RisingTransfers
AI DNA Similarity

Best Alternatives to Ethan Erhahon

Players most similar to Ethan Erhahon (Midfielder, €860K) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Ethan Erhahon

  1. 1.Gonçalo Nogueira99% DNA match·Vitória Guimarães
  2. 2.Jay Matete99% DNA match·Sunderland
  3. 3.Gibson Yah99% DNA match·FC Volendam

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

RT

Intelligence Verdict

Chances MissedTop 0%
???Bottom 23%

A Ball-Winner....

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Playing Style Analysis

Ball-WinnerDefensive

A Ball-Winner. Statistically, he stands out as a capable chance creator (1.0 key passes/90), a reliable supplier (0.15 assists/90), an aggressive ball-winner (2.9 tackles/90), meticulous in distribution (85% pass accuracy), wins the physical battle (60% duel success), wins the ball cleanly (1.9 successful tackles/90), heavily involved in play (62 touches/90), active off the ball (2.9 press score/90), contributing to defensive transitions and top 10% tackler in the league. The three most similar players to Ethan Erhahon by playing style are:

  • Gonçalo Nogueira(99% match)A Ball-Winner. Statistically, he stands out as a capable chance creator (1.4 key passes/90), a prolific assist provider (0.30 assists/90), an aggressive ball-winner (3.2 tackles/90), meticulous in distribution (87% pass accuracy), wins the physical battle (56% duel success), wins the ball cleanly (2.0 successful tackles/90), draws fouls effectively (2.7/90), active off the ball (2.5 press score/90), contributing to defensive transitions and top 10% tackler in the league.
  • Jay Matete(99% match)A Ball-Winner. Statistically, he stands out as a capable chance creator (1.2 key passes/90), an aggressive ball-winner (2.7 tackles/90), meticulous in distribution (88% pass accuracy), wins the physical battle (56% duel success), creates high-quality scoring opportunities (0.65 big chances/90), heavily involved in play (64 touches/90), draws fouls effectively (2.4/90) and top 10% tackler in the league.
  • Gibson Yah(99% match)A Ball-Winner. Statistically, he stands out as a reliable supplier (0.17 assists/90), an aggressive ball-winner (3.7 tackles/90), reads the game exceptionally (1.7 interceptions/90), wins the physical battle (63% duel success), wins the ball cleanly (2.4 successful tackles/90), heavily involved in play (67 touches/90), a high-intensity presser (press score 3.5/90), constantly disrupting opposition build-up and top 10% tackler in the league.

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

E
Comparison Base
Ethan Erhahon
MidfielderScotland€860K
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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 Ethan Erhahon.

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Frequently Asked Questions

Who are the best alternatives to Ethan Erhahon?
The top alternatives to Ethan Erhahon based on AI DNA playing style analysis include: Gonçalo Nogueira, Jay Matete, Gibson Yah, Dennis Dressel, Celil Yüksel. 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 Ethan Erhahon in 2026?
Players with a similar profile to Ethan Erhahon in 2026 include Gonçalo Nogueira (N/A), Jay Matete (N/A), Gibson Yah (N/A). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Ethan Erhahon play and who plays similarly?
Ethan Erhahon plays as a Midfielder. Players with a comparable positional profile include Gonçalo Nogueira (Portugal, N/A); Jay Matete (England, N/A); Gibson Yah (Netherlands, N/A); Dennis Dressel (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.