Best Alternatives to Yaw Ackah
Players most similar to Yaw Ackah (Midfielder, N/A) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.
Top 3 Alternatives to Yaw Ackah
- 1.Xander Blomme87% DNA match·FC Eindhoven
- 2.Mart Ristl86% DNA match·Homburg
- 3.Frederik Lauenborg86% DNA match·Randers FC
Ranked by AI DNA similarity — 768 dimensions across playing style, pressing intensity, and tactical fit.
Intelligence Verdict
“A Ball-Winner....”
See Full Verdict + Share Card →Playing Style Analysis
A Ball-Winner. Statistically, he stands out as an aggressive ball-winner (4.6 tackles/90), meticulous in distribution (85% pass accuracy), wins the physical battle (59% duel success), heavily involved in play (64 touches/90), a high-intensity presser (press score 3.6/90), constantly disrupting opposition build-up and top 10% tackler in the league. However, he loses possession under pressure (1.8 dispossessed/90). The three most similar players to Yaw Ackah by playing style are:
- Xander Blomme(87% match) — Xander Blomme is a Ball-Winner. Aggressive midfielder who disrupts opponents. Statistically, he stands out as an aggressive ball-winner (3.8 tackles/90), reads the game exceptionally (2.0 interceptions/90) and top 10% tackler in the league.
- Mart Ristl(86% match) — Mart Ristl is a Ball-Winner. Aggressive midfielder who disrupts opponents. Statistically, he stands out as an aggressive ball-winner (3.6 tackles/90) and top 10% tackler in the league. (Limited sample: 394 mins)
- Frederik Lauenborg(86% match) — A Ball-Winner. Statistically, he stands out as an elite creator (2.0 key passes/90), an aggressive ball-winner (3.1 tackles/90), reads the game exceptionally (2.0 interceptions/90), wins the physical battle (65% duel success), heavily involved in play (63 touches/90), switches play with precision (5.1 long balls/90, 85% accuracy), a high-intensity presser (press score 4.6/90), constantly disrupting opposition build-up and top 10% creator in the league. Note: this profile is based on 460 minutes of playing time this season.
Similarity is calculated using per-90 performance data across multiple playing style dimensions. How Player DNA matching works →
Similar Players — Ranked by DNA Similarity
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