Best Alternatives to Talles Costa

Top 3 Alternatives to Talles Costa

1. 1.Alex Scott87% DNA match·AFC Bournemouth€40.0M
2. 2.Samú Costa87% DNA match·Mallorca€15.0M
3. 3.Mike Tresor86% DNA match·Burnley€3.0M

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

Playing Style Analysis

Costa is a technical facilitator operating with a quiet efficiency that belies the chaotic environment of a Tier C Premier League outfit. While his 373 minutes represent a partial sample, the data suggests a player who demands the ball, ranking in the top 30% for pass volume (35.5/90) and accuracy (84.1%). He is not merely a sideways recycler; his 0.24 assists per 90 place him among the league’s most productive creators from deep, outperforming the typical midfield "engine." Counterintuitively, despite his slight profile, his duel win rate (42.9%) sits in the top 30%, proving he possesses a deceptive functional strength that many scouts overlook in favor of raw physicality. The three most similar players to Talles Costa by playing style are:

• Alex Scott(87% match) — A Box-to-Box. Statistically, he stands out as active in the tackle (1.9 tackles/90), wins the physical battle (55% duel success), heavily involved in play (63 touches/90) and a high-intensity presser (press score 3.1/90), constantly disrupting opposition build-up.
• Samú Costa(87% match) — A Ball-Winner. Statistically, he stands out as naturally left-footed, a regular goalscorer (0.26 goals/90), active in the tackle (2.2 tackles/90), heavily involved in play (60 touches/90), draws fouls effectively (2.4/90) and active off the ball (2.3 press score/90), contributing to defensive transitions.
• Mike Tresor(86% match) — A Creator. Statistically, he stands out as an elite creator (3.0 key passes/90), a regular goalscorer (0.22 goals/90), a prolific assist provider (0.65 assists/90), creates high-quality scoring opportunities (0.60 big chances/90) and top 10% creator in the league.

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