RisingTransfers
AI DNA Similarity

Best Alternatives to Jay Dasilva

Players most similar to Jay Dasilva (Defender, €2.4M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Jay Dasilva

  1. 1.Ian Maatsen85% DNA match·Aston Villa€25.0M
  2. 2.Michael Kayode84% DNA match·Brentford€35.0M
  3. 3.Malick Thiaw83% DNA match·Newcastle United€45.0M

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

RT

Intelligence Verdict

Key PassesTop 9%
???Bottom 0%

A Active Full-Back....

See Full Verdict + Share Card →

Playing Style Analysis

Active Full-Back

A Active Full-Back. Statistically, he stands out as naturally left-footed, a capable chance creator (1.2 key passes/90), active in the tackle (1.8 tackles/90), meticulous in distribution (87% pass accuracy), central to possession (72 touches/90) and active off the ball (2.4 press score/90), contributing to defensive transitions. The three most similar players to Jay Dasilva by playing style are:

  • Ian Maatsen(85% match)A Active Full-Back. Statistically, he stands out as naturally left-footed, a capable chance creator (1.4 key passes/90), active in the tackle (2.3 tackles/90), meticulous in distribution (86% pass accuracy), central to possession (72 touches/90) and active off the ball (2.6 press score/90), contributing to defensive transitions.
  • Michael Kayode(84% match)A Active Full-Back. Statistically, he stands out as active in the tackle (1.8 tackles/90), meticulous in distribution (85% pass accuracy), wins the physical battle (58% duel success) and active off the ball (2.5 press score/90), contributing to defensive transitions.
  • Malick Thiaw(83% match)Thiaw has quietly become one of the Premier League's most complete defensive profiles — a towering centre-back who doesn't just win his battles, he wins them cleanly. His aerial win rate of 65.1% and duel success of 64.2% both sit in the league's top 20%, but the counterintuitive story is his attacking output: 0.16 goals per 90 and 0.98 shots per 90 place him in the top 10% among defenders, suggesting a genuine threat from set-pieces that opponents routinely underestimate. His pass accuracy of 90.6% reflects a ball-player comfortable in possession-heavy systems, and his above-average delivery into the final third adds genuine build-up value.

Transfer Intelligence

Ian Maatsen delivers 85% of the same playing style, at a 942% premium over Jay Dasilva, with 2.33 tackles won per 90 at age 24.

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

J
Comparison Base
Jay Dasilva
DefenderEngland€2.4M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
I
Ian Maatsen
Aston Villa · Premier League
Netherlands24yContract 2030
Tkl/902.33
KP/901.44
Active Full-Back
Last 5: ↓ Dip
vs Dasilva: €23M more expensive · 4y younger
85% match
€25.0M
#2
M
Michael Kayode
Brentford · Premier League
Italy21yContract 2030
Tkl/901.87
KP/900.99
Active Full-Back
Last 5: → Stable
vs Dasilva: €33M more expensive · 7y younger
84% match
€35.0M
#3
M
Malick Thiaw
Newcastle United · Premier League
Germany24yContract 2029
Tkl/901.29
KP/900.19
Ball-Playing CBAerial
Last 5: ↑ Hot
vs Dasilva: €43M more expensive · 4y younger
83% match
€45.0M
#4
R
Riccardo Calafiori
Arsenal · Premier League
Italy23yContract 2029
Tkl/901.81
KP/900.34
Active Full-Back
Last 5: → Stable
83% match
€50.0M
#5
M
Mathías Olivera
Napoli · Serie A
Uruguay28yContract 2030
Tkl/902.59
KP/900.94
Active Full-BackBall-Playing
Last 5: ↓ Dip
84% match
€15.0M
#6
A
Antonee Robinson
Fulham · Premier League
United States28yContract 2028
Tkl/903.02
KP/901.37
Active Full-Back
Last 5: → Stable
83% match
€25.0M
#7
L
Levi Colwill
Chelsea · Premier League
England23yContract 2029
Tkl/901.41
KP/900.41
Ball-Playing CBBall-Playing
82% match
€50.0M
#8
K
Kevin Danso
Tottenham Hotspur · Premier League
Austria27yContract 2030
Tkl/901.84
KP/900.20
Ball-Playing CBBall-Playing
Last 5: → Stable
83% match
€22.0M
#9
C
Chadi Riad
Crystal Palace · Premier League
Morocco22yContract 2029
Tkl/901.62
KP/900.23
Ball-Playing CBAerial
Last 5: → Stable
82% match
€12.0M
#10
K
Kenny Tete
Fulham · Premier League
Netherlands30yContract 2028
Tkl/903.26
KP/900.55
Physical Stopper
Last 5: → Stable
82% match
€11.0M
#11
N
Neco Williams
Nottingham Forest · Premier League
Wales25yContract 2029
Tkl/902.71
KP/901.07
Active Full-Back
Last 5: → Stable
82% match
€25.0M
#12
J
James Hill
AFC Bournemouth · Premier League
England24yContract 2026
Tkl/901.77
KP/900.61
Physical StopperAerial
Last 5: → Stable
82% 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 Jay Dasilva.

Ask AI about Jay Dasilva

Frequently Asked Questions

Who are the best alternatives to Jay Dasilva?
The top alternatives to Jay Dasilva based on AI DNA playing style analysis include: Ian Maatsen, Michael Kayode, Malick Thiaw, Riccardo Calafiori, Mathías Olivera. 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 Jay Dasilva in 2026?
Players with a similar profile to Jay Dasilva in 2026 include Ian Maatsen (€25.0M), Michael Kayode (€35.0M), Malick Thiaw (€45.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Jay Dasilva play and who plays similarly?
Jay Dasilva plays as a Defender. Players with a comparable positional profile include Ian Maatsen (Netherlands, €25.0M); Michael Kayode (Italy, €35.0M); Malick Thiaw (Germany, €45.0M); Riccardo Calafiori (Italy, €50.0M).
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.