RisingTransfers
AI DNA Similarity

Best Alternatives to Nicola Zalewski

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

Top 3 Alternatives to Nicola Zalewski

  1. 1.Cristian Volpato88% DNA match·Sassuolo€10.0M
  2. 2.Nicolò Zaniolo87% DNA match·Udinese€13.0M
  3. 3.Alexis Saelemaekers86% DNA match·AC Milan€25.0M

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

RT

Intelligence Verdict

Big ChancesTop 2%
???Bottom 0%

A Creator....

See Full Verdict + Share Card →

Playing Style Analysis

CreatorCreative

A Creator. Statistically, he stands out as an elite creator (2.0 key passes/90), wins the physical battle (57% duel success), creates high-quality scoring opportunities (0.60 big chances/90), heavily involved in play (64 touches/90), draws fouls effectively (2.3/90), active off the ball (2.9 press score/90), contributing to defensive transitions and top 20% creator in the league. The three most similar players to Nicola Zalewski by playing style are:

  • Cristian Volpato(88% match)A Creator. Statistically, he stands out as an elite creator (2.0 key passes/90), a regular goalscorer (0.20 goals/90), a prolific assist provider (0.40 assists/90), creates high-quality scoring opportunities (0.50 big chances/90), heavily involved in play (57 touches/90), active off the ball (2.0 press score/90), contributing to defensive transitions and top 10% creator in the league. However, he loses possession under pressure (2.0 dispossessed/90).
  • Nicolò Zaniolo(87% match)A Creator. Statistically, he stands out as an elite creator (2.7 key passes/90), a constant goal threat (2.9 shots/90), a regular goalscorer (0.21 goals/90), a reliable supplier (0.21 assists/90), heavily involved in play (50 touches/90), draws fouls effectively (2.3/90), active off the ball (2.0 press score/90), contributing to defensive transitions and top 10% creator in the league. However, he loses possession under pressure (2.5 dispossessed/90).
  • Alexis Saelemaekers(86% match)A Box-to-Box. Statistically, he stands out as an elite creator (1.6 key passes/90), an aggressive ball-winner (2.7 tackles/90), wins the physical battle (56% duel success), heavily involved in play (61 touches/90), active off the ball (2.3 press score/90), contributing to defensive transitions and top 10% tackler in the league. Note: this profile is based on 857 minutes of playing time this season.

Transfer Intelligence

Cristian Volpato delivers 88% of the same playing style, at 33% lower cost (€10.0M vs €15.0M), with 1.88 key passes per 90 at age 22.

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

N
Comparison Base
Nicola Zalewski
MidfielderPoland€15.0M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
C
Cristian Volpato
Sassuolo · Serie A
Italy22yContract 2028
KP/901.88
G/900.00
CreatorCreative
vs Zalewski: 2y younger
88% match
€10.0M
#2
N
Nicolò Zaniolo
Udinese · Serie A
Italy26yContract 2026
KP/902.74
G/900.20
CreatorCreative
Last 5: ↑ Hot
vs Zalewski: 2y older
87% match
€13.0M
#3
A
Alexis Saelemaekers
AC Milan · Serie A
Belgium26yContract 2027
KP/901.57
G/900.10
Box-to-BoxCreative
Last 5: ↑ Hot
vs Zalewski: €10M more expensive · 2y older
86% match
€25.0M
#4
T
Tommaso Baldanzi
Genoa · Serie A
Italy23yContract 2028
KP/901.42
G/900.24
Chance Creator
Last 5: ↑ Hot
86% match
€10.0M
#5
T
Tomas Suslov
Hellas Verona · Serie A
Slovakia23yContract 2027
KP/900.48
G/900.00
Creator
Last 5: → Stable
85% match
€5.0M
#6
F
Fabio Miretti
Juventus · Serie A
Italy22yContract 2028
KP/901.68
G/900.34
CreatorCreative
85% match
€16.0M
#7
S
Simone Pafundi
Udinese · Serie A
Italy20yContract 2026
KP/902.55
G/900.23
CreatorCreative
Last 5: ↓ Dip
85% match
€5.0M
#8
N
Nicolò Fagioli
Fiorentina · Serie A
Italy25yContract 2028
KP/902.74
G/900.06
Elite Playmaker
Last 5: ↓ Dip
85% match
€14.0M
#9
J
Jurgen Ekkelenkamp
Udinese · Serie A
Netherlands26yContract 2029
KP/901.41
G/900.19
Creator
Last 5: → Stable
84% match
€7.0M
#10
S
Samuele Ricci
AC Milan · Serie A
Italy24yContract 2029
KP/901.61
G/900.00
Ball-WinnerCreative
Last 5: ↑ Hot
84% match
€25.0M
#11
B
Bryan Cristante
Roma · Serie A
Italy31yContract 2027
KP/900.88
G/900.05
Metronome
Last 5: ↓ Dip
84% match
€7.0M
#12
C
Charles De Ketelaere
Atalanta · Serie A
Belgium25yContract 2028
KP/902.53
G/900.06
CreatorCreative
Last 5: → Stable
83% match
€35.0M

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 Nicola Zalewski.

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Frequently Asked Questions

Who are the best alternatives to Nicola Zalewski?
The top alternatives to Nicola Zalewski based on AI DNA playing style analysis include: Cristian Volpato, Nicolò Zaniolo, Alexis Saelemaekers, Tommaso Baldanzi, Tomas Suslov. 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 Nicola Zalewski in 2026?
Players with a similar profile to Nicola Zalewski in 2026 include Cristian Volpato (€10.0M), Nicolò Zaniolo (€13.0M), Alexis Saelemaekers (€25.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Nicola Zalewski play and who plays similarly?
Nicola Zalewski plays as a Midfielder. Players with a comparable positional profile include Cristian Volpato (Italy, €10.0M); Nicolò Zaniolo (Italy, €13.0M); Alexis Saelemaekers (Belgium, €25.0M); Tommaso Baldanzi (Italy, €10.0M).
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.