RisingTransfers
AI DNA Similarity

Best Alternatives to Simon Graves

Players most similar to Simon Graves (Defender, €1.4M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Simon Graves

  1. 1.Wouter Goes85% DNA match·AZ€12.0M
  2. 2.Tsuyoshi Watanabe85% DNA match·Feyenoord€10.0M
  3. 3.Bram Nuytinck85% DNA match·NEC Nijmegen€3.0M

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

RT

Intelligence Verdict

Aerials WonTop 13%
???Bottom 19%

A Ball-Playing CB....

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Playing Style Analysis

Ball-Playing CBBall-PlayingAerial

A Ball-Playing CB. Statistically, he stands out as commanding in the air (8.1 clearances/90), central to possession (72 touches/90), uses long balls frequently (7.8/90) and active off the ball (2.1 press score/90), contributing to defensive transitions. The three most similar players to Simon Graves by playing style are:

  • Wouter Goes(85% match)A Ball-Playing CB. Statistically, he stands out as commanding in the air (4.2 clearances/90), meticulous in distribution (89% pass accuracy), wins the physical battle (64% duel success), heavily involved in possession (63 passes/90), penetrates with forward passing (8.7 final-third passes/90), central to possession (76 touches/90), uses long balls frequently (7.2/90) and active off the ball (2.4 press score/90), contributing to defensive transitions.
  • Tsuyoshi Watanabe(85% match)A Ball-Playing CB. Statistically, he stands out as commanding in the air (5.0 clearances/90), meticulous in distribution (89% pass accuracy), wins the physical battle (61% duel success), heavily involved in possession (62 passes/90), central to possession (75 touches/90), strong in aerial duels (3.2 aerials won/90), uses long balls frequently (5.2/90) and active off the ball (2.1 press score/90), contributing to defensive transitions.
  • Bram Nuytinck(85% match)Nuytinck is the quintessential Eredivisie "old head" whose value lies in the safety of his distribution rather than the dynamism of his defending. While he lacks the mobility of modern elite center-backs, his 89.7% pass accuracy puts him in the top 30% of the league, marking him as a reliable metronome for a Tier C side looking to build from the back without risk. Counterintuitively, despite his reputation as a physical presence, his 52.6% duel win rate is merely average, suggesting he relies more on positioning than raw power to survive.

Transfer Intelligence

Wouter Goes delivers 85% of the same playing style, at a 757% premium over Simon Graves, with 1.25 tackles won per 90 at age 21.

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

S
Comparison Base
Simon Graves
DefenderDenmark€1.4M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
W
Wouter Goes
AZ · Eredivisie
Netherlands21yContract 2028
Tkl/901.25
KP/900.34
Ball-Playing CBBall-Playing
Last 5: ↑ Hot
vs Graves: €11M more expensive · 5y younger
85% match
€12.0M
#2
T
Tsuyoshi Watanabe
Feyenoord · Eredivisie
Japan29yContract 2029
Tkl/901.16
KP/900.44
Ball-Playing CBBall-Playing
Last 5: → Stable
vs Graves: €9M more expensive · 3y older
85% match
€10.0M
#3
B
Bram Nuytinck
NEC Nijmegen · Eredivisie
Netherlands36y
Tkl/901.08
KP/900.00
Ball-Playing CBBall-Playing
Last 5: → Stable
vs Graves: 10y older
85% match
€3.0M
#4
A
Armando Obispo
PSV · Eredivisie
Netherlands27yContract 2027
Tkl/900.67
KP/900.00
Ball-Playing CBBall-Playing
Last 5: ↓ Dip
85% match
€3.0M
#5
Y
Youri Baas
Ajax · Eredivisie
Netherlands23yContract 2028
Tkl/901.79
KP/900.30
Ball-Playing CBBall-Playing
Last 5: ↓ Dip
85% match
€16.0M
#6
Y
Yarek Gasiorowski
PSV · Eredivisie
Spain21yContract 2030
Tkl/901.18
KP/900.22
Ball-Playing CBBall-Playing
Last 5: → Stable
84% match
€16.0M
#7
S
Sepp van den Berg
Brentford · Premier League
Netherlands24yContract 2029
Tkl/900.64
KP/900.20
Ball-Playing CBAerial
Last 5: → Stable
84% match
€28.0M
#8
A
Anel Ahmedhodzic
Feyenoord · Eredivisie
Bosnia and Herzegovina27yContract 2029
Tkl/901.10
KP/900.53
Ball-Playing CBBall-Playing
Last 5: → Stable
84% match
€12.0M
#9
K
Kristoffer Ajer
Brentford · Premier League
Norway28yContract 2028
Tkl/901.87
KP/900.26
Physical StopperAerial
Last 5: ↓ Dip
84% match
€18.0M
#10
C
Calvin Bassey
Fulham · Premier League
Nigeria26yContract 2027
Tkl/902.22
KP/900.34
Ball-Playing CBBall-Playing
Last 5: → Stable
84% match
€28.0M
#11
M
Mees de Wit
AZ · Eredivisie
Netherlands28yContract 2029
Tkl/902.28
KP/901.12
Active Full-Back
Last 5: → Stable
84% match
€4.5M
#12
A
Ahmetcan Kaplan
NEC Nijmegen · Eredivisie
Turkey23y
Tkl/902.15
KP/900.44
Ball-Playing CBAerial
Last 5: → Stable
84% match
€9.5M

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 Simon Graves.

Ask AI about Simon Graves

Frequently Asked Questions

Who are the best alternatives to Simon Graves?
The top alternatives to Simon Graves based on AI DNA playing style analysis include: Wouter Goes, Tsuyoshi Watanabe, Bram Nuytinck, Armando Obispo, Youri Baas. 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 Simon Graves in 2026?
Players with a similar profile to Simon Graves in 2026 include Wouter Goes (€12.0M), Tsuyoshi Watanabe (€10.0M), Bram Nuytinck (€3.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Simon Graves play and who plays similarly?
Simon Graves plays as a Defender. Players with a comparable positional profile include Wouter Goes (Netherlands, €12.0M); Tsuyoshi Watanabe (Japan, €10.0M); Bram Nuytinck (Netherlands, €3.0M); Armando Obispo (Netherlands, €3.0M).
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.