Best Alternatives to Paulos Abraham

Top 3 Alternatives to Paulos Abraham

1. 1.Tammy Abraham85% DNA match·Aston Villa€14.0M
2. 2.Fisnik Asllani84% DNA match·TSG Hoffenheim€30.0M
3. 3.Tim Kleindienst82% DNA match·Borussia Mönchengladbach€12.0M

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

Playing Style Analysis

Abraham is a multifaceted offensive engine operating with a technical refinement that belies the typical "Tier C" Allsvenskan environment. While his 0.40 goals per 90 marks him as a reliable finisher, his true value lies in his elite creative output; his assists per 90 place him in the top 5% of the league, suggesting a playmaker’s brain trapped in a striker’s frame. The counterintuitive reality of his profile is his aerial prowess; despite not being a traditional target man, his 46.7% aerial win rate puts him in the top quintile of the league, making him a deceptive threat on second balls and set pieces. The three most similar players to Paulos Abraham by playing style are:

• Tammy Abraham(85% match) — A Target Man. Statistically, he stands out as a capable chance creator (1.2 key passes/90), a regular goalscorer (0.23 goals/90) and a prolific assist provider (0.31 assists/90).
• Fisnik Asllani(84% match) — A Complete Forward. Statistically, he stands out as comfortable with both feet, an elite creator (1.6 key passes/90), a constant goal threat (2.6 shots/90), a regular goalscorer (0.20 goals/90), a prolific assist provider (0.40 assists/90) and creates high-quality scoring opportunities (0.60 big chances/90). Note: this profile is based on 450 minutes of playing time this season.
• Tim Kleindienst(82% match) — A Target Man. Statistically, he stands out as comfortable with both feet, a proven goalscorer (0.52 goals/90), a reliable supplier (0.23 assists/90), creates high-quality scoring opportunities (0.52 big chances/90), dominant in the air (4.9 aerials won/90, 60%) and top 20% scorer in the league.

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