RisingTransfers
AI DNA Similarity

Best Alternatives to Nico Paz

Players most similar to Nico Paz (Midfielder, €65.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Nico Paz

  1. 1.Simone Pafundi86% DNA match·Udinese€5.0M
  2. 2.Mario Pašalić84% DNA match·Atalanta€7.0M
  3. 3.Cristian Volpato84% DNA match·Sassuolo€10.0M

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

RT

Intelligence Verdict

ShotsTop 0%

A Creator....

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Playing Style Analysis

CreatorDefensive

A Creator. Statistically, he stands out as naturally left-footed, a capable chance creator (1.5 key passes/90), a constant goal threat (3.9 shots/90), a regular goalscorer (0.35 goals/90), a dynamic dribbler (2.0/90), an aggressive ball-winner (2.9 tackles/90), wins the physical battle (56% duel success), wins the ball cleanly (2.0 successful tackles/90), heavily involved in play (67 touches/90), active off the ball (2.5 press score/90), contributing to defensive transitions and top 10% tackler in the league. The three most similar players to Nico Paz by playing style are:

  • Simone Pafundi(86% match)A Creator. Statistically, he stands out as an elite creator (2.4 key passes/90), a constant goal threat (3.8 shots/90), a prolific assist provider (0.26 assists/90), heavily involved in play (56 touches/90), draws fouls effectively (2.8/90), active off the ball (2.3 press score/90), contributing to defensive transitions and top 10% creator in the league. However, he loses possession under pressure (1.6 dispossessed/90).
  • Mario Pašalić(84% 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.
  • Cristian Volpato(84% 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).

Transfer Intelligence

Simone Pafundi delivers 86% of the same playing style, at 92% lower cost (€5.0M vs €65.0M), with 2.55 key passes per 90 at age 20.

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

N
Comparison Base
Nico Paz
MidfielderArgentina€65.0M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
S
Simone Pafundi
Udinese · Serie A
Italy20yContract 2026
KP/902.55
G/900.23
CreatorCreative
Last 5: ↓ Dip
vs Paz: €60M cheaper
86% match
€5.0M
#2
M
Mario Pašalić
Atalanta · Serie A
Croatia31yContract 2028
KP/901.75
G/900.10
Creative Playmaker
Last 5: ↓ Dip
vs Paz: €58M cheaper · 10y older
84% match
€7.0M
#3
C
Cristian Volpato
Sassuolo · Serie A
Italy22yContract 2028
KP/901.88
G/900.00
CreatorCreative
vs Paz: €55M cheaper
84% match
€10.0M
#4
M
Martin Baturina
Como · Serie A
Croatia23yContract 2030
KP/904.11
G/900.51
CreatorCreative
Last 5: → Stable
82% match
€18.0M
#5
A
Andrea Cambiaso
Juventus · Serie A
Italy26yContract 2029
KP/902.38
G/900.00
CreatorCreative
Last 5: ↑ Hot
82% match
€30.0M
#6
T
Tommaso Baldanzi
Genoa · Serie A
Italy23yContract 2028
KP/901.42
G/900.24
Chance Creator
Last 5: ↑ Hot
83% match
€10.0M
#7
F
Fabio Miretti
Juventus · Serie A
Italy22yContract 2028
KP/901.68
G/900.34
CreatorCreative
83% match
€16.0M
#8
S
Samuele Ricci
AC Milan · Serie A
Italy24yContract 2029
KP/901.61
G/900.00
Ball-WinnerCreative
Last 5: ↑ Hot
83% match
€25.0M
#9
A
Alexis Saelemaekers
AC Milan · Serie A
Belgium26yContract 2027
KP/901.57
G/900.10
Box-to-BoxCreative
Last 5: ↑ Hot
82% match
€25.0M
#10
L
Lennon Miller
Udinese · Serie A
Scotland19yContract 2030
KP/901.22
G/900.00
Box-to-BoxDefensive
Last 5: ↑ Hot
83% match
€8.0M
#11
N
Nicolò Fagioli
Fiorentina · Serie A
Italy25yContract 2028
KP/902.74
G/900.06
Elite Playmaker
Last 5: ↓ Dip
82% match
€14.0M
#12
M
Máximo Perrone
Como · Serie A
Argentina23yContract 2029
KP/900.93
G/900.17
Metronome
Last 5: → Stable
82% match
€25.0M

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 Nico Paz.

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Frequently Asked Questions

Who are the best alternatives to Nico Paz?
The top alternatives to Nico Paz based on AI DNA playing style analysis include: Simone Pafundi, Mario Pašalić, Cristian Volpato, Martin Baturina, Andrea Cambiaso. 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 Nico Paz in 2026?
Players with a similar profile to Nico Paz in 2026 include Simone Pafundi (€5.0M), Mario Pašalić (€7.0M), Cristian Volpato (€10.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Nico Paz play and who plays similarly?
Nico Paz plays as a Midfielder. Players with a comparable positional profile include Simone Pafundi (Italy, €5.0M); Mario Pašalić (Croatia, €7.0M); Cristian Volpato (Italy, €10.0M); Martin Baturina (Croatia, €18.0M).
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.