RisingTransfers
AI DNA Similarity

Best Alternatives to Saleh Abu Al-Shamat

Players most similar to Saleh Abu Al-Shamat (Attacker, €2.1M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Saleh Abu Al-Shamat

  1. 1.Simon Adingra98% DNA match·Monaco€22.0M
  2. 2.Tunahan Taşçı98% DNA match·Konyaspor
  3. 3.Frederik Emmery98% DNA match·AGF

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

RT

Intelligence Verdict

Press IntensityTop 0%
???Bottom 0%

A Dynamic Forward....

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Playing Style Analysis

Dynamic ForwardDribblerSmall Sample

A Dynamic Forward. Statistically, he stands out as an elite creator (3.0 key passes/90), a prolific assist provider (0.33 assists/90), a dynamic dribbler (2.5/90), wins the physical battle (58% duel success), creates high-quality scoring opportunities (0.67 big chances/90) and central to possession (79 touches/90). Note: this profile is based on 539 minutes of playing time this season. The three most similar players to Saleh Abu Al-Shamat by playing style are:

  • Simon Adingra(98% match)A Dynamic Forward. Statistically, he stands out as an elite creator (2.1 key passes/90), a reliable supplier (0.16 assists/90) and a dynamic dribbler (3.0/90). However, he loses possession under pressure (1.6 dispossessed/90).
  • Tunahan Taşçı(98% match)A Dynamic Forward. Statistically, he stands out as an elite creator (1.7 key passes/90), a reliable supplier (0.17 assists/90), a dynamic dribbler (2.2/90) and creates high-quality scoring opportunities (1.18 big chances/90). Note: this profile is based on 532 minutes of playing time this season.
  • Frederik Emmery(98% match)A Dynamic Forward. Statistically, he stands out as an elite creator (1.8 key passes/90), a regular goalscorer (0.27 goals/90), a prolific assist provider (0.27 assists/90), a dynamic dribbler (3.1/90), creates high-quality scoring opportunities (0.81 big chances/90) and draws fouls effectively (2.7/90). However, he loses possession under pressure (2.2 dispossessed/90).

Transfer Intelligence

Simon Adingra delivers 98% of the same playing style, at a 963% premium over Saleh Abu Al-Shamat, with 0.14 goals per 90 at age 24.

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

S
Comparison Base
Saleh Abu Al-Shamat
AttackerSaudi Arabia€2.1M
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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 Saleh Abu Al-Shamat.

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Frequently Asked Questions

Who are the best alternatives to Saleh Abu Al-Shamat?
The top alternatives to Saleh Abu Al-Shamat based on AI DNA playing style analysis include: Simon Adingra, Tunahan Taşçı, Frederik Emmery, Noam Emeran, Isaiah Young. 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 Saleh Abu Al-Shamat in 2026?
Players with a similar profile to Saleh Abu Al-Shamat in 2026 include Simon Adingra (€22.0M), Tunahan Taşçı (N/A), Frederik Emmery (N/A). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Saleh Abu Al-Shamat play and who plays similarly?
Saleh Abu Al-Shamat plays as a Attacker. Players with a comparable positional profile include Simon Adingra (Ivory Coast, €22.0M); Tunahan Taşçı (Turkey, N/A); Frederik Emmery (Denmark, N/A); Noam Emeran (France, 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.