⬡ AI DNA · Live season

Jeonbuk Motors· 2026 · K League 1 · PARTIAL

Best Alternatives to Wi-je Cho

Centre BackSouth Korea24yN/AFull profile →

Ball-Playing CBBall-PlayingAerial

2.26Tkl/90

0.11KP/90

Based on 1,066 min · 2026 · K League 1 · PARTIAL

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

Note: Top DNA style matches can come from lower leagues. We also surface K League 1 peers ranked by market value and league tier — scroll the full list below.

DNA matchDNA style match · see league & value below

Top 3 alternatives to Wi-je Cho

Peter Matiebel98% match
Hertha BSC II · Bundesliga
Claudio Kammerknecht97% match
Dynamo Dresden · Bundesliga
Niko Koulis

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Playing Style Analysis

Ball-Playing CBBall-PlayingAerial

A Ball-Playing CB. Statistically, he stands out as active in the tackle (1.9 tackles/90), commanding in the air (5.1 clearances/90), meticulous in distribution (88% pass accuracy), wins the physical battle (55% duel success), heavily involved in possession (65 passes/90), central to possession (78 touches/90), strong in aerial duels (3.6 aerials won/90) and uses long balls frequently (8.2/90). The three closest DNA matches to Wi-je Cho:

Peter Matiebel(98% match) — A Ball-Playing CB. Statistically, he stands out as an aggressive ball-winner (2.6 tackles/90), commanding in the air (5.1 clearances/90), meticulous in distribution (87% pass accuracy), central to possession (74 touches/90), uses long balls frequently (8.5/90) and top 10% tackler in the league.
Claudio Kammerknecht(97% match) — A Ball-Playing CB. Statistically, he stands out as an aggressive ball-winner (3.2 tackles/90), commanding in the air (6.8 clearances/90), meticulous in distribution (86% pass accuracy), wins the physical battle (70% duel success), heavily involved in possession (72 passes/90), penetrates with forward passing (10.1 final-third passes/90), central to possession (96 touches/90), strong in aerial duels (3.2 aerials won/90), uses long balls frequently (7.4/90), a high-intensity presser (press score 3.2/90), constantly disrupting opposition build-up and top 10% tackler in the league.
Niko Koulis(97% match) — A Ball-Playing CB. Statistically, he stands out as active in the tackle (1.9 tackles/90), commanding in the air (6.3 clearances/90), meticulous in distribution (90% pass accuracy) and wins the physical battle (58% duel success).

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

Comparison Base

Wi-je Cho

DefenderSouth KoreaK League 1N/A

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Similar Players — Ranked by DNA Similarity

Peter Matiebel

Hertha BSC II · Bundesliga

Germany21y

Tkl/902.50

KP/900.17

Ball-Playing CBBall-PlayingSteady form

vs Cho: 3y younger

98% match

N/A

Compare Cho vs Matiebel →

Ask about replacements for Cho

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 Wi-je Cho?▼

The top alternatives to Wi-je Cho based on AI DNA playing style analysis include: Peter Matiebel, Claudio Kammerknecht, Niko Koulis, Diego Coppola, João Silva. 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 Wi-je Cho in 2026?▼

Players with a similar profile to Wi-je Cho in 2026 include Peter Matiebel (N/A), Claudio Kammerknecht (N/A), Niko Koulis (N/A). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.

What position does Wi-je Cho play and who plays similarly?▼

Wi-je Cho plays as a Defender. Players with a comparable positional profile include Peter Matiebel (Germany, N/A); Claudio Kammerknecht (Germany, N/A); Niko Koulis (Germany, N/A); Diego Coppola (Italy, €11.0M).

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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