RisingTransfers
AI DNA Similarity

Best Alternatives to Simone Pafundi

Players most similar to Simone Pafundi (Midfielder, €5.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Simone Pafundi

  1. 1.Cristian Volpato88% DNA match·Sassuolo€10.0M
  2. 2.Fabio Miretti87% DNA match·Juventus€16.0M
  3. 3.Nico Paz86% DNA match·Como€65.0M

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

RT

Intelligence Verdict

ShotsTop 3%

A Creator....

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Playing Style Analysis

CreatorCreative

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). The three most similar players to Simone Pafundi 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).
  • Fabio Miretti(87% match)Miretti is the rare academy product who graduated from Juventus's shadow and found his voice in the chaos of a mid-table Serie A environment. At just 544 minutes of data, the sample is partial—but what it reveals is striking. His assists rate lands in the top 5% of Serie A midfielders, a figure that flatters him only if you ignore the equally elite press intensity and shot volume sitting underneath it.
  • Nico Paz(86% match)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.

Transfer Intelligence

Cristian Volpato delivers 88% of the same playing style, at a 100% premium over Simone Pafundi, 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 →

S
Comparison Base
Simone Pafundi
MidfielderItaly€5.0M
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 Pafundi: 2y older
88% match
€10.0M
#2
F
Fabio Miretti
Juventus · Serie A
Italy22yContract 2028
KP/901.68
G/900.34
CreatorCreative
vs Pafundi: €11M more expensive · 2y older
87% match
€16.0M
#3
N
Nico Paz
Como · Serie A
Argentina21yContract 2028
KP/901.46
G/900.35
CreatorDefensive
Last 5: → Stable
vs Pafundi: €60M more expensive
86% match
€65.0M
#4
F
Facundo Buonanotte
Leeds United · Premier League
Argentina21yContract 2026
KP/901.49
G/900.37
Ball-WinnerDefensive
86% match
€18.0M
#5
J
Jari Vandeputte
Cremonese · Serie A
Belgium30y
KP/903.00
G/900.00
CreatorCreative
85% match
€3.3M
#6
M
Martin Baturina
Como · Serie A
Croatia23yContract 2030
KP/904.11
G/900.51
CreatorCreative
Last 5: → Stable
85% match
€18.0M
#7
M
Máximo Perrone
Como · Serie A
Argentina23yContract 2029
KP/900.93
G/900.17
Metronome
Last 5: → Stable
85% match
€25.0M
#8
N
Nicola Zalewski
Atalanta · Serie A
Poland24yContract 2029
KP/901.98
G/900.00
CreatorCreative
Last 5: ↓ Dip
85% match
€15.0M
#9
N
Nicolò Fagioli
Fiorentina · Serie A
Italy25yContract 2028
KP/902.74
G/900.06
Elite Playmaker
Last 5: ↓ Dip
85% match
€14.0M
#10
C
Charles De Ketelaere
Atalanta · Serie A
Belgium25yContract 2028
KP/902.53
G/900.06
CreatorCreative
Last 5: → Stable
84% match
€35.0M
#11
S
Samuele Ricci
AC Milan · Serie A
Italy24yContract 2029
KP/901.61
G/900.00
Ball-WinnerCreative
Last 5: ↑ Hot
85% match
€25.0M
#12
M
Matteo Tramoni
Pisa · Serie A
France26yContract 2026
KP/902.56
G/900.23
CreatorCreative
85% match
€3.0M

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 Simone Pafundi.

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Frequently Asked Questions

Who are the best alternatives to Simone Pafundi?
The top alternatives to Simone Pafundi based on AI DNA playing style analysis include: Cristian Volpato, Fabio Miretti, Nico Paz, Facundo Buonanotte, Jari Vandeputte. 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 Simone Pafundi in 2026?
Players with a similar profile to Simone Pafundi in 2026 include Cristian Volpato (€10.0M), Fabio Miretti (€16.0M), Nico Paz (€65.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Simone Pafundi play and who plays similarly?
Simone Pafundi plays as a Midfielder. Players with a comparable positional profile include Cristian Volpato (Italy, €10.0M); Fabio Miretti (Italy, €16.0M); Nico Paz (Argentina, €65.0M); Facundo Buonanotte (Argentina, €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.