AI DNA Similarity
Best Alternatives to Fatih Kamaci
Players most similar to Fatih Kamaci (Midfielder, N/A) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.
Playing Style Analysis
A Midfielder in KNVB Beker. Statistically, he stands out as a proven goalscorer (0.43 goals/90) and a reliable supplier (0.17 assists/90). The three most similar players to Fatih Kamaci by playing style are:
- Nick Runderkamp(97% match) — A Midfielder in KNVB Beker. Statistically, he stands out as a reliable supplier (0.22 assists/90).
- Mitchel Van Rosmalen(96% match) — A Midfielder in KNVB Beker. Statistically, he stands out as a reliable supplier (0.18 assists/90).
- Jamie Jacobs(95% match) — A Balanced Midfielder in KNVB Beker. Statistically, he stands out as a regular goalscorer (0.24 goals/90), a prolific assist provider (0.28 assists/90), active in the tackle (2.4 tackles/90) and creates high-quality scoring opportunities (0.66 big chances/90).
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
N
Nick Runderkamp
RKAV Volendam · Eredivisie
Netherlands29y
KP/900.00
G/900.15
97% match
N/A
#2
M
Mitchel Van Rosmalen
Blauw Geel '38 · Eredivisie
Netherlands24y
KP/900.72
G/900.00
Small Sample
96% match
N/A
#3
J
Jamie Jacobs
Almere City · Eredivisie
Netherlands28y
KP/901.06
G/900.24
Balanced Midfielder
95% match
N/A
#4
T
Tom van der Werff
ACV · Eredivisie
Netherlands23y
KP/900.59
G/900.00
Balanced MidfielderSmall Sample
94% match
N/A
#5
M
Max de Waal
Willem II · Eredivisie
Netherlands24y
KP/900.28
G/900.19
93% match
N/A
#6
C
Cas Dijkstra
Koninklijke HFC · Eredivisie
Netherlands24y
KP/900.71
G/900.19
93% match
N/A
#7
J
Jesse Schuurman
IJsselmeervogels · Eredivisie
Netherlands28y
KP/900.30
G/900.00
Balanced Midfielder
92% match
N/A
#8
G
Grad Damen
Kozakken Boys · Eredivisie
Netherlands28y
KP/901.36
G/900.15
Creator
91% match
N/A
#9
S
S. van Doorm
HHC · Eredivisie
Netherlands28y
KP/900.90
G/900.06
Box-to-Box
91% match
N/A
#10
N
Noah Naujoks
Excelsior · Eredivisie
Netherlands23yContract 2027
KP/901.08
G/900.39
Balanced Midfielder
Last 5: ↑ Hot91% match
N/A
#11
G
Gjivai Zechiël
FC Utrecht · Eredivisie
Netherlands21y
KP/901.14
G/900.24
Box-to-Box
Last 5: → Stable90% match
N/A
#12
M
Mart Remans
TOP Oss · Eredivisie
Netherlands27yContract 2026
KP/901.13
G/900.30
Creator
Last 5: ↓ Dip90% 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 Fatih Kamaci.
Ask AI about Fatih Kamaci →Frequently Asked Questions
Who are the best alternatives to Fatih Kamaci?▼
The top alternatives to Fatih Kamaci based on AI DNA playing style analysis include: Nick Runderkamp, Mitchel Van Rosmalen, Jamie Jacobs, Tom van der Werff, Max de Waal. 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 Fatih Kamaci in 2026?▼
Players with a similar profile to Fatih Kamaci in 2026 include Nick Runderkamp (N/A), Mitchel Van Rosmalen (N/A), Jamie Jacobs (N/A). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Fatih Kamaci play and who plays similarly?▼
Fatih Kamaci plays as a Midfielder. Players with a comparable positional profile include Nick Runderkamp (Netherlands, N/A); Mitchel Van Rosmalen (Netherlands, N/A); Jamie Jacobs (Netherlands, N/A); Tom van der Werff (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.