AI DNA Similarity
Best Alternatives to Romano Postema
Players most similar to Romano Postema (Attacker, N/A) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.
Top 3 Alternatives to Romano Postema
- 1.Michael Breij83% DNA match·Roda JC Kerkrade
- 2.Dani van der Moot83% DNA match·Katwijk
- 3.Enzo Stroo83% DNA match·Lisse
Ranked by AI DNA similarity — 768 dimensions across playing style, pressing intensity, and tactical fit.
RT
Intelligence Verdict
GoalsTop 7%
???Bottom 17%
“A Forward....”
See Full Verdict + Share Card →Playing Style Analysis
A Forward. The three most similar players to Romano Postema by playing style are:
- Michael Breij(83% match) — Michael Breij is a Forward. Versatile attacking option. Statistically, he stands out as a capable chance creator (1.2 key passes/90).
- Dani van der Moot(83% match) — Dani van der Moot is a Forward. Versatile attacking option. Statistically, he stands out as a regular goalscorer (0.22 goals/90) and a reliable supplier (0.22 assists/90). (Limited sample: 414 mins)
- Enzo Stroo(83% match) — Enzo Stroo is a Forward. Versatile attacking option. Statistically, he stands out as a reliable supplier (0.22 assists/90). (Limited sample: 408 mins)
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
M
Michael Breij
Roda JC Kerkrade · Eredivisie
Netherlands29y
G/900.58
A/900.17
vs Postema: 5y older · -0.11 G/90
83% match
N/A
#2
D
Dani van der Moot
Katwijk · Eredivisie
Netherlands29y
G/900.22
A/900.22
Small Sample
vs Postema: 5y older · -0.47 G/90
83% match
N/A
#3
E
Enzo Stroo
Lisse · Eredivisie
Netherlands31y
G/900.00
A/900.22
Small Sample
vs Postema: 7y older
83% match
N/A
#4
M
Martijn Berden
GVVV · Eredivisie
Netherlands28y
G/900.00
A/900.34
Small Sample
82% match
N/A
#5
Á
Álex Sola
Granada · La Liga
Spain26yContract 2026
G/900.10
A/900.10
82% match
N/A
#6
D
Dennis Johnsen
Cremonese · Serie A
Norway28yContract 2029
G/900.28
A/900.00
81% match
€3.0M
#7
A
André Bukia
Al Adalah · Liga Portugal
DR Congo31y
G/900.17
A/900.00
81% match
N/A
#8
V
Vaclav Jurecka
Baník Ostrava · Super Lig
Czech Republic31y
G/900.19
A/900.00
Small Sample
Last 5: ↓ Dip81% match
N/A
#9
N
Nikola Gjorgjev
Farense · Liga Portugal
Switzerland28y
G/900.00
A/900.00
Small Sample
81% match
N/A
#10
M
Michiel Kramer
RKC Waalwijk · Eredivisie
Netherlands37y
G/900.39
A/900.00
Small Sample
81% match
N/A
#11
Z
Zach Booth
Real Salt Lake · Eredivisie
United States22y
G/900.00
A/900.00
80% match
N/A
#12
A
Amath Ndiaye
Real Valladolid · La Liga
Senegal29yContract 2027
G/900.76
A/900.00
80% match
€6.5M
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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 Romano Postema.
Ask AI about Romano Postema →Frequently Asked Questions
Who are the best alternatives to Romano Postema?▼
The top alternatives to Romano Postema based on AI DNA playing style analysis include: Michael Breij, Dani van der Moot, Enzo Stroo, Martijn Berden, Álex Sola. 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 Romano Postema in 2026?▼
Players with a similar profile to Romano Postema in 2026 include Michael Breij (N/A), Dani van der Moot (N/A), Enzo Stroo (N/A). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Romano Postema play and who plays similarly?▼
Romano Postema plays as a Attacker. Players with a comparable positional profile include Michael Breij (Netherlands, N/A); Dani van der Moot (Netherlands, N/A); Enzo Stroo (Netherlands, N/A); Martijn Berden (Netherlands, 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.