Best Alternatives to Héctor Herrera

Top 3 Alternatives to Héctor Herrera

1. 1.Matheus Uribe87% DNA match·Atlético Nacional€9.5M
2. 2.Damián Rodríguez87% DNA match·Celta de Vigo
3. 3.Jordan Holsgrove87% DNA match·Estoril

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

Playing Style Analysis

Héctor Miguel Herrera López is a Metronome. Possession anchor who dictates tempo. Statistically, he stands out as an elite creator (2.8 key passes/90), meticulous in distribution (91% pass accuracy), heavily involved in possession (95 passes/90), creates high-quality scoring opportunities (1.58 big chances/90) and top 10% creator in the league. The three most similar players to Héctor Herrera by playing style are:

• Matheus Uribe(87% match) — A Metronome. Statistically, he stands out as an aggressive ball-winner (2.7 tackles/90), reads the game exceptionally (1.9 interceptions/90), meticulous in distribution (85% pass accuracy), wins the physical battle (56% duel success) and heavily involved in possession (62 passes/90).
• Damián Rodríguez(87% match) — Damián Rodríguez Sousa is a Metronome. Possession anchor who dictates tempo. Statistically, he stands out as an elite creator (1.6 key passes/90), meticulous in distribution (92% pass accuracy), heavily involved in possession (75 passes/90), creates high-quality scoring opportunities (0.67 big chances/90) and central to possession (86 touches/90).
• Jordan Holsgrove(87% match) — A Metronome. Statistically, he stands out as an elite creator (1.8 key passes/90), a reliable supplier (0.23 assists/90), active in the tackle (1.9 tackles/90), meticulous in distribution (85% pass accuracy), heavily involved in possession (75 passes/90), penetrates with forward passing (12.6 final-third passes/90), central to possession (92 touches/90), uses long balls frequently (7.9/90), active off the ball (2.6 press score/90), contributing to defensive transitions and top 10% creator in the league.

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