Best Alternatives to Andrés Guardado

Top 3 Alternatives to Andrés Guardado

1. 1.Marc Aguado82% DNA match·Elche€3.0M
2. 2.Pol Lozano82% DNA match·Espanyol€6.0M
3. 3.Sergio Lozano81% DNA match·Levante€6.0M

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

Playing Style Analysis

Guardado is a legendary Mexican general currently navigating the twilight of a storied career, transitioning from a European metronome to a localized veteran presence in Liga MX. The data suggests a player whose physical profile is rapidly receding; his 33.3% duel win rate and bottom-decile press intensity indicate he can no longer be trusted to anchor a midfield or hunt the ball in high-octane transitions. While an 81.0% pass accuracy appears underwhelming, the counterintuitive reality is that he remains a progressive risk-taker, sitting in the top 20% for successful dribbles as he attempts to manipulate space that his legs can no longer conquer through sheer speed. The three most similar players to Andrés Guardado by playing style are:

• Marc Aguado(82% match) — A Ball-Winner. Statistically, he stands out as active in the tackle (1.9 tackles/90), reads the game exceptionally (1.8 interceptions/90), meticulous in distribution (91% pass accuracy), wins the physical battle (63% duel success), heavily involved in play (57 touches/90) and active off the ball (2.2 press score/90), contributing to defensive transitions.
• Pol Lozano(82% match) — A Balanced Midfielder. Statistically, he stands out as meticulous in distribution (87% pass accuracy). However, he prone to committing fouls (3.0/90).
• Sergio Lozano(81% match) — A Ball-Winner. Statistically, he stands out as an elite creator (2.0 key passes/90), a prolific assist provider (0.25 assists/90), an aggressive ball-winner (2.5 tackles/90), creates high-quality scoring opportunities (0.84 big chances/90), heavily involved in play (69 touches/90), draws fouls effectively (2.3/90) and top 10% creator in the league. However, he prone to committing fouls (3.5/90).

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