Best Alternatives to Fally Mayulu

Top 3 Alternatives to Fally Mayulu

1. 1.Yassir Zabiri86% DNA match·Rennes€4.0M
2. 2.Lucas João86% DNA match·Nacional€5.4M
3. 3.Samu Aghehowa85% DNA match·Porto€45.0M

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

Playing Style Analysis

Mayulu is a high-volume shot monster currently masking a developmental deficit through pure, cold-blooded efficiency in front of goal. While his 0.56 goals per 90 puts him in the elite top 5% of Liga Portugal strikers, the underlying metrics paint a picture of a player who is essentially a passenger until the ball enters the box. He dominates the air with 3.07 aerials won per 90—again, top-tier production—yet his 33.3% win rate suggests he is simply contesting everything rather than winning with authority. The three most similar players to Fally Mayulu by playing style are:

• Yassir Zabiri(86% match) — A Poacher. Statistically, he stands out as a capable chance creator (1.2 key passes/90), a constant goal threat (3.4 shots/90), a proven goalscorer (0.55 goals/90) and top 20% scorer in the league. Note: this profile is based on 660 minutes of playing time this season.
• Lucas João(86% match) — João is a blunt instrument in the best possible sense — a physical presence in Liga Portugal who makes his mark not through elegance but through sheer aerial dominance and shot volume. His 3.84 aerial wins per 90 place him in the top 5% of attackers in the league, and his shots per 90 rank in the top 10% — numbers that tell you exactly what kind of threat he poses. The counterintuitive detail: his 50% pass accuracy looks damning until you realise it partly reflects how often he's operating in congested, high-pressure zones rather than recycling possession safely.
• Samu Aghehowa(85% match) — A Poacher. Statistically, he stands out as a constant goal threat (3.6 shots/90), a proven goalscorer (0.83 goals/90) and top 10% scorer in the league. However, he loses possession under pressure (1.6 dispossessed/90).

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