Best Alternatives to Matt Targett

Top 3 Alternatives to Matt Targett

1. 1.Kyle Walker-Peters87% DNA match·West Ham United€13.0M
2. 2.Calvin Bassey84% DNA match·Fulham€28.0M
3. 3.Luca Pellegrini85% DNA match·Lazio€3.5M

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

Playing Style Analysis

Targett operates as a specialized offensive outlet masquerading as a Championship fullback, functioning more as a progressive hub than a traditional defensive anchor. While his 82.8% pass accuracy suggests safety, the real story lies in his 8.48 passes into the final third per 90, placing him in the elite bracket of Tier C distributors. He is a statistical anomaly in front of goal; his 1.29 shots per 90 rank him in the top 5% of all league defenders, proving he isn’t just overlapping, but actively hunting for finishing opportunities. The three most similar players to Matt Targett by playing style are:

• Kyle Walker-Peters(87% match) — A Defender. Statistically, he stands out as an aggressive ball-winner (3.2 tackles/90), meticulous in distribution (86% pass accuracy), wins the physical battle (62% duel success), wins the ball cleanly (2.2 successful tackles/90), active off the ball (2.3 press score/90), contributing to defensive transitions and top 10% tackler in the league.
• Calvin Bassey(84% match) — A Ball-Playing CB. Statistically, he stands out as naturally left-footed, active in the tackle (2.2 tackles/90), meticulous in distribution (88% pass accuracy), wins the physical battle (61% duel success), heavily involved in possession (61 passes/90), central to possession (76 touches/90), uses long balls frequently (5.4/90) and active off the ball (2.2 press score/90), contributing to defensive transitions.
• Luca Pellegrini(85% match) — A Active Full-Back. Statistically, he stands out as naturally left-footed and active in the tackle (1.8 tackles/90). Note: this profile is based on 890 minutes of playing time this season.

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