RisingTransfers
AI DNA Similarity

Best Alternatives to Gustavo Cuéllar

Players most similar to Gustavo Cuéllar (Midfielder, €1.4M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Gustavo Cuéllar

  1. 1.Federico Redondo85% DNA match·Elche€4.0M
  2. 2.Marc Aguado84% DNA match·Elche€3.0M
  3. 3.Carlos Dotor84% DNA match·Málaga€3.0M

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

RT

Intelligence Verdict

Chances MissedTop 0%
???Bottom 2%

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 (3.1 tackles/90), meticulous in distribution (92% pass accuracy), wins the physical battle (57% duel success), wins the ball cleanly (2.4 successful tackles/90), central to possession (72 touches/90) and a high-intensity presser (press score 3.5/90), constantly disrupting opposition build-up. Note: this profile is based on 879 minutes of playing time this season. The three most similar players to Gustavo Cuéllar by playing style are:

  • Federico Redondo(85% match)Redondo is the quintessential "volume controller" whose surgical distribution and relentless defensive work rate suggest a player far more physically imposing than his duel success rate implies. Operating at a Tier C club, he is effectively the entire engine room, ranking in the top 5% for both passes per 90 (84.3) and tackles won (1.91), a rare statistical profile that combines the elegance of a deep-lying playmaker with the grit of a ball-winner. The counterintuitive insight lies in his goalscoring; despite sitting in the bottom 10% for shot volume, his 0.27 goals per 90 (top 5%) reveals a lethal efficiency when he does arrive late in the box.
  • Marc Aguado(84% 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.
  • Carlos Dotor(84% match)A Box-to-Box. Statistically, he stands out as an elite creator (1.8 key passes/90), meticulous in distribution (86% pass accuracy), heavily involved in play (60 touches/90), active off the ball (2.2 press score/90), contributing to defensive transitions and top 20% creator in the league.

Transfer Intelligence

Federico Redondo delivers 85% of the same playing style, at a 186% premium over Gustavo Cuéllar, with 1.09 key passes per 90 at age 23.

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

G
Comparison Base
Gustavo Cuéllar
MidfielderColombia€1.4M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
F
Federico Redondo
Elche · La Liga
Argentina23yContract 2030
KP/901.09
G/900.27
Chance CreatorDeep Distributor
vs Cuéllar: 10y younger
85% match
€4.0M
#2
M
Marc Aguado
Elche · La Liga
Spain26yContract 2027
KP/900.31
G/900.00
Ball-Winner
Last 5: ↑ Hot
vs Cuéllar: 7y younger
84% match
€3.0M
#3
C
Carlos Dotor
Málaga · La Liga
Spain25yContract 2026
KP/901.29
G/900.00
Box-to-BoxCreative
Last 5: ↑ Hot
vs Cuéllar: 8y younger
84% match
€3.0M
#4
A
Ander Guevara
Deportivo Alavés · La Liga
Spain28yContract 2027
KP/901.08
G/900.18
MetronomeSmall Sample
Last 5: ↑ Hot
84% match
€3.0M
#5
S
Sergi Darder
Mallorca · La Liga
Spain32yContract 2028
KP/902.22
G/900.00
CreatorCreative
Last 5: ↑ Hot
83% match
€3.5M
#6
M
Manu Trigueros
Granada · La Liga
Spain34yContract 2026
KP/900.00
G/900.00
MetronomeSmall Sample
83% match
N/A
#7
S
Santiago Colombatto
Real Oviedo · La Liga
Argentina29yContract 2026
KP/901.23
G/900.00
Box-to-Box
Last 5: → Stable
84% match
€3.0M
#8
D
Danilo Cataldi
Lazio · Serie A
Italy31yContract 2027
KP/901.06
G/900.14
Ball-Winner
83% match
€3.5M
#9
J
Josh Cullen
Burnley · Premier League
Republic of Ireland30yContract 2027
KP/900.77
G/900.12
Balanced Midfielder
83% match
€6.0M
#10
M
Michel Aebischer
Pisa · Serie A
Switzerland29yContract 2026
KP/901.05
G/900.00
Balanced Midfielder
Last 5: ↑ Hot
83% match
€4.0M
#11
S
Salih Özcan
Borussia Dortmund · Bundesliga
Turkey28yContract 2026
KP/901.26
G/900.00
MetronomeSmall Sample
83% match
€3.5M
#12
R
Remo Freuler
Bologna · Serie A
Switzerland34yContract 2026
KP/900.83
G/900.00
Chance Creator
Last 5: → Stable
83% match
€4.0M

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 Gustavo Cuéllar.

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Frequently Asked Questions

Who are the best alternatives to Gustavo Cuéllar?
The top alternatives to Gustavo Cuéllar based on AI DNA playing style analysis include: Federico Redondo, Marc Aguado, Carlos Dotor, Ander Guevara, Sergi Darder. 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 Gustavo Cuéllar in 2026?
Players with a similar profile to Gustavo Cuéllar in 2026 include Federico Redondo (€4.0M), Marc Aguado (€3.0M), Carlos Dotor (€3.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Gustavo Cuéllar play and who plays similarly?
Gustavo Cuéllar plays as a Midfielder. Players with a comparable positional profile include Federico Redondo (Argentina, €4.0M); Marc Aguado (Spain, €3.0M); Carlos Dotor (Spain, €3.0M); Ander Guevara (Spain, €3.0M).
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.