AI DNA Similarity
Best Alternatives to Steve Kapuadi
Players most similar to Steve Kapuadi (Defender, €2.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.
Top 3 Alternatives to Steve Kapuadi
- 1.Dean van der Sluys79% DNA match·Kozakken Boys
- 2.Damian van der Haar79% DNA match·PEC Zwolle
- 3.Rasmus Brodersen79% DNA match·HB Køge
Ranked by AI DNA similarity — 768 dimensions across playing style, pressing intensity, and tactical fit.
RT
Intelligence Verdict
Chances MissedTop 0%
???Bottom 0%
“A Defender....”
See Full Verdict + Share Card →Playing Style Analysis
Small Sample
A Defender. Statistically, he stands out as top 10% tackler in the league. Note: this profile is based on 540 minutes of playing time this season. The three most similar players to Steve Kapuadi by playing style are:
- Dean van der Sluys(79% match) — A Solid Defender.
- Damian van der Haar(79% match) — A Solid Defender.
- Rasmus Brodersen(79% match) — A Solid Defender.
Similarity is calculated using per-90 performance data across multiple playing style dimensions. How Player DNA matching works →
Similar Players — Ranked by DNA Similarity
#1
D
Dean van der Sluys
Kozakken Boys · Eredivisie
Netherlands30y
Tkl/901.49
KP/900.87
Solid Defender
vs Kapuadi: 2y older
79% match
N/A
#2
D
Damian van der Haar
PEC Zwolle · Eredivisie
Netherlands22yContract 2028
Tkl/901.75
KP/900.72
Solid Defender
vs Kapuadi: 6y younger
79% match
N/A
#3
R
Rasmus Brodersen
HB Køge · Superliga
Denmark24y
Tkl/900.63
KP/900.63
Solid Defender
Last 5: ↑ Hotvs Kapuadi: 4y younger
79% match
N/A
#4
N
Noah Barholt Rasmussen
Middelfart · Superliga
Denmark20y
Tkl/901.47
KP/900.42
Solid Defender
Last 5: ↑ Hot79% match
N/A
#5
B
Burhan Ersoy
Fatih Karagümrük · Super Lig
Turkey22y
Tkl/901.61
KP/900.00
Solid Defender
79% match
N/A
#6
E
E. Bayrak
HB Køge · Superliga
Denmark19y
Tkl/900.28
KP/900.07
77% match
N/A
#7
D
Darryl Baly
Lisse · Eredivisie
Aruba28y
Tkl/900.00
KP/900.00
77% match
N/A
#8
L
Luis Pedro
ASWH · Eredivisie
Netherlands34y
Tkl/900.00
KP/900.00
77% match
N/A
#9
M
Magnus Lysholm
Hvidovre · Superliga
Denmark24y
Tkl/900.00
KP/900.00
77% match
N/A
#10
D
Doriano Marvin Kortstam
Halsteren · Eredivisie
Curaçao31y
Tkl/900.00
KP/900.00
77% match
N/A
#11
E
Emil Møller
B 93 · Superliga
Denmark21y
Tkl/900.07
KP/900.13
77% match
N/A
#12
D
Daniel Lønborg Thøgersen
Fredericia · Superliga
Denmark26y
Tkl/900.27
KP/900.11
77% match
N/A
⬡
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 Steve Kapuadi.
Ask AI about Steve Kapuadi →Frequently Asked Questions
Who are the best alternatives to Steve Kapuadi?▼
The top alternatives to Steve Kapuadi based on AI DNA playing style analysis include: Dean van der Sluys, Damian van der Haar, Rasmus Brodersen, Noah Barholt Rasmussen, Burhan Ersoy. 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 Steve Kapuadi in 2026?▼
Players with a similar profile to Steve Kapuadi in 2026 include Dean van der Sluys (N/A), Damian van der Haar (N/A), Rasmus Brodersen (N/A). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Steve Kapuadi play and who plays similarly?▼
Steve Kapuadi plays as a Defender. Players with a comparable positional profile include Dean van der Sluys (Netherlands, N/A); Damian van der Haar (Netherlands, N/A); Rasmus Brodersen (Denmark, N/A); Noah Barholt Rasmussen (Denmark, N/A).
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.