RisingTransfers
AI DNA Similarity

Best Alternatives to Anthony Musaba

Players most similar to Anthony Musaba (Attacker, €4.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Anthony Musaba

  1. 1.Ahmed Kutucu85% DNA match·Galatasaray€4.0M
  2. 2.Moussa Djenepo85% DNA match·Esteghlal€15.7M
  3. 3.Milot Rashica84% DNA match·Beşiktaş€4.0M

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

RT

Intelligence Verdict

Big ChancesTop 6%
???Bottom 8%

A Inside Forward....

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Playing Style Analysis

Inside ForwardDribbler

A Inside Forward. Statistically, he stands out as a capable chance creator (1.1 key passes/90), a constant goal threat (3.1 shots/90), a regular goalscorer (0.31 goals/90), a reliable supplier (0.15 assists/90), a dynamic dribbler (2.1/90) and creates high-quality scoring opportunities (0.61 big chances/90). However, he loses possession under pressure (1.5 dispossessed/90). The three most similar players to Anthony Musaba by playing style are:

  • Ahmed Kutucu(85% match)Kutucu is the Turkish Süper Lig’s most efficient offensive enigma, a high-volume shooter who combines the clinical finishing of a veteran poacher with the creative vision of a seasoned playmaker. While playing for a Tier C side, his output is undeniably elite; he ranks in the top 5% of the league for both shots and assists per 90, proving he is as much a facilitator as he is a finisher. The data reveals a fascinating paradox: despite being an "Attacker" by trade, his 85.7% pass accuracy puts him in the top 10% of his peers, suggesting he operates more as a sophisticated offensive hub than a traditional line-leader.
  • Moussa Djenepo(85% match)A Complete Forward. Statistically, he stands out as a capable chance creator (1.1 key passes/90), a dynamic dribbler (4.0/90), creates high-quality scoring opportunities (0.84 big chances/90) and draws fouls effectively (2.7/90). However, he loses possession under pressure (2.0 dispossessed/90) and prone to committing fouls (2.5/90).
  • Milot Rashica(84% match)Rashica has evolved from a purebred transitional speedster into a blue-collar creative engine who defies the typical "luxury" winger archetype. While his 72% pass accuracy suggests a lack of refinement, the data reveals a high-risk, high-reward playmaker who sits in the top 5% of the Super Lig for key passes (2.11/90) and assists (0.32/90). The counterintuitive insight here is his defensive ferocity; despite being an attacker, he ranks in the top 5% for both ground duel win rate (83.3%) and tackles won, functioning more like a defensive end in a high-pressing system than a traditional wide man.

Transfer Intelligence

Ahmed Kutucu delivers 85% of the same playing style, with 0.49 goals per 90 at age 26. That's 160% of Anthony Musaba's output in goals per 90 — a credible like-for-like option.

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

A
Comparison Base
Anthony Musaba
AttackerNetherlands€4.0M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
A
Ahmed Kutucu
Galatasaray · Super Lig
Turkey26yContract 2028
G/900.49
A/900.37
Inside ForwardProlific
vs Musaba: +0.18 G/90
85% match
€4.0M
#2
M
Moussa Djenepo
Esteghlal · Super Lig
Mali27y
G/900.09
A/900.00
Complete ForwardDribbler
vs Musaba: €12M more expensive · 2y older · -0.22 G/90
85% match
€15.7M
#3
M
Milot Rashica
Beşiktaş · Super Lig
Kosovo29yContract 2027
G/900.09
A/900.28
Small Sample
Last 5: ↓ Dip
vs Musaba: 4y older · -0.21 G/90
84% match
€4.0M
#4
K
Kerem Aktürkoğlu
Fenerbahçe · Super Lig
Turkey27yContract 2029
G/900.29
A/900.34
Complete Forward
Last 5: → Stable
84% match
€22.0M
#5
D
Darko Churlinov
Kocaelispor · Super Lig
Macedonia25y
G/900.00
A/900.27
Dynamic ForwardDribbler
84% match
€3.5M
#6
A
Anis Hadj Moussa
Feyenoord · Eredivisie
Algeria24yContract 2030
G/900.33
A/900.22
Inside ForwardDribbler
Last 5: ↓ Dip
82% match
€20.0M
#7
M
Mohamed Bayo
Gaziantep F.K. · Super Lig
Guinea27y
G/900.60
A/900.12
PoacherProlific
Last 5: → Stable
82% match
€14.0M
#8
C
Cheikh Sabaly
Vancouver Whitecaps · Ligue 1
Senegal27yContract 2029
G/900.46
A/900.00
Last 5: → Stable
83% match
€3.5M
#9
M
Mama Baldé
Brest · Ligue 1
Guinea-Bissau30yContract 2027
G/900.00
A/900.65
Target ManSmall Sample
83% match
€3.5M
#10
İ
İrfan Can Kahveci
Kasımpaşa · Super Lig
Turkey30yContract 2026
G/900.15
A/900.23
Last 5: ↑ Hot
83% match
€4.5M
#11
C
Cherif Ndiaye
Samsunspor · Super Lig
Senegal30y
G/900.47
A/900.07
Complete ForwardProlific
Last 5: ↑ Hot
83% match
€4.0M
#12
F
Franco Tongya
Gençlerbirliği · Super Lig
Italy24y
G/900.16
A/900.08
Last 5: ↑ Hot
83% match
€8.0M

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 Anthony Musaba.

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Frequently Asked Questions

Who are the best alternatives to Anthony Musaba?
The top alternatives to Anthony Musaba based on AI DNA playing style analysis include: Ahmed Kutucu, Moussa Djenepo, Milot Rashica, Kerem Aktürkoğlu, Darko Churlinov. 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 Anthony Musaba in 2026?
Players with a similar profile to Anthony Musaba in 2026 include Ahmed Kutucu (€4.0M), Moussa Djenepo (€15.7M), Milot Rashica (€4.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Anthony Musaba play and who plays similarly?
Anthony Musaba plays as a Attacker. Players with a comparable positional profile include Ahmed Kutucu (Turkey, €4.0M); Moussa Djenepo (Mali, €15.7M); Milot Rashica (Kosovo, €4.0M); Kerem Aktürkoğlu (Turkey, €22.0M).
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.