Best Alternatives to Andrew

Top 3 Alternatives to Andrew

1. 1.Jean Butez87% DNA match·Como€8.0M
2. 2.Emil Audero87% DNA match·Cremonese€3.2M
3. 3.Marco Carnesecchi86% DNA match·Atalanta€25.0M

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

Playing Style Analysis

A Reliable Keeper. Statistically, he stands out as dominant in aerial duels (100% success) and keeps goals out effectively (0.72 conceded/90). The three most similar players to Andrew by playing style are:

• Jean Butez(87% match) — Butez has carved out a quietly elite identity in Serie A as a goalkeeper who builds play with the conviction of a midfielder and dominates his aerial zone with uncommon authority. His 84.9% pass accuracy and 36.5 passes per 90 both land in the top 10% of Serie A keepers, meaning he isn't just tidy in possession—he's genuinely driving his team's build-up from the back. The aerial win rate sitting in the top 5% is the counterintuitive headline: raw numbers suggest an average volume of aerial duels won, but his 50% success rate against elite Serie A attackers tells a different story about physical dominance under pressure.
• Emil Audero(87% match) — A Sweeper-Keeper. Statistically, he stands out as dominant in aerial duels (100% success) and reliable in goal (3.5 saves/90).
• Marco Carnesecchi(86% match) — Carnesecchi has quietly built one of Serie A's most complete goalkeeping profiles without ever dominating a single headline statistic—which is, paradoxically, exactly what makes him interesting. His 30.9 passes per 90 sits above the league average, and a 68.6% accuracy rate suggests he's attempting ambitious distribution rather than recycling safe laterals—his passes into the final third rank above average, meaning he's actively functioning as a build-up participant rather than a reset button. The duel win rate of 91.7% lands at league average, which sounds unremarkable until you consider Atalanta's high defensive line routinely exposes keepers to one-versus-one situations most Serie A goalkeepers simply never face.

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