AI DNA Similarity

Best Alternatives to Kyle De Silva

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

Playing Style Analysis

A Midfielder in FA Cup. The three most similar players to Kyle De Silva by playing style are:

  • Alexandre Vincent(92% match)A Midfielder in Coupe de France.
  • Cas Dijkstra(90% match)A Midfielder in KNVB Beker.
  • Max de Waal(90% match)A Midfielder in KNVB Beker.

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

K
Comparison Base
Kyle De Silva
MidfielderEnglandN/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 Kyle De Silva.

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Frequently Asked Questions

Who are the best alternatives to Kyle De Silva?
The top alternatives to Kyle De Silva based on AI DNA playing style analysis include: Alexandre Vincent, Cas Dijkstra, Max de Waal, Habib Diarra, Mathis Picouleau. 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 Kyle De Silva in 2026?
Players with a similar profile to Kyle De Silva in 2026 include Alexandre Vincent (N/A), Cas Dijkstra (N/A), Max de Waal (N/A). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Kyle De Silva play and who plays similarly?
Kyle De Silva plays as a Midfielder. Players with a comparable positional profile include Alexandre Vincent (France, N/A); Cas Dijkstra (Netherlands, N/A); Max de Waal (Netherlands, N/A); Habib Diarra (France, €32.0M).
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.