Best Alternatives to Martin Braithwaite

Top 3 Alternatives to Martin Braithwaite

1. 1.Idrissa Gueye83% DNA match·Udinese€4.0M
2. 2.Matija Frigan83% DNA match·Parma€7.5M
3. 3.Rasmus Højlund84% DNA match·Napoli€50.0M

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

Playing Style Analysis

Braithwaite remains football’s ultimate survivalist, a high-volume shot monster thriving within the tactical constraints of a Tier C Serie A outfit. While his 0.57 goals per ninety place him comfortably in the league’s top 20%, it is his sheer audacity to pull the trigger that defines him; ranking in the top 5% for shots per ninety, he operates with a "shoot on sight" mentality that borders on the obsessive. Counterintuitively, despite his reputation as a physical pest, his 42.7% duel win rate is underwhelming, suggesting he isn't a traditional target man but rather an opportunistic aerial predator who uses his top-30% aerial volume to disrupt rather than dominate. The three most similar players to Martin Braithwaite by playing style are:

• Idrissa Gueye(83% match) — A Target Man. Statistically, he stands out as a constant goal threat (2.6 shots/90), a regular goalscorer (0.39 goals/90) and strong in aerial duels (4.1 aerials won/90).
• Matija Frigan(83% match) — A Complete Forward. Statistically, he stands out as naturally left-footed, a constant goal threat (3.0 shots/90) and a proven goalscorer (0.44 goals/90).
• Rasmus Højlund(84% match) — Højlund arrived in Serie A carrying the blueprint of a modern target forward — raw, physical, and still being written. His goal return of 0.43 per 90 places him comfortably in the top 30% of Serie A attackers, a figure that flatters a player whose broader offensive contribution remains frustratingly thin. The counterintuitive read here is his aerial dominance: winning nearly half his aerial duels at above-average volume, he functions as a genuine aerial threat in a league that punishes soft strikers — yet his ground duel rate sits in the bottom 10%, exposing a player who struggles when the game drops to feet.

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