RisingTransfers
AI DNA Similarity

Best Alternatives to Anselmo

Players most similar to Anselmo (Midfielder, €3.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Anselmo

  1. 1.Hamza Akman97% DNA match·Eyüpspor
  2. 2.Charles-Andre Raux Yao97% DNA match·Eyüpspor
  3. 3.W. Steindorsson96% DNA match·Lyngby Boldklub

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

RT

Intelligence Verdict

ShotsTop 0%
???Bottom 14%

A Ball-Winner....

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Playing Style Analysis

Ball-WinnerSmall Sample

A Ball-Winner. Statistically, he stands out as a capable chance creator (1.2 key passes/90), a constant goal threat (3.2 shots/90), a regular goalscorer (0.29 goals/90), a reliable supplier (0.15 assists/90), active in the tackle (2.3 tackles/90), strong in aerial duels (4.7 aerials won/90) and active off the ball (2.0 press score/90), contributing to defensive transitions. However, he loses possession under pressure (2.0 dispossessed/90). The three most similar players to Anselmo by playing style are:

  • Hamza Akman(97% match)A Box-to-Box. Statistically, he stands out as a capable chance creator (1.0 key passes/90), meticulous in distribution (87% pass accuracy), heavily involved in play (53 touches/90), draws fouls effectively (3.4/90) and active off the ball (2.3 press score/90), contributing to defensive transitions.
  • Charles-Andre Raux Yao(97% match)A Ball-Winner. Statistically, he stands out as a capable chance creator (1.1 key passes/90), a constant goal threat (2.5 shots/90), a regular goalscorer (0.36 goals/90), active in the tackle (2.2 tackles/90), heavily involved in play (64 touches/90), draws fouls effectively (5.8/90) and a high-intensity presser (press score 3.2/90), constantly disrupting opposition build-up. However, he loses possession under pressure (2.7 dispossessed/90).
  • W. Steindorsson(96% match)A Ball-Winner. Statistically, he stands out as a constant goal threat (2.9 shots/90), a proven goalscorer (0.52 goals/90), a prolific assist provider (0.34 assists/90), a dynamic dribbler (2.1/90), an aggressive ball-winner (2.8 tackles/90), wins the physical battle (57% duel success), wins the ball cleanly (2.1 successful tackles/90), heavily involved in play (53 touches/90), draws fouls effectively (2.6/90), active off the ball (2.0 press score/90), contributing to defensive transitions and top 10% tackler 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 →

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Comparison Base
Anselmo
MidfielderBrazil€3.0M
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Similar Players — Ranked by DNA Similarity

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Our 768-dimension Player DNA model matches playing style, physical profile, pressing intensity, and tactical fit. Ask the AI to explain exactly what makes these players statistically similar to Anselmo.

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Frequently Asked Questions

Who are the best alternatives to Anselmo?
The top alternatives to Anselmo based on AI DNA playing style analysis include: Hamza Akman, Charles-Andre Raux Yao, W. Steindorsson, Maurice Krattenmacher, Antonio Vergara. These players were matched using Rising Transfers' 768-dimension DNA model across playing style, pressing intensity, and tactical fit — not just position or market value.
Which players are similar to Anselmo in 2026?
Players with a similar profile to Anselmo in 2026 include Hamza Akman (N/A), Charles-Andre Raux Yao (N/A), W. Steindorsson (N/A). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Anselmo play and who plays similarly?
Anselmo plays as a Midfielder. Players with a comparable positional profile include Hamza Akman (Turkey, N/A); Charles-Andre Raux Yao (France, N/A); W. Steindorsson (Denmark, N/A); Maurice Krattenmacher (Germany, N/A).
How does Rising Transfers find similar players?
Rising Transfers uses a proprietary 768-dimension Player DNA model trained on 3.2 million match events. Each player is represented as a vector across 35+ per-90 metrics including pressing intensity, passing footprint, dribbling profile, and defensive contribution. Similarity is measured using cosine distance — the same technique used in state-of-the-art AI systems — making it the most precise player comparison tool available publicly.