Best Alternatives to Ken Nkuba

Top 3 Alternatives to Ken Nkuba

1. 1.Willy Kambwala85% DNA match·Villarreal€4.0M
2. 2.Jordan Lotomba85% DNA match·Feyenoord€5.0M
3. 3.Jordan Zemura83% DNA match·Udinese€4.0M

Ranked by AI DNA similarity — 768 dimensions across playing style, pressing intensity, and tactical fit.

Playing Style Analysis

A Active Full-Back. Statistically, he stands out as an aggressive ball-winner (3.7 tackles/90), commanding in the air (4.0 clearances/90), wins the ball cleanly (2.6 successful tackles/90), central to possession (84 touches/90), active off the ball (2.7 press score/90), contributing to defensive transitions and top 10% tackler in the league. Note: this profile is based on 513 minutes of playing time this season. The three most similar players to Ken Nkuba by playing style are:

• Willy Kambwala(85% match) — A Ball-Playing CB. Statistically, he stands out as commanding in the air (4.3 clearances/90), meticulous in distribution (88% pass accuracy), wins the physical battle (56% duel success) and uses long balls frequently (6.5/90).
• Jordan Lotomba(85% match) — Lotomba is the kind of full-back who quietly does enough in five different departments without fully owning any of them—a profile that sounds damning until you look at the league context. His 88.5% pass accuracy lands in the top 30% of Eredivisie defenders, and his assist rate per 90 sits in the top 20%, suggesting a genuine threat in transition despite a dribble count that also cracks that same elite bracket. Here's the counterintuitive part: his suspiciously low passes-per-90 figure—bottom 10% in the league—likely reflects positional role and game state rather than technical limitation, given how clean his accuracy numbers are when he does receive.
• Jordan Zemura(83% match) — A Active Full-Back. Statistically, he stands out as naturally left-footed, a reliable supplier (0.19 assists/90), an aggressive ball-winner (2.7 tackles/90), reads the game exceptionally (1.7 interceptions/90), active off the ball (2.4 press score/90), contributing to defensive transitions and top 10% tackler in the league. However, he prone to committing fouls (2.7/90).

Similarity is calculated using per-90 performance data across multiple playing style dimensions. How Player DNA matching works →