RisingTransfers
AI DNA Similarity

Best Alternatives to Nikola Vlašić

Players most similar to Nikola Vlašić (Midfielder, €9.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Nikola Vlašić

  1. 1.Sandi Lovrić89% DNA match·Hellas Verona€6.0M
  2. 2.Petar Sučić88% DNA match·Inter€30.0M
  3. 3.Mario Pašalić88% DNA match·Atalanta€7.0M

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

RT

Intelligence Verdict

Chances MissedTop 0%

A Creator....

See Full Verdict + Share Card →

Playing Style Analysis

CreatorCreative

A Creator. Statistically, he stands out as an elite creator (1.6 key passes/90), a regular goalscorer (0.20 goals/90), active in the tackle (1.9 tackles/90), heavily involved in play (50 touches/90) and active off the ball (2.6 press score/90), contributing to defensive transitions. The three most similar players to Nikola Vlašić by playing style are:

  • Sandi Lovrić(89% match)A Creator. Statistically, he stands out as a capable chance creator (1.2 key passes/90), active in the tackle (1.9 tackles/90), meticulous in distribution (85% pass accuracy), heavily involved in play (52 touches/90) and active off the ball (2.3 press score/90), contributing to defensive transitions.
  • Petar Sučić(88% match)Sučić has quietly built a case as one of Serie A's more quietly effective midfield operators — a Croatian with a continental pedigree who does more with the ball than his modest goal contributions suggest. His 52.2 passes per 90 places him in the league's top 20%, and that volume carries real quality: 87.9% accuracy, 6.36 progressive passes into the final third, and 1.50 key passes per 90 all land in the top tier. Here's the counterintuitive part — his 1.09 tackles won per 90 sits in the top 30%, yet his overall duel win rate is below average, meaning he picks his battles intelligently rather than throwing himself into everything.
  • Mario Pašalić(88% match)Pašalić has quietly become one of Serie A's most efficient midfield connectors — a player whose value lives entirely in the spaces between the headlines. His pass accuracy sits in the top 10% of the league, but the more telling number is his 64 passes per 90, which ranks in the top 5% — this isn't a man recycling possession sideways, it's a midfielder who genuinely orchestrates. His 0.22 assists per 90 (top 10%) confirms the end product follows the volume.

Transfer Intelligence

Sandi Lovrić delivers 89% of the same playing style, at 33% lower cost (€6.0M vs €9.0M), with 0.94 key passes per 90 at age 28.

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

N
Comparison Base
Nikola Vlašić
MidfielderCroatia€9.0M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
S
Sandi Lovrić
Hellas Verona · Serie A
Slovenia28yContract 2027
KP/900.94
G/900.00
Creator
89% match
€6.0M
#2
P
Petar Sučić
Inter · Serie A
Croatia22yContract 2030
KP/900.90
G/900.15
Creative Playmaker
Last 5: ↑ Hot
vs Vlašić: €21M more expensive · 6y younger
88% match
€30.0M
#3
M
Mario Pašalić
Atalanta · Serie A
Croatia31yContract 2028
KP/901.75
G/900.10
Creative Playmaker
Last 5: ↓ Dip
vs Vlašić: 3y older
88% match
€7.0M
#4
P
Pablo Fornals
Real Betis · La Liga
Spain30yContract 2029
KP/902.63
G/900.25
CreatorCreative
Last 5: → Stable
85% match
€8.0M
#5
L
Lazar Samardžić
Atalanta · Serie A
Germany24yContract 2029
KP/902.64
G/900.22
CreatorCreative
Last 5: → Stable
85% match
€15.0M
#6
L
Luka Modrić
AC Milan · Serie A
Croatia40yContract 2026
KP/901.48
G/900.00
MetronomeSmall Sample
Last 5: → Stable
84% match
€4.0M
#7
L
Luka Ivanušec
PAOK · Eredivisie
Croatia27y
KP/901.96
G/900.00
Box-to-BoxSmall Sample
Last 5: ↓ Dip
84% match
€8.5M
#8
I
Ivan Ilić
Torino · Serie A
Serbia25yContract 2027
KP/901.73
G/900.00
Creative Playmaker
85% match
€10.0M
#9
M
Martin Baturina
Como · Serie A
Croatia23yContract 2030
KP/904.11
G/900.51
CreatorCreative
Last 5: → Stable
84% match
€18.0M
#10
W
Weston McKennie
Juventus · Serie A
United States27yContract 2026
KP/901.59
G/900.28
Creator
Last 5: → Stable
84% match
€22.0M
#11
M
Manuel Locatelli
Juventus · Serie A
Italy28yContract 2028
KP/901.88
G/900.00
MetronomeDefensive
Last 5: ↓ Dip
84% match
€25.0M
#12
K
Kristjan Asllani
Beşiktaş · Serie A
Albania24yContract 2026
KP/900.99
G/900.22
Ball-WinnerSmall Sample
Last 5: → Stable
84% match
€13.0M

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 Nikola Vlašić.

Ask AI about Nikola Vlašić

Frequently Asked Questions

Who are the best alternatives to Nikola Vlašić?
The top alternatives to Nikola Vlašić based on AI DNA playing style analysis include: Sandi Lovrić, Petar Sučić, Mario Pašalić, Pablo Fornals, Lazar Samardžić. 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 Nikola Vlašić in 2026?
Players with a similar profile to Nikola Vlašić in 2026 include Sandi Lovrić (€6.0M), Petar Sučić (€30.0M), Mario Pašalić (€7.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Nikola Vlašić play and who plays similarly?
Nikola Vlašić plays as a Midfielder. Players with a comparable positional profile include Sandi Lovrić (Slovenia, €6.0M); Petar Sučić (Croatia, €30.0M); Mario Pašalić (Croatia, €7.0M); Pablo Fornals (Spain, €8.0M).
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.