Regeer(82% match) — A Ball-Winner. Statistically, he stands out as an aggressive ball-winner (2.8 tackles/90), meticulous in distribution (91% pass accuracy), wins the physical battle (62% duel success), heavily involved in play (70 touches/90) and a high-intensity presser (press score 3.0/90), constantly disrupting opposition build-up.

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

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Similar Players — Ranked by DNA Similarity

Peer Koopmeiners

AZ · Eredivisie

Netherlands26yContract 2028

KP/901.14

G/900.08

Ball-WinnerDefensiveIn form ↑

vs Hwang: 3y younger

84% match

€10.0M

Ask about replacements for Hwang

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 In-beom Hwang?▼

The top alternatives to In-beom Hwang based on AI DNA playing style analysis include: Peer Koopmeiners, Ramiz Zerrouki, Youri Regeer, Jorthy Mokio, Oussama Targhalline. 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 In-beom Hwang in 2026?▼

Players with a similar profile to In-beom Hwang in 2026 include Peer Koopmeiners (€10.0M), Ramiz Zerrouki (€7.2M), Youri Regeer (€5.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.

What position does In-beom Hwang play and who plays similarly?▼

In-beom Hwang plays as a Midfielder. Players with a comparable positional profile include Peer Koopmeiners (Netherlands, €10.0M); Ramiz Zerrouki (Algeria, €7.2M); Youri Regeer (Netherlands, €5.0M); Jorthy Mokio (Belgium, €8.0M).

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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