AI DNA Similarity
Best Alternatives to Igor Savic
Players most similar to Igor Savic (Midfielder, €500K) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.
Top 3 Alternatives to Igor Savic
- 1.Salvador Blopa86% DNA match·Sporting CP
- 2.Maurizio Brenna84% DNA match·Katwijk
- 3.Jeremiah Mensah82% DNA match·Bayer 04 Leverkusen
Ranked by AI DNA similarity — 768 dimensions across playing style, pressing intensity, and tactical fit.
RT
Intelligence Verdict
InterceptionsTop 2%
???Bottom 0%
“Igor Savić is a Midfielder....”
See Full Verdict + Share Card →Playing Style Analysis
Small Sample
Igor Savić is a Midfielder. Solid midfield option. (Limited sample: 270 mins) The three most similar players to Igor Savic by playing style are:
- Salvador Blopa(86% match) — Salvador Blopa is a Midfielder. Solid midfield option. (Limited sample: 270 mins)
- Maurizio Brenna(84% match) — Maurizio Brenna is a Midfielder. Solid midfield option. (Limited sample: 299 mins)
- Jeremiah Mensah(82% match) — Jeremiah Dennit Mensah is a Midfielder. Solid midfield option. (Limited sample: 327 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 Savic: 7y younger
86% match
N/A
#2
M
Maurizio Brenna
Katwijk · Eredivisie
Netherlands27y
KP/900.00
G/900.00
Small Sample
vs Savic: 2y older
84% match
N/A
#3
J
Jeremiah Mensah
Bayer 04 Leverkusen · Bundesliga
Germany18y
KP/900.00
G/900.00
Small Sample
vs Savic: 7y younger
82% match
N/A
#4
D
Doni Arifi
SpVgg Greuther Fürth · Bundesliga
Finland24y
KP/901.12
G/900.00
Small Sample
Last 5: ↓ Dip82% match
N/A
#5
G
Gerry Vlak
Koninklijke HFC · Eredivisie
Netherlands30y
KP/900.00
G/900.00
Small Sample
82% match
N/A
#6
R
Rick van der Meer
Katwijk · Eredivisie
Netherlands28y
KP/900.00
G/900.00
Small Sample
81% match
N/A
#7
K
Kiano Dyer
FC Volendam · Eredivisie
England19y
KP/900.00
G/900.00
Small Sample
81% match
N/A
#8
D
Daniel Bisgard Haarbo
Fredericia · Superliga
Denmark23y
KP/900.00
G/900.31
Small Sample
81% match
N/A
#9
U
Ulrich Taffertshofer
Atlético Baleares · La Liga
Germany34yContract 2026
KP/900.00
G/900.00
81% match
N/A
#10
L
Luka Ivanušec
PAOK · Eredivisie
Croatia27y
KP/901.96
G/900.00
Box-to-BoxSmall Sample
Last 5: ↓ Dip80% match
€8.5M
#11
N
Noah Fenyö
Eintracht Frankfurt · Bundesliga
Hungary20yContract 2029
KP/900.26
G/900.52
Small Sample
81% match
N/A
#12
Y
Yanis Khafi
Paris Saint Germain · Ligue 1
France20y
KP/901.18
G/900.00
Small Sample
81% match
N/A
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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 Igor Savic.
Ask AI about Igor Savic →Frequently Asked Questions
Who are the best alternatives to Igor Savic?▼
The top alternatives to Igor Savic based on AI DNA playing style analysis include: Salvador Blopa, Maurizio Brenna, Jeremiah Mensah, Doni Arifi, Gerry Vlak. 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 Igor Savic in 2026?▼
Players with a similar profile to Igor Savic in 2026 include Salvador Blopa (N/A), Maurizio Brenna (N/A), Jeremiah Mensah (N/A). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Igor Savic play and who plays similarly?▼
Igor Savic plays as a Midfielder. Players with a comparable positional profile include Salvador Blopa (Portugal, N/A); Maurizio Brenna (Netherlands, N/A); Jeremiah Mensah (Germany, N/A); Doni Arifi (Finland, 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.