AI DNA Similarity

Best Alternatives to Milan de Haan

Players most similar to Milan de Haan (Midfielder, N/A) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Playing Style Analysis

Milan de Haan is a Creator. Playmaker unlocking defenses with key passes. The three most similar players to Milan de Haan by playing style are:

  • Daniël van Kaam(88% match)Daniël van Kaam is a Creator. Playmaker unlocking defenses with key passes.
  • Richard Neudecker(85% match)Richard Neudecker is a Creator. Playmaker unlocking defenses with key passes.
  • Smilla Vallotto(85% match)Smilla Vallotto is a Creator. Playmaker unlocking defenses with key passes.

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

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Comparison Base
Milan de Haan
MidfielderNetherlandsN/A
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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 Milan de Haan.

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Frequently Asked Questions

Who are the best alternatives to Milan de Haan?
The top alternatives to Milan de Haan based on AI DNA playing style analysis include: Daniël van Kaam, Richard Neudecker, Smilla Vallotto, Luís André Leite Esteves, Mitchel Bakker. 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 Milan de Haan in 2026?
Players with a similar profile to Milan de Haan in 2026 include Daniël van Kaam (N/A), Richard Neudecker (N/A), Smilla Vallotto (N/A). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Milan de Haan play and who plays similarly?
Milan de Haan plays as a Midfielder. Players with a comparable positional profile include Daniël van Kaam (Netherlands, N/A); Richard Neudecker (Germany, N/A); Smilla Vallotto (Switzerland, N/A); Luís André Leite Esteves (Portugal, 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.