RisingTransfers
AI DNA Similarity

Best Alternatives to Cihan Kahraman

Players most similar to Cihan Kahraman (Midfielder, €50K) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Cihan Kahraman

  1. 1.Rocco Ascone97% DNA match·Nordsjælland
  2. 2.Gustavo Klismahn96% DNA match·Santa Clara
  3. 3.Odysseus Velanas96% DNA match·PEC Zwolle

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

RT

Intelligence Verdict

AssistsTop 0%
???Bottom 0%

A Ball-Winner....

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Playing Style Analysis

Ball-WinnerCreativeDefensiveSmall Sample

A Ball-Winner. Statistically, he stands out as an elite creator (1.9 key passes/90), a prolific assist provider (0.62 assists/90), a dynamic dribbler (2.5/90), an aggressive ball-winner (2.9 tackles/90), reads the game exceptionally (1.5 interceptions/90), creates high-quality scoring opportunities (0.75 big chances/90) and top 10% creator in the league. Note: this profile is based on 721 minutes of playing time this season. The three most similar players to Cihan Kahraman by playing style are:

  • Rocco Ascone(97% match)A Ball-Winner. Statistically, he stands out as an elite creator (2.2 key passes/90), an aggressive ball-winner (5.5 tackles/90), wins the physical battle (60% duel success), wins the ball cleanly (2.8 successful tackles/90), central to possession (70 touches/90), uses long balls frequently (5.5/90), active off the ball (2.9 press score/90), contributing to defensive transitions, top 10% creator in the league and top 10% tackler in the league. Note: this profile is based on 542 minutes of playing time this season.
  • Gustavo Klismahn(96% match)A Creator. Statistically, he stands out as an elite creator (1.6 key passes/90) and top 20% creator in the league.
  • Odysseus Velanas(96% match)A Creator. Statistically, he stands out as an elite creator (2.0 key passes/90), a regular goalscorer (0.33 goals/90), a reliable supplier (0.17 assists/90), an aggressive ball-winner (3.3 tackles/90), creates high-quality scoring opportunities (0.67 big chances/90), wins the ball cleanly (2.0 successful tackles/90), heavily involved in play (53 touches/90), draws fouls effectively (2.5/90), active off the ball (2.4 press score/90), contributing to defensive transitions, top 20% creator in the league and top 10% tackler in the league. Note: this profile is based on 539 minutes of playing time this season.

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

C
Comparison Base
Cihan Kahraman
MidfielderTurkey€50K
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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 Cihan Kahraman.

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Frequently Asked Questions

Who are the best alternatives to Cihan Kahraman?
The top alternatives to Cihan Kahraman based on AI DNA playing style analysis include: Rocco Ascone, Gustavo Klismahn, Odysseus Velanas, Tyler Onyango, Iván Corralejo. 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 Cihan Kahraman in 2026?
Players with a similar profile to Cihan Kahraman in 2026 include Rocco Ascone (N/A), Gustavo Klismahn (N/A), Odysseus Velanas (N/A). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Cihan Kahraman play and who plays similarly?
Cihan Kahraman plays as a Midfielder. Players with a comparable positional profile include Rocco Ascone (France, N/A); Gustavo Klismahn (Brazil, N/A); Odysseus Velanas (Netherlands, N/A); Tyler Onyango (England, 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.