RisingTransfers
AI DNA Similarity

Best Alternatives to Jean-Victor Makengo

Players most similar to Jean-Victor Makengo (Midfielder, €2.5M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Jean-Victor Makengo

  1. 1.Junior Dina Ebimbe86% DNA match·Brest€6.0M
  2. 2.Beni Mukendi86% DNA match·Vitória Guimarães€3.0M
  3. 3.Kamory Doumbia85% DNA match·Brest€7.0M

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

RT

Intelligence Verdict

Chances MissedTop 0%
???Bottom 12%

A Creator....

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Playing Style Analysis

CreatorSmall Sample

A Creator. Statistically, he stands out as naturally left-footed, a proven goalscorer (0.54 goals/90), a reliable supplier (0.18 assists/90), active in the tackle (2.2 tackles/90), wins the physical battle (64% duel success) and active off the ball (2.2 press score/90), contributing to defensive transitions. Note: this profile is based on 498 minutes of playing time this season. The three most similar players to Jean-Victor Makengo by playing style are:

  • Junior Dina Ebimbe(86% match)A Balanced Midfielder. Statistically, he stands out as a proven goalscorer (0.52 goals/90). Note: this profile is based on 863 minutes of playing time this season.
  • Beni Mukendi(86% match)A Box-to-Box. Statistically, he stands out as active in the tackle (1.9 tackles/90), meticulous in distribution (89% pass accuracy), wins the physical battle (62% duel success), heavily involved in play (64 touches/90), draws fouls effectively (2.2/90) and a high-intensity presser (press score 3.1/90), constantly disrupting opposition build-up.
  • Kamory Doumbia(85% match)A Creator. Statistically, he stands out as an elite creator (1.7 key passes/90), a proven goalscorer (0.63 goals/90), an aggressive ball-winner (3.0 tackles/90), meticulous in distribution (86% pass accuracy), heavily involved in play (57 touches/90) and active off the ball (2.7 press score/90), contributing to defensive transitions. However, he loses possession under pressure (1.9 dispossessed/90).

Transfer Intelligence

Junior Dina Ebimbe delivers 86% of the same playing style, at a 140% premium over Jean-Victor Makengo, with 0.28 key passes per 90 at age 25.

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

J
Comparison Base
Jean-Victor Makengo
MidfielderFrance€2.5M
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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 Jean-Victor Makengo.

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Frequently Asked Questions

Who are the best alternatives to Jean-Victor Makengo?
The top alternatives to Jean-Victor Makengo based on AI DNA playing style analysis include: Junior Dina Ebimbe, Beni Mukendi, Kamory Doumbia, Marshall Munetsi, Junior Mwanga. 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 Jean-Victor Makengo in 2026?
Players with a similar profile to Jean-Victor Makengo in 2026 include Junior Dina Ebimbe (€6.0M), Beni Mukendi (€3.0M), Kamory Doumbia (€7.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Jean-Victor Makengo play and who plays similarly?
Jean-Victor Makengo plays as a Midfielder. Players with a comparable positional profile include Junior Dina Ebimbe (France, €6.0M); Beni Mukendi (Angola, €3.0M); Kamory Doumbia (Mali, €7.0M); Marshall Munetsi (Zimbabwe, €18.0M).
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.