RisingTransfers
AI DNA Similarity

Best Alternatives to Ayumu Ohata

Players most similar to Ayumu Ohata (Defender, €700K) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Ayumu Ohata

  1. 1.Tim Köther98% DNA match·Roda JC Kerkrade
  2. 2.Fahem Benaïssa98% DNA match·Casa Pia
  3. 3.Sacha Boey98% DNA match·Galatasaray€15.0M

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

RT

Intelligence Verdict

Chances MissedTop 0%
???Bottom 0%

A Active Full-Back....

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Playing Style Analysis

Active Full-BackSmall Sample

A Active Full-Back. Statistically, he stands out as active in the tackle (2.4 tackles/90), wins the physical battle (60% duel success), draws fouls effectively (2.1/90) and top 10% tackler in the league. Note: this profile is based on 738 minutes of playing time this season. The three most similar players to Ayumu Ohata by playing style are:

  • Tim Köther(98% match)A Active Full-Back. Statistically, he stands out as an aggressive ball-winner (3.8 tackles/90), wins the physical battle (59% duel success), wins the ball cleanly (2.5 successful tackles/90) and active off the ball (2.6 press score/90), contributing to defensive transitions. Note: this profile is based on 815 minutes of playing time this season.
  • Fahem Benaïssa(98% match)A Active Full-Back. Statistically, he stands out as an aggressive ball-winner (3.2 tackles/90), wins the physical battle (61% duel success), wins the ball cleanly (1.9 successful tackles/90), a high-intensity presser (press score 3.4/90), constantly disrupting opposition build-up and top 10% tackler in the league. Note: this profile is based on 560 minutes of playing time this season.
  • Sacha Boey(98% match)A Active Full-Back. Statistically, he stands out as an aggressive ball-winner (3.4 tackles/90), meticulous in distribution (89% pass accuracy), wins the physical battle (55% duel success), wins the ball cleanly (2.2 successful tackles/90), central to possession (71 touches/90), active off the ball (2.8 press score/90), contributing to defensive transitions and top 10% tackler in the league. Note: this profile is based on 482 minutes of playing time this season.

Transfer Intelligence

Sacha Boey delivers 98% of the same playing style, at a 2043% premium over Ayumu Ohata, with 3.36 tackles won per 90 at age 25.

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

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Comparison Base
Ayumu Ohata
DefenderJapan€700K
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Similar Players — Ranked by DNA Similarity

Ask AI: Why are these players similar?

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 Ayumu Ohata.

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Frequently Asked Questions

Who are the best alternatives to Ayumu Ohata?
The top alternatives to Ayumu Ohata based on AI DNA playing style analysis include: Tim Köther, Fahem Benaïssa, Sacha Boey, Lushendry Edward Martes, Max Scholze. 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 Ayumu Ohata in 2026?
Players with a similar profile to Ayumu Ohata in 2026 include Tim Köther (N/A), Fahem Benaïssa (N/A), Sacha Boey (€15.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Ayumu Ohata play and who plays similarly?
Ayumu Ohata plays as a Defender. Players with a comparable positional profile include Tim Köther (Germany, N/A); Fahem Benaïssa (France, N/A); Sacha Boey (France, €15.0M); Lushendry Edward Martes (Netherlands, 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.