RisingTransfers
AI DNA Similarity

Best Alternatives to Mussa Kaba

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

Top 3 Alternatives to Mussa Kaba

  1. 1.Charlie Gray97% DNA match·Manchester City
  2. 2.Dave Kwakman97% DNA match·FC Volendam
  3. 3.Rafael Filipe Gonçalves Soares Luís96% DNA match·Strasbourg€4.0M

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

RT

Intelligence Verdict

???Bottom 0%

A Ball-Winner....

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Playing Style Analysis

Ball-WinnerSmall Sample

A Ball-Winner. Statistically, he stands out as a reliable supplier (0.17 assists/90), meticulous in distribution (90% pass accuracy) and wins the physical battle (67% duel success). Note: this profile is based on 523 minutes of playing time this season. The three most similar players to Mussa Kaba by playing style are:

  • Charlie Gray(97% match)A Ball-Winner. Statistically, he stands out as a capable chance creator (1.0 key passes/90), a reliable supplier (0.17 assists/90), meticulous in distribution (92% pass accuracy), heavily involved in play (56 touches/90) and top 10% creator in the league. Note: this profile is based on 541 minutes of playing time this season.
  • Dave Kwakman(97% match)A Ball-Winner. Statistically, he stands out as a prolific assist provider (0.50 assists/90), an aggressive ball-winner (3.8 tackles/90), meticulous in distribution (85% pass accuracy), wins the physical battle (56% duel success), wins the ball cleanly (2.0 successful tackles/90), heavily involved in play (60 touches/90), draws fouls effectively (2.3/90), active off the ball (2.8 press score/90), contributing to defensive transitions and top 10% tackler in the league. Note: this profile is based on 717 minutes of playing time this season.
  • Rafael Filipe Gonçalves Soares Luís(96% match)A Ball-Winner. Statistically, he stands out as naturally left-footed, a capable chance creator (1.0 key passes/90), a reliable supplier (0.17 assists/90), an aggressive ball-winner (3.0 tackles/90), meticulous in distribution (88% pass accuracy), central to possession (72 touches/90) and top 10% tackler in the league. Note: this profile is based on 541 minutes of playing time this season.

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

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Comparison Base
Mussa Kaba
MidfielderGuineaN/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 Mussa Kaba.

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Frequently Asked Questions

Who are the best alternatives to Mussa Kaba?
The top alternatives to Mussa Kaba based on AI DNA playing style analysis include: Charlie Gray, Dave Kwakman, Rafael Filipe Gonçalves Soares Luís, José Luís Rocha Tavares, Juanpe. 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 Mussa Kaba in 2026?
Players with a similar profile to Mussa Kaba in 2026 include Charlie Gray (N/A), Dave Kwakman (N/A), Rafael Filipe Gonçalves Soares Luís (€4.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Mussa Kaba play and who plays similarly?
Mussa Kaba plays as a Midfielder. Players with a comparable positional profile include Charlie Gray (England, N/A); Dave Kwakman (Netherlands, N/A); Rafael Filipe Gonçalves Soares Luís (Portugal, €4.0M); José Luís Rocha Tavares (Cape Verde, 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.