RisingTransfers
AI DNA Similarity

Best Alternatives to Armando Obispo

Players most similar to Armando Obispo (Defender, €3.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Armando Obispo

  1. 1.Anel Ahmedhodzic85% DNA match·Feyenoord€12.0M
  2. 2.Ryan Flamingo85% DNA match·PSV€17.0M
  3. 3.Mees de Wit85% DNA match·AZ€4.5M

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

RT

Intelligence Verdict

Aerials WonTop 0%
???Bottom 0%

A Ball-Playing CB....

See Full Verdict + Share Card →

Playing Style Analysis

Ball-Playing CBBall-PlayingAerialSmall Sample

A Ball-Playing CB. Statistically, he stands out as naturally left-footed, a regular goalscorer (0.22 goals/90), commanding in the air (6.2 clearances/90), meticulous in distribution (90% pass accuracy), wins the physical battle (57% duel success), heavily involved in possession (66 passes/90), penetrates with forward passing (9.2 final-third passes/90), central to possession (79 touches/90), strong in aerial duels (4.3 aerials won/90) and switches play with precision (5.4 long balls/90, 62% accuracy). Note: this profile is based on 806 minutes of playing time this season. The three most similar players to Armando Obispo by playing style are:

  • Anel Ahmedhodzic(85% match)A Ball-Playing CB. Statistically, he stands out as commanding in the air (5.0 clearances/90), reads the game exceptionally (1.6 interceptions/90), meticulous in distribution (91% pass accuracy), wins the physical battle (60% duel success), central to possession (72 touches/90) and active off the ball (2.3 press score/90), contributing to defensive transitions.
  • Ryan Flamingo(85% match)A Ball-Playing CB. Statistically, he stands out as commanding in the air (6.5 clearances/90), meticulous in distribution (89% pass accuracy), wins the physical battle (64% duel success), heavily involved in possession (71 passes/90), penetrates with forward passing (10.4 final-third passes/90), central to possession (88 touches/90), dominant in the air (3.8 aerials won/90, 69%) and switches play with precision (7.0 long balls/90, 63% accuracy).
  • Mees de Wit(85% match)A Active Full-Back. Statistically, he stands out as naturally left-footed, a capable chance creator (1.1 key passes/90), a reliable supplier (0.22 assists/90), active in the tackle (2.3 tackles/90), uses long balls frequently (5.5/90) and active off the ball (2.2 press score/90), contributing to defensive transitions.

Transfer Intelligence

Anel Ahmedhodzic delivers 85% of the same playing style, at a 300% premium over Armando Obispo, with 1.10 tackles won per 90 at age 27.

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

A
Comparison Base
Armando Obispo
DefenderNetherlands€3.0M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
A
Anel Ahmedhodzic
Feyenoord · Eredivisie
Bosnia and Herzegovina27yContract 2029
Tkl/901.10
KP/900.53
Ball-Playing CBBall-Playing
Last 5: → Stable
vs Obispo: €9M more expensive
85% match
€12.0M
#2
R
Ryan Flamingo
PSV · Eredivisie
Netherlands23yContract 2029
Tkl/901.66
KP/900.40
Ball-Playing CBBall-Playing
Last 5: → Stable
vs Obispo: €14M more expensive · 4y younger
85% match
€17.0M
#3
M
Mees de Wit
AZ · Eredivisie
Netherlands28yContract 2029
Tkl/902.28
KP/901.12
Active Full-Back
Last 5: → Stable
85% match
€4.5M
#4
Y
Yarek Gasiorowski
PSV · Eredivisie
Spain21yContract 2030
Tkl/901.18
KP/900.22
Ball-Playing CBBall-Playing
Last 5: → Stable
84% match
€16.0M
#5
B
Bram Nuytinck
NEC Nijmegen · Eredivisie
Netherlands36y
Tkl/901.08
KP/900.00
Ball-Playing CBBall-Playing
Last 5: → Stable
84% match
€3.0M
#6
D
Danilho Doekhi
FC Union Berlin · Bundesliga
Netherlands27yContract 2026
Tkl/901.00
KP/900.29
Physical StopperAerial
84% match
€13.0M
#7
J
Jordan Bos
Feyenoord · Eredivisie
Australia23yContract 2029
Tkl/903.11
KP/901.65
Active Full-Back
Last 5: ↓ Dip
84% match
€5.0M
#8
Y
Youri Baas
Ajax · Eredivisie
Netherlands23yContract 2028
Tkl/901.79
KP/900.30
Ball-Playing CBBall-Playing
Last 5: ↓ Dip
84% match
€16.0M
#9
T
Tsuyoshi Watanabe
Feyenoord · Eredivisie
Japan29yContract 2029
Tkl/901.16
KP/900.44
Ball-Playing CBBall-Playing
Last 5: → Stable
83% match
€10.0M
#10
L
Louis Oppie
St. Pauli · Bundesliga
Germany23y
Tkl/900.99
KP/900.17
Small Sample
84% match
€3.0M
#11
C
Calvin Verdonk
LOSC Lille · Ligue 1
Netherlands29yContract 2028
Tkl/903.05
KP/901.22
Active Full-BackBall-Playing
Last 5: ↓ Dip
84% match
€3.0M
#12
J
Jan Paul van Hecke
Brighton & Hove Albion · Premier League
Netherlands25yContract 2027
Tkl/901.54
KP/900.36
Ball-Playing CBBall-Playing
Last 5: → Stable
83% match
€35.0M

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 Armando Obispo.

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Frequently Asked Questions

Who are the best alternatives to Armando Obispo?
The top alternatives to Armando Obispo based on AI DNA playing style analysis include: Anel Ahmedhodzic, Ryan Flamingo, Mees de Wit, Yarek Gasiorowski, Bram Nuytinck. 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 Armando Obispo in 2026?
Players with a similar profile to Armando Obispo in 2026 include Anel Ahmedhodzic (€12.0M), Ryan Flamingo (€17.0M), Mees de Wit (€4.5M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Armando Obispo play and who plays similarly?
Armando Obispo plays as a Defender. Players with a comparable positional profile include Anel Ahmedhodzic (Bosnia and Herzegovina, €12.0M); Ryan Flamingo (Netherlands, €17.0M); Mees de Wit (Netherlands, €4.5M); Yarek Gasiorowski (Spain, €16.0M).
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.