AI DNA Similarity
Best Alternatives to A. Ksenofontov
Players most similar to A. Ksenofontov (Midfielder, €100K) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.
Top 3 Alternatives to A. Ksenofontov
- 1.Salvador Blopa85% DNA match·Sporting CP
- 2.Jeremiah Mensah84% DNA match·Bayer 04 Leverkusen
- 3.Maurizio Brenna84% DNA match·Katwijk
Ranked by AI DNA similarity — 768 dimensions across playing style, pressing intensity, and tactical fit.
RT
Intelligence Verdict
???Bottom 0%
“Aleksandr Ksenofontov is a Midfielder....”
See Full Verdict + Share Card →Playing Style Analysis
Small Sample
Aleksandr Ksenofontov is a Midfielder. Solid midfield option. (Limited sample: 278 mins) The three most similar players to A. Ksenofontov by playing style are:
- Salvador Blopa(85% match) — Salvador Blopa is a Midfielder. Solid midfield option. (Limited sample: 270 mins)
- Jeremiah Mensah(84% match) — Jeremiah Dennit Mensah is a Midfielder. Solid midfield option. (Limited sample: 327 mins)
- Maurizio Brenna(84% match) — Maurizio Brenna is a Midfielder. Solid midfield option. (Limited sample: 299 mins)
Similarity is calculated using per-90 performance data across multiple playing style dimensions. How Player DNA matching works →
Similar Players — Ranked by DNA Similarity
#1
S
Salvador Blopa
Sporting CP · Liga Portugal
Portugal18y
KP/900.00
G/900.00
Small Sample
vs Ksenofontov: 9y younger
85% match
N/A
#2
J
Jeremiah Mensah
Bayer 04 Leverkusen · Bundesliga
Germany18y
KP/900.00
G/900.00
Small Sample
vs Ksenofontov: 9y younger
84% match
N/A
#3
M
Maurizio Brenna
Katwijk · Eredivisie
Netherlands27y
KP/900.00
G/900.00
Small Sample
84% match
N/A
#4
K
Kiano Dyer
FC Volendam · Eredivisie
England19y
KP/900.00
G/900.00
Small Sample
84% match
N/A
#5
D
Doni Arifi
SpVgg Greuther Fürth · Bundesliga
Finland24y
KP/901.12
G/900.00
Small Sample
Last 5: ↓ Dip83% match
N/A
#6
G
Gerry Vlak
Koninklijke HFC · Eredivisie
Netherlands30y
KP/900.00
G/900.00
Small Sample
82% match
N/A
#7
Y
Yanis Khafi
Paris Saint Germain · Ligue 1
France20y
KP/901.18
G/900.00
Small Sample
82% match
N/A
#8
A
Alamara Djabi
FC Midtjylland · Superliga
Guinea-Bissau19y
KP/900.00
G/900.00
Small Sample
82% match
N/A
#9
R
Rick van der Meer
Katwijk · Eredivisie
Netherlands28y
KP/900.00
G/900.00
Small Sample
81% match
N/A
#10
N
Noah Fenyö
Eintracht Frankfurt · Bundesliga
Hungary20yContract 2029
KP/900.26
G/900.52
Small Sample
81% match
N/A
#11
U
Ulrich Taffertshofer
Atlético Baleares · La Liga
Germany34yContract 2026
KP/900.00
G/900.00
81% match
N/A
#12
J
Joseph Nduquidi
Metz · Ligue 1
France21y
KP/900.15
G/900.00
Balanced MidfielderSmall Sample
Last 5: ↓ Dip81% match
N/A
⬡
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 A. Ksenofontov.
Ask AI about A. Ksenofontov →Frequently Asked Questions
Who are the best alternatives to A. Ksenofontov?▼
The top alternatives to A. Ksenofontov based on AI DNA playing style analysis include: Salvador Blopa, Jeremiah Mensah, Maurizio Brenna, Kiano Dyer, Doni Arifi. 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 A. Ksenofontov in 2026?▼
Players with a similar profile to A. Ksenofontov in 2026 include Salvador Blopa (N/A), Jeremiah Mensah (N/A), Maurizio Brenna (N/A). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does A. Ksenofontov play and who plays similarly?▼
A. Ksenofontov plays as a Midfielder. Players with a comparable positional profile include Salvador Blopa (Portugal, N/A); Jeremiah Mensah (Germany, N/A); Maurizio Brenna (Netherlands, N/A); Kiano Dyer (England, 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.