AI DNA Similarity
Best Alternatives to Danilho Doekhi
Players most similar to Danilho Doekhi (Defender, €13.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.
Top 3 Alternatives to Danilho Doekhi
- 1.Anel Ahmedhodzic88% DNA match·Feyenoord€12.0M
- 2.Nico Schlotterbeck88% DNA match·Borussia Dortmund€55.0M
- 3.Kevin Diks88% DNA match·Borussia Mönchengladbach€5.0M
Ranked by AI DNA similarity — 768 dimensions across playing style, pressing intensity, and tactical fit.
RT
Intelligence Verdict
Aerials WonTop 1%
???Bottom 13%
“A Physical Stopper....”
See Full Verdict + Share Card →Playing Style Analysis
Physical StopperAerialSmall Sample
A Physical Stopper. Statistically, he stands out as a regular goalscorer (0.33 goals/90), commanding in the air (5.3 clearances/90), wins the physical battle (62% duel success), dominant in the air (4.8 aerials won/90, 63%) and uses long balls frequently (7.5/90). Note: this profile is based on 540 minutes of playing time this season. The three most similar players to Danilho Doekhi by playing style are:
- Anel Ahmedhodzic(88% 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.
- Nico Schlotterbeck(88% match) — A Ball-Playing CB. Statistically, he stands out as naturally left-footed, active in the tackle (2.0 tackles/90), commanding in the air (4.2 clearances/90), meticulous in distribution (86% pass accuracy), wins the physical battle (66% duel success), heavily involved in possession (75 passes/90), penetrates with forward passing (13.6 final-third passes/90), central to possession (97 touches/90), uses long balls frequently (12.2/90) and active off the ball (2.7 press score/90), contributing to defensive transitions. Note: this profile is based on 720 minutes of playing time this season.
- Kevin Diks(88% match) — A Ball-Playing CB. Statistically, he stands out as active in the tackle (2.0 tackles/90), commanding in the air (4.9 clearances/90), meticulous in distribution (89% pass accuracy), wins the physical battle (66% duel success), heavily involved in possession (62 passes/90), central to possession (75 touches/90), uses long balls frequently (6.5/90) and active off the ball (3.0 press score/90), contributing to defensive transitions. Note: this profile is based on 778 minutes of playing time this season.
Transfer Intelligence
Anel Ahmedhodzic delivers 88% of the same playing style, 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 →
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: → Stable88% match
€12.0M
#2
N
Nico Schlotterbeck
Borussia Dortmund · Bundesliga
Germany26yContract 2027
Tkl/902.00
KP/900.89
Ball-Playing CBBall-Playing
Last 5: → Stablevs Doekhi: €42M more expensive
88% match
€55.0M
#3
K
Kevin Diks
Borussia Mönchengladbach · Bundesliga
Netherlands29yContract 2030
Tkl/901.87
KP/900.21
Ball-Playing CBBall-Playing
Last 5: ↓ Dipvs Doekhi: €8M cheaper · 2y older
88% match
€5.0M
#4
M
Malick Thiaw
Newcastle United · Premier League
Germany24yContract 2029
Tkl/901.29
KP/900.19
Ball-Playing CBAerial
Last 5: ↑ Hot87% match
€45.0M
#5
L
Luka Vuskovic
Hamburger SV · Bundesliga
Croatia19yContract 2026
Tkl/900.86
KP/900.74
Ball-Playing CBBall-Playing
Last 5: ↑ Hot87% match
€40.0M
#6
A
Arthur Theate
Eintracht Frankfurt · Bundesliga
Belgium25yContract 2029
Tkl/902.42
KP/900.70
Ball-Playing CBBall-Playing
86% match
€20.0M
#7
L
Leopold Querfeld
FC Union Berlin · Bundesliga
Austria22y
Tkl/901.00
KP/900.20
Physical StopperAerial
86% match
€18.0M
#8
L
Lukas Ullrich
Borussia Mönchengladbach · Bundesliga
Germany22yContract 2027
Tkl/901.33
KP/900.53
Active Full-Back
86% match
€7.0M
#9
J
Jaka Bijol
Leeds United · Premier League
Slovenia27yContract 2030
Tkl/901.30
KP/900.36
Ball-Playing CBAerial
Last 5: ↓ Dip86% match
€18.0M
#10
J
Jordy Makengo
SC Freiburg · Bundesliga
France24y
Tkl/901.50
KP/900.30
Aerial
Last 5: → Stable87% match
€6.0M
#11
M
Moritz Jenz
VfL Wolfsburg · Bundesliga
Germany27yContract 2027
Tkl/902.37
KP/900.00
Ball-Playing CBAerial
86% match
€5.0M
#12
M
Moussa Niakhaté
Olympique Lyonnais · Ligue 1
Senegal30yContract 2028
Tkl/900.85
KP/900.36
Ball-Playing CBBall-Playing
Last 5: ↑ Hot86% match
€15.0M
⬡
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 Danilho Doekhi.
Ask AI about Danilho Doekhi →Frequently Asked Questions
Who are the best alternatives to Danilho Doekhi?▼
The top alternatives to Danilho Doekhi based on AI DNA playing style analysis include: Anel Ahmedhodzic, Nico Schlotterbeck, Kevin Diks, Malick Thiaw, Luka Vuskovic. 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 Danilho Doekhi in 2026?▼
Players with a similar profile to Danilho Doekhi in 2026 include Anel Ahmedhodzic (€12.0M), Nico Schlotterbeck (€55.0M), Kevin Diks (€5.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Danilho Doekhi play and who plays similarly?▼
Danilho Doekhi plays as a Defender. Players with a comparable positional profile include Anel Ahmedhodzic (Bosnia and Herzegovina, €12.0M); Nico Schlotterbeck (Germany, €55.0M); Kevin Diks (Netherlands, €5.0M); Malick Thiaw (Germany, €45.0M).
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.