RisingTransfers
AI DNA Similarity

Best Alternatives to Michael Ohana

Players most similar to Michael Ohana (Midfielder, €2.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Michael Ohana

  1. 1.Luis Hasa86% DNA match·Napoli€3.0M
  2. 2.Dani Lorenzo83% DNA match·Málaga
  3. 3.Mike Tresor83% DNA match·Burnley€3.0M

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

RT

Intelligence Verdict

AssistsTop 0%
???Bottom 0%

A Creator....

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Playing Style Analysis

CreatorCreativeDefensiveSmall Sample

A Creator. Statistically, he stands out as an elite creator (2.3 key passes/90), a regular goalscorer (0.22 goals/90), a prolific assist provider (0.43 assists/90), a dynamic dribbler (2.3/90), an aggressive ball-winner (2.6 tackles/90), creates high-quality scoring opportunities (0.87 big chances/90), heavily involved in play (51 touches/90), active off the ball (2.3 press score/90), contributing to defensive transitions and top 10% creator in the league. However, he loses possession under pressure (1.5 dispossessed/90). The three most similar players to Michael Ohana by playing style are:

  • Luis Hasa(86% match)A Box-to-Box. Statistically, he stands out as a capable chance creator (1.5 key passes/90), a regular goalscorer (0.20 goals/90), a reliable supplier (0.16 assists/90), meticulous in distribution (89% pass accuracy), heavily involved in play (61 touches/90), draws fouls effectively (2.7/90) and active off the ball (2.8 press score/90), contributing to defensive transitions.
  • Dani Lorenzo(83% match)A Creator. Statistically, he stands out as a capable chance creator (1.4 key passes/90), a dynamic dribbler (2.0/90), meticulous in distribution (90% pass accuracy), heavily involved in play (65 touches/90) and active off the ball (2.7 press score/90), contributing to defensive transitions.
  • Mike Tresor(83% 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.

Transfer Intelligence

Luis Hasa delivers 86% of the same playing style, at a 50% premium over Michael Ohana, with 0.90 key passes per 90 at age 22.

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

M
Comparison Base
Michael Ohana
MidfielderIsrael€2.0M
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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 Michael Ohana.

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Frequently Asked Questions

Who are the best alternatives to Michael Ohana?
The top alternatives to Michael Ohana based on AI DNA playing style analysis include: Luis Hasa, Dani Lorenzo, Mike Tresor, Dani Rodríguez, Antoni Milambo. 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 Michael Ohana in 2026?
Players with a similar profile to Michael Ohana in 2026 include Luis Hasa (€3.0M), Dani Lorenzo (N/A), Mike Tresor (€3.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Michael Ohana play and who plays similarly?
Michael Ohana plays as a Midfielder. Players with a comparable positional profile include Luis Hasa (Italy, €3.0M); Dani Lorenzo (Spain, N/A); Mike Tresor (Belgium, €3.0M); Dani Rodríguez (Spain, 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.