RisingTransfers
AI DNA Similarity

Best Alternatives to Valentin Atangana

Players most similar to Valentin Atangana (Midfielder, €15.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Valentin Atangana

  1. 1.Oussama Targhalline85% DNA match·Feyenoord€8.0M
  2. 2.Frank Anguissa 86% DNA match·Napoli€15.0M
  3. 3.Amadou Onana85% DNA match·Aston Villa€42.0M

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

RT

Intelligence Verdict

GoalsTop 6%
???Bottom 0%

A Balanced Midfielder....

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Playing Style Analysis

Balanced MidfielderDefensive

A Balanced Midfielder. Statistically, he stands out as a regular goalscorer (0.30 goals/90), an aggressive ball-winner (2.7 tackles/90), meticulous in distribution (85% pass accuracy), active off the ball (2.7 press score/90), contributing to defensive transitions and top 10% tackler in the league. The three most similar players to Valentin Atangana by playing style are:

  • Oussama Targhalline(85% match)Targhalline is the kind of midfielder who wins games in the spaces most fans never notice—a relentless ground-level disruptor who ranks in the Eredivisie's top 5% for duel success and top 10% for both interceptions and tackles won. His shot volume sits in the bottom 10% of the league, which looks damning until you realise his game is built entirely around controlling territory rather than claiming it for himself—he wins the ball, moves it accurately at 85.2%, and consistently threads passes into the final third at a top-20% clip. The counterintuitive truth is that his low key pass numbers don't signal a lack of ambition; they signal a player who transitions quickly rather than loitering in creative zones.
  • Frank Anguissa (86% match)A Box-to-Box. Statistically, he stands out as a capable chance creator (1.3 key passes/90), heavily involved in play (60 touches/90) and active off the ball (2.1 press score/90), contributing to defensive transitions. However, he loses possession under pressure (1.5 dispossessed/90).
  • Amadou Onana(85% match)A Box-to-Box. Statistically, he stands out as active in the tackle (2.4 tackles/90), meticulous in distribution (87% pass accuracy), wins the physical battle (64% duel success), heavily involved in play (58 touches/90) and active off the ball (2.3 press score/90), contributing to defensive transitions.

Transfer Intelligence

Oussama Targhalline delivers 85% of the same playing style, at 47% lower cost (€8.0M vs €15.0M), with 0.94 key passes per 90 at age 23.

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

V
Comparison Base
Valentin Atangana
MidfielderFrance€15.0M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
O
Oussama Targhalline
Feyenoord · Eredivisie
Morocco23yContract 2028
KP/900.94
G/900.10
Ball-WinnerDefensive
Last 5: ↑ Hot
vs Atangana: €7M cheaper · 3y older
85% match
€8.0M
#2
F
Frank Anguissa 
Napoli · Serie A
Cameroon30yContract 2027
KP/901.31
G/900.19
Box-to-BoxSmall Sample
vs Atangana: 10y older
86% match
€15.0M
#3
A
Amadou Onana
Aston Villa · Premier League
Belgium24yContract 2029
KP/900.36
G/900.10
Box-to-Box
Last 5: ↑ Hot
vs Atangana: €27M more expensive · 4y older
85% match
€42.0M
#4
C
Carlos Baleba
Brighton & Hove Albion · Premier League
Cameroon22yContract 2028
KP/900.35
G/900.00
Box-to-Box
Last 5: ↑ Hot
85% match
€60.0M
#5
J
Johann Lepenant
Nantes · Ligue 1
France23yContract 2029
KP/902.13
G/900.00
Ball-WinnerCreative
Last 5: ↑ Hot
85% match
€7.0M
#6
J
Junior Mwanga
Strasbourg · Ligue 1
France23yContract 2027
KP/901.19
G/900.00
Box-to-Box
85% match
€6.0M
#7
M
Mamadou Sangaré
Lens · Ligue 1
Mali23yContract 2030
KP/902.24
G/900.00
CreatorCreative
Last 5: → Stable
85% match
€15.0M
#8
A
Ao Tanaka
Leeds United · Premier League
Japan27yContract 2028
KP/901.52
G/900.15
CreatorCreative
Last 5: → Stable
84% match
€10.0M
#9
J
Jorthy Mokio
Ajax · Eredivisie
Belgium18yContract 2027
KP/900.80
G/900.15
Ball-WinnerDefensive
Last 5: → Stable
84% match
€8.0M
#10
L
Lamine Camara
Monaco · Ligue 1
Senegal22yContract 2029
KP/901.40
G/900.00
MetronomeCreative
Last 5: → Stable
84% match
€35.0M
#11
R
Ramiz Zerrouki
FC Twente · Eredivisie
Algeria27y
KP/901.56
G/900.11
MetronomeCreative
Last 5: ↑ Hot
83% match
€7.2M
#12
M
Mahdi Camara
Rennes · Ligue 1
France27yContract 2029
KP/900.97
G/900.00
Box-to-Box
Last 5: ↓ Dip
84% match
€10.0M

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 Valentin Atangana.

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Frequently Asked Questions

Who are the best alternatives to Valentin Atangana?
The top alternatives to Valentin Atangana based on AI DNA playing style analysis include: Oussama Targhalline, Frank Anguissa , Amadou Onana, Carlos Baleba, Johann Lepenant. 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 Valentin Atangana in 2026?
Players with a similar profile to Valentin Atangana in 2026 include Oussama Targhalline (€8.0M), Frank Anguissa  (€15.0M), Amadou Onana (€42.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Valentin Atangana play and who plays similarly?
Valentin Atangana plays as a Midfielder. Players with a comparable positional profile include Oussama Targhalline (Morocco, €8.0M); Frank Anguissa  (Cameroon, €15.0M); Amadou Onana (Belgium, €42.0M); Carlos Baleba (Cameroon, €60.0M).
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.