RisingTransfers
AI DNA Similarity

Best Alternatives to Moisés Caicedo

Players most similar to Moisés Caicedo (Midfielder, €110.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Moisés Caicedo

  1. 1.Martín Zubimendi87% DNA match·Arsenal€80.0M
  2. 2.Roméo Lavia88% DNA match·Chelsea€30.0M
  3. 3.Enzo Fernández86% DNA match·Chelsea€90.0M

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

RT

Intelligence Verdict

Press IntensityTop 3%

A Ball-Winner....

See Full Verdict + Share Card →

Playing Style Analysis

Ball-WinnerDefensive

A Ball-Winner. Statistically, he stands out as an aggressive ball-winner (3.0 tackles/90), reads the game exceptionally (1.9 interceptions/90), meticulous in distribution (92% pass accuracy), wins the physical battle (56% duel success), heavily involved in possession (66 passes/90), central to possession (81 touches/90) and a high-intensity presser (press score 3.4/90), constantly disrupting opposition build-up. The three most similar players to Moisés Caicedo by playing style are:

  • Martín Zubimendi(87% match)A Metronome. Statistically, he stands out as active in the tackle (2.1 tackles/90), meticulous in distribution (88% pass accuracy), wins the physical battle (60% duel success), heavily involved in play (69 touches/90) and active off the ball (2.1 press score/90), contributing to defensive transitions.
  • Roméo Lavia(88% match)A Box-to-Box. Statistically, he stands out as active in the tackle (2.5 tackles/90), reads the game exceptionally (1.8 interceptions/90), meticulous in distribution (92% pass accuracy), heavily involved in play (59 touches/90) and active off the ball (2.8 press score/90), contributing to defensive transitions. Note: this profile is based on 803 minutes of playing time this season.
  • Enzo Fernández(86% match)A Creator. Statistically, he stands out as an elite creator (2.0 key passes/90), a regular goalscorer (0.28 goals/90), meticulous in distribution (87% pass accuracy), penetrates with forward passing (8.5 final-third passes/90), central to possession (76 touches/90) and top 10% creator in the league.

Transfer Intelligence

Martín Zubimendi delivers 87% of the same playing style, at 27% lower cost (€80.0M vs €110.0M), with 0.59 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 →

M
Comparison Base
Moisés Caicedo
MidfielderEcuador€110.0M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
M
Martín Zubimendi
Arsenal · Premier League
Spain27yContract 2030
KP/900.59
G/900.15
Metronome
Last 5: ↑ Hot
vs Caicedo: €30M cheaper · 3y older
87% match
€80.0M
#2
R
Roméo Lavia
Chelsea · Premier League
Belgium22yContract 2030
KP/900.24
G/900.00
Box-to-BoxSmall Sample
Last 5: ↑ Hot
vs Caicedo: €80M cheaper · 2y younger
88% match
€30.0M
#3
E
Enzo Fernández
Chelsea · Premier League
Argentina25yContract 2032
KP/901.99
G/900.28
CreatorCreative
Last 5: ↑ Hot
vs Caicedo: €20M cheaper
86% match
€90.0M
#4
A
Alexis Mac Allister
Liverpool · Premier League
Argentina27yContract 2028
KP/901.12
G/900.07
Balanced Midfielder
Last 5: → Stable
86% match
€85.0M
#5
R
Ryan Gravenberch
Liverpool · Premier League
Netherlands23yContract 2028
KP/900.85
G/900.16
Metronome
Last 5: → Stable
85% match
€90.0M
#6
J
Jude Bellingham
Real Madrid · La Liga
England22yContract 2029
KP/901.67
G/900.20
CreatorCreative
Last 5: ↓ Dip
84% match
€140.0M
#7
N
Nicolás Domínguez
Nottingham Forest · Premier League
Argentina27yContract 2028
KP/900.91
G/900.08
Ball-WinnerDefensive
Last 5: → Stable
85% match
€15.0M
#8
J
Julio Enciso
Strasbourg · Ligue 1
Paraguay22yContract 2029
KP/901.65
G/900.45
CreatorSmall Sample
Last 5: → Stable
85% match
€20.0M
#9
M
Mats Wieffer
Brighton & Hove Albion · Premier League
Netherlands26yContract 2029
KP/900.99
G/900.10
Ball-WinnerDefensive
Last 5: ↓ Dip
84% match
€25.0M
#10
D
Dominik Szoboszlai
Liverpool · Premier League
Hungary25yContract 2028
KP/902.00
G/900.18
CreatorCreative
Last 5: → Stable
84% match
€100.0M
#11
W
Warren Zaïre-Emery
Paris Saint Germain · Ligue 1
France20yContract 2029
KP/901.50
G/900.00
MetronomeCreative
Last 5: → Stable
84% match
€50.0M
#12
C
Carlos Baleba
Brighton & Hove Albion · Premier League
Cameroon22yContract 2028
KP/900.35
G/900.00
Box-to-Box
Last 5: ↑ Hot
84% match
€60.0M

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 Moisés Caicedo.

Ask AI about Moisés Caicedo

Frequently Asked Questions

Who are the best alternatives to Moisés Caicedo?
The top alternatives to Moisés Caicedo based on AI DNA playing style analysis include: Martín Zubimendi, Roméo Lavia, Enzo Fernández, Alexis Mac Allister, Ryan Gravenberch. 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 Moisés Caicedo in 2026?
Players with a similar profile to Moisés Caicedo in 2026 include Martín Zubimendi (€80.0M), Roméo Lavia (€30.0M), Enzo Fernández (€90.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Moisés Caicedo play and who plays similarly?
Moisés Caicedo plays as a Midfielder. Players with a comparable positional profile include Martín Zubimendi (Spain, €80.0M); Roméo Lavia (Belgium, €30.0M); Enzo Fernández (Argentina, €90.0M); Alexis Mac Allister (Argentina, €85.0M).
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.