Best Alternatives to Maksym Taloverov

Top 3 Alternatives to Maksym Taloverov

1. 1.Malick Thiaw84% DNA match·Newcastle United€45.0M
2. 2.Montassar Talbi83% DNA match·Lorient€7.0M
3. 3.Jaka Bijol83% DNA match·Leeds United€18.0M

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

Playing Style Analysis

A Ball-Playing CB. Statistically, he stands out as an aggressive ball-winner (3.0 tackles/90), commanding in the air (6.2 clearances/90), wins the physical battle (62% duel success), central to possession (70 touches/90), uses long balls frequently (6.2/90), active off the ball (2.5 press score/90), contributing to defensive transitions and top 10% tackler in the league. The three most similar players to Maksym Taloverov by playing style are:

• Malick Thiaw(84% match) — Thiaw has quietly become one of the Premier League's most complete defensive profiles — a towering centre-back who doesn't just win his battles, he wins them cleanly. His aerial win rate of 65.1% and duel success of 64.2% both sit in the league's top 20%, but the counterintuitive story is his attacking output: 0.16 goals per 90 and 0.98 shots per 90 place him in the top 10% among defenders, suggesting a genuine threat from set-pieces that opponents routinely underestimate. His pass accuracy of 90.6% reflects a ball-player comfortable in possession-heavy systems, and his above-average delivery into the final third adds genuine build-up value.
• Montassar Talbi(83% match) — A Ball-Playing CB. Statistically, he stands out as commanding in the air (6.4 clearances/90), meticulous in distribution (92% pass accuracy) and wins the physical battle (64% duel success).
• Jaka Bijol(83% match) — A Ball-Playing CB. Statistically, he stands out as commanding in the air (7.0 clearances/90), meticulous in distribution (85% pass accuracy), wins the physical battle (56% duel success), strong in aerial duels (3.2 aerials won/90) and uses long balls frequently (6.3/90).

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