RisingTransfers
AI DNA Similarity

Best Alternatives to Kenneth Taylor

Players most similar to Kenneth Taylor (Midfielder, €23.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Kenneth Taylor

  1. 1.Weston McKennie83% DNA match·Juventus€22.0M
  2. 2.Amir Richardson83% DNA match·FC København€9.0M
  3. 3.Peer Koopmeiners84% DNA match·AZ€10.0M

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

RT

Intelligence Verdict

AssistsTop 8%
???Bottom 1%

A Creator....

See Full Verdict + Share Card →

Playing Style Analysis

CreatorCreative

A Creator. Statistically, he stands out as naturally left-footed, an elite creator (1.7 key passes/90), a prolific assist provider (0.28 assists/90), meticulous in distribution (86% pass accuracy), heavily involved in play (56 touches/90) and active off the ball (2.1 press score/90), contributing to defensive transitions. The three most similar players to Kenneth Taylor by playing style are:

  • Weston McKennie(83% match)McKennie is the American who made Serie A believers out of skeptics—a box-to-box engine who wins aerial duels at a rate that puts him in the top 10% of Italian midfielders, a remarkable feat for someone operating in one of Europe's most physically demanding leagues. His 1.44 key passes per 90 and consistent presence in the final third suggest a midfielder who genuinely influences the game's decisive moments, not just its connective tissue. The counterintuitive truth, though, is that his passing accuracy sits at dead average—which for a player asked to carry and progress the ball in tight spaces, is a quiet limitation that compounds under pressure.
  • Amir Richardson(83% match)A Box-to-Box. Statistically, he stands out as an aggressive ball-winner (2.5 tackles/90), meticulous in distribution (88% pass accuracy), heavily involved in play (69 touches/90), active off the ball (2.1 press score/90), contributing to defensive transitions and top 10% tackler in the league. However, he prone to committing fouls (2.7/90).
  • Peer Koopmeiners(84% match)A Ball-Winner. Statistically, he stands out as a capable chance creator (1.0 key passes/90), an aggressive ball-winner (3.3 tackles/90), wins the ball cleanly (2.0 successful tackles/90), heavily involved in play (61 touches/90), active off the ball (2.6 press score/90), contributing to defensive transitions and top 10% tackler in the league.

Transfer Intelligence

Weston McKennie delivers 83% of the same playing style, with 1.59 key passes per 90 at age 27.

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

K
Comparison Base
Kenneth Taylor
MidfielderNetherlands€23.0M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
W
Weston McKennie
Juventus · Serie A
United States27yContract 2026
KP/901.59
G/900.28
Creator
Last 5: → Stable
vs Taylor: 4y older
83% match
€22.0M
#2
A
Amir Richardson
FC København · Serie A
France24yContract 2026
KP/900.65
G/900.09
Box-to-BoxDefensive
Last 5: ↓ Dip
vs Taylor: €14M cheaper
83% match
€9.0M
#3
P
Peer Koopmeiners
AZ · Eredivisie
Netherlands26yContract 2028
KP/901.10
G/900.09
Ball-WinnerDefensive
Last 5: → Stable
vs Taylor: €13M cheaper · 3y older
84% match
€10.0M
#4
R
Ramiz Zerrouki
FC Twente · Eredivisie
Algeria27y
KP/901.56
G/900.11
MetronomeCreative
Last 5: ↑ Hot
82% match
€7.2M
#5
M
Manuel Locatelli
Juventus · Serie A
Italy28yContract 2028
KP/901.88
G/900.00
MetronomeDefensive
Last 5: ↓ Dip
82% match
€25.0M
#6
T
Teun Koopmeiners
Juventus · Serie A
Netherlands28yContract 2029
KP/900.72
G/900.24
Chance Creator
Last 5: → Stable
83% match
€28.0M
#7
T
Tijjani Reijnders
Manchester City · Premier League
Netherlands27yContract 2030
KP/901.04
G/900.29
Last 5: → Stable
82% match
€60.0M
#8
L
Lennon Miller
Udinese · Serie A
Scotland19yContract 2030
KP/901.22
G/900.00
Box-to-BoxDefensive
Last 5: ↑ Hot
83% match
€8.0M
#9
J
Jurgen Ekkelenkamp
Udinese · Serie A
Netherlands26yContract 2029
KP/901.41
G/900.19
Creator
Last 5: → Stable
83% match
€7.0M
#10
M
Mario Pašalić
Atalanta · Serie A
Croatia31yContract 2028
KP/901.75
G/900.10
Creative Playmaker
Last 5: ↓ Dip
82% match
€7.0M
#11
M
Morten Frendrup
Genoa · Serie A
Denmark25yContract 2028
KP/900.23
G/900.06
Ball-WinnerDefensive
Last 5: ↓ Dip
81% match
€18.0M
#12
K
Kees Smit
AZ · Eredivisie
Netherlands20yContract 2028
KP/901.56
G/900.13
Box-to-BoxCreative
Last 5: → Stable
81% match
€22.0M

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 Kenneth Taylor.

Ask AI about Kenneth Taylor

Frequently Asked Questions

Who are the best alternatives to Kenneth Taylor?
The top alternatives to Kenneth Taylor based on AI DNA playing style analysis include: Weston McKennie, Amir Richardson, Peer Koopmeiners, Ramiz Zerrouki, Manuel Locatelli. 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 Kenneth Taylor in 2026?
Players with a similar profile to Kenneth Taylor in 2026 include Weston McKennie (€22.0M), Amir Richardson (€9.0M), Peer Koopmeiners (€10.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Kenneth Taylor play and who plays similarly?
Kenneth Taylor plays as a Midfielder. Players with a comparable positional profile include Weston McKennie (United States, €22.0M); Amir Richardson (France, €9.0M); Peer Koopmeiners (Netherlands, €10.0M); Ramiz Zerrouki (Algeria, €7.2M).
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.