RisingTransfers
AI DNA Similarity

Best Alternatives to Pepê

Players most similar to Pepê (Midfielder, €1.5M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Pepê

  1. 1.Pepelu86% DNA match·Valencia€9.0M
  2. 2.Tommaso Pobega86% DNA match·Bologna€9.0M
  3. 3.Jari Vandeputte84% DNA match·Cremonese€3.3M

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

RT

Intelligence Verdict

Press IntensityTop 3%
???Bottom 5%

A Ball-Winner....

See Full Verdict + Share Card →

Playing Style Analysis

Ball-WinnerDefensiveSmall Sample

A Ball-Winner. Statistically, he stands out as an aggressive ball-winner (3.3 tackles/90), wins the physical battle (60% duel success), wins the ball cleanly (2.2 successful tackles/90), heavily involved in play (60 touches/90), draws fouls effectively (2.6/90), a high-intensity presser (press score 3.4/90), constantly disrupting opposition build-up and top 10% tackler in the league. However, he prone to committing fouls (3.0/90). The three most similar players to Pepê by playing style are:

  • Pepelu(86% match)A Ball-Winner. Statistically, he stands out as an aggressive ball-winner (2.7 tackles/90), meticulous in distribution (87% pass accuracy), wins the physical battle (61% duel success), penetrates with forward passing (9.4 final-third passes/90), central to possession (72 touches/90), uses long balls frequently (7.2/90) and active off the ball (2.9 press score/90), contributing to defensive transitions.
  • Tommaso Pobega(86% match)Pobega is the midfielder who wins the ball before the danger exists—a defensive instinct so sharp his interception rate lands in Serie A's top 10%, a figure that quietly separates him from most midfielders who simply react. His aerial dominance (top 20%) and tackle success (top 20%) confirm a player built for the physical confrontations modern pressing football demands. The counterintuitive read here: his modest 0.17 goals per 90 actually places him in the top 30% of Serie A midfielders, meaning he contributes more in front of goal than his limited minutes suggest.
  • Jari Vandeputte(84% match)A Creator. Statistically, he stands out as an elite creator (3.0 key passes/90), a prolific assist provider (0.29 assists/90), creates high-quality scoring opportunities (0.68 big chances/90), penetrates with forward passing (9.7 final-third passes/90), heavily involved in play (70 touches/90), uses long balls frequently (6.1/90), active off the ball (2.5 press score/90), contributing to defensive transitions and top 10% creator in the league.

Transfer Intelligence

Pepelu delivers 86% of the same playing style, at a 500% premium over Pepê, with 0.88 key passes per 90 at age 27.

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

P
Comparison Base
Pepê
MidfielderBrazil€1.5M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
P
Pepelu
Valencia · La Liga
Spain27yContract 2028
KP/900.88
G/900.10
Ball-WinnerDefensive
Last 5: ↓ Dip
vs Pepê: €8M more expensive
86% match
€9.0M
#2
T
Tommaso Pobega
Bologna · Serie A
Italy26yContract 2026
KP/900.36
G/900.18
Balanced Midfielder
Last 5: ↑ Hot
vs Pepê: €8M more expensive · 2y younger
86% match
€9.0M
#3
J
Jari Vandeputte
Cremonese · Serie A
Belgium30y
KP/903.00
G/900.00
CreatorCreative
vs Pepê: 2y older
84% match
€3.3M
#4
M
Michel Adopo
Cagliari · Serie A
France25yContract 2029
KP/900.80
G/900.06
Balanced Midfielder
Last 5: ↑ Hot
85% match
€6.0M
#5
M
Máximo Perrone
Como · Serie A
Argentina23yContract 2029
KP/900.93
G/900.17
Metronome
Last 5: → Stable
85% match
€25.0M
#6
A
Antoine Bernede
Hellas Verona · Serie A
France26yContract 2028
KP/901.26
G/900.07
CreatorDefensive
84% match
€3.5M
#7
É
Éderson
Atalanta · Serie A
Brazil26yContract 2027
KP/901.04
G/900.07
Metronome
Last 5: → Stable
84% match
€40.0M
#8
M
Mandela Keita
Parma · Serie A
Belgium24yContract 2029
KP/900.34
G/900.07
Ball-WinnerDefensive
83% match
€12.0M
#9
P
Patrizio Masini
Genoa · Serie A
Italy25yContract 2028
KP/900.84
G/900.00
Ball-WinnerDefensive
Last 5: → Stable
84% match
€6.0M
#10
L
Luis Henrique
Inter · Serie A
Brazil24yContract 2030
KP/901.31
G/900.00
Creator
Last 5: → Stable
83% match
€23.0M
#11
A
Amir Richardson
FC København · Serie A
France24yContract 2026
KP/900.65
G/900.09
Box-to-BoxDefensive
Last 5: ↓ Dip
82% match
€9.0M
#12
M
Manuel Locatelli
Juventus · Serie A
Italy28yContract 2028
KP/901.88
G/900.00
MetronomeDefensive
Last 5: ↓ Dip
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 Pepê.

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Frequently Asked Questions

Who are the best alternatives to Pepê?
The top alternatives to Pepê based on AI DNA playing style analysis include: Pepelu, Tommaso Pobega, Jari Vandeputte, Michel Adopo, Máximo Perrone. 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 Pepê in 2026?
Players with a similar profile to Pepê in 2026 include Pepelu (€9.0M), Tommaso Pobega (€9.0M), Jari Vandeputte (€3.3M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Pepê play and who plays similarly?
Pepê plays as a Midfielder. Players with a comparable positional profile include Pepelu (Spain, €9.0M); Tommaso Pobega (Italy, €9.0M); Jari Vandeputte (Belgium, €3.3M); Michel Adopo (France, €6.0M).
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.