RisingTransfers
AI DNA Similarity

Best Alternatives to Miguel Román

Players most similar to Miguel Román (Midfielder, €2.5M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Miguel Román

  1. 1.Ander Guevara87% DNA match·Deportivo Alavés€3.0M
  2. 2.Marc Aguado86% DNA match·Elche€3.0M
  3. 3.Edu Expósito86% DNA match·Espanyol€4.0M

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

RT

Intelligence Verdict

Big ChancesTop 25%
???Bottom 0%

A Creator....

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Playing Style Analysis

Creator

A Creator. Statistically, he stands out as a capable chance creator (1.3 key passes/90), active in the tackle (2.2 tackles/90), meticulous in distribution (87% pass accuracy), penetrates with forward passing (8.0 final-third passes/90), heavily involved in play (64 touches/90), uses long balls frequently (6.2/90) and active off the ball (2.5 press score/90), contributing to defensive transitions. The three most similar players to Miguel Román by playing style are:

  • Ander Guevara(87% match)A Metronome. Statistically, he stands out as a capable chance creator (1.1 key passes/90), a reliable supplier (0.18 assists/90), active in the tackle (1.8 tackles/90), central to possession (76 touches/90), switches play with precision (5.6 long balls/90, 61% accuracy) and a high-intensity presser (press score 3.0/90), constantly disrupting opposition build-up. However, he can be exposed in 1v1 situations and loses possession under pressure (1.6 dispossessed/90).
  • Marc Aguado(86% match)A Ball-Winner. Statistically, he stands out as active in the tackle (1.9 tackles/90), reads the game exceptionally (1.8 interceptions/90), meticulous in distribution (91% pass accuracy), wins the physical battle (63% duel success), heavily involved in play (57 touches/90) and active off the ball (2.2 press score/90), contributing to defensive transitions.
  • Edu Expósito(86% match)A Box-to-Box. Statistically, he stands out as an elite creator (3.2 key passes/90), a prolific assist provider (0.27 assists/90), active in the tackle (1.8 tackles/90), wins the physical battle (55% duel success), creates high-quality scoring opportunities (0.55 big chances/90), delivers dangerous crosses (2.6 accurate crosses/90), penetrates with forward passing (8.9 final-third passes/90), heavily involved in play (60 touches/90), uses long balls frequently (5.4/90), active off the ball (2.4 press score/90), contributing to defensive transitions and top 10% creator in the league.

Transfer Intelligence

Ander Guevara delivers 87% of the same playing style, at a 20% premium over Miguel Román, with 1.08 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 →

M
Comparison Base
Miguel Román
MidfielderSpain€2.5M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
A
Ander Guevara
Deportivo Alavés · La Liga
Spain28yContract 2027
KP/901.08
G/900.18
MetronomeSmall Sample
Last 5: ↑ Hot
vs Román: 5y older
87% match
€3.0M
#2
M
Marc Aguado
Elche · La Liga
Spain26yContract 2027
KP/900.31
G/900.00
Ball-Winner
Last 5: ↑ Hot
vs Román: 3y older
86% match
€3.0M
#3
E
Edu Expósito
Espanyol · La Liga
Spain29yContract 2027
KP/903.18
G/900.00
Box-to-BoxCreative
Last 5: → Stable
vs Román: 6y older
86% match
€4.0M
#4
S
Santi Comesaña
Villarreal · La Liga
Spain29yContract 2028
KP/900.73
G/900.10
Box-to-Box
Last 5: → Stable
85% match
€8.0M
#5
A
Aleix Febas
Elche · La Liga
Spain30yContract 2026
KP/900.61
G/900.08
Metronome
Last 5: → Stable
85% match
€5.0M
#6
F
Fran Beltrán
Girona · La Liga
Spain27yContract 2026
KP/900.38
G/900.19
MetronomeDefensive
Last 5: → Stable
86% match
€5.0M
#7
A
Aleix García
Bayer 04 Leverkusen · Bundesliga
Spain28yContract 2026
KP/900.72
G/900.18
MetronomeSmall Sample
Last 5: ↑ Hot
85% match
€20.0M
#8
F
Federico Redondo
Elche · La Liga
Argentina23yContract 2030
KP/901.09
G/900.27
Chance CreatorDeep Distributor
85% match
€4.0M
#9
M
Marc Casadó
FC Barcelona · La Liga
Spain22yContract 2028
KP/901.10
G/900.00
MetronomeSmall Sample
Last 5: ↓ Dip
85% match
€25.0M
#10
I
Iván Martín
Girona · La Liga
Spain27yContract 2028
KP/900.66
G/900.00
Box-to-BoxDefensive
Last 5: ↓ Dip
85% match
€6.0M
#11
P
Pol Lozano
Espanyol · La Liga
Spain26yContract 2027
KP/900.94
G/900.07
Balanced Midfielder
Last 5: ↑ Hot
85% match
€6.0M
#12
A
Antonio Blanco
Deportivo Alavés · La Liga
Spain25yContract 2027
KP/900.62
G/900.08
Ball-WinnerDefensive
Last 5: ↑ Hot
84% match
€10.0M

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 Miguel Román.

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Frequently Asked Questions

Who are the best alternatives to Miguel Román?
The top alternatives to Miguel Román based on AI DNA playing style analysis include: Ander Guevara, Marc Aguado, Edu Expósito, Santi Comesaña, Aleix Febas. 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 Miguel Román in 2026?
Players with a similar profile to Miguel Román in 2026 include Ander Guevara (€3.0M), Marc Aguado (€3.0M), Edu Expósito (€4.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Miguel Román play and who plays similarly?
Miguel Román plays as a Midfielder. Players with a comparable positional profile include Ander Guevara (Spain, €3.0M); Marc Aguado (Spain, €3.0M); Edu Expósito (Spain, €4.0M); Santi Comesaña (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.