RisingTransfers
AI DNA Similarity

Best Alternatives to David Ayala

Players most similar to David Ayala (Midfielder, €4.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to David Ayala

  1. 1.Kevin Paredes84% DNA match·VfL Wolfsburg€3.0M
  2. 2.Johnny Cardoso84% DNA match·Atlético Madrid€22.0M
  3. 3.Malik Tillman84% DNA match·Bayer 04 Leverkusen€35.0M

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

RT

Intelligence Verdict

Press IntensityTop 4%
???Bottom 0%

A Ball-Winner....

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Playing Style Analysis

Ball-WinnerDefensive

A Ball-Winner. Statistically, he stands out as naturally left-footed, an aggressive ball-winner (3.0 tackles/90), reads the game exceptionally (1.6 interceptions/90), meticulous in distribution (88% pass accuracy), wins the physical battle (63% duel success), heavily involved in possession (61 passes/90), penetrates with forward passing (8.8 final-third passes/90), wins the ball cleanly (1.9 successful tackles/90), central to possession (76 touches/90), switches play with precision (7.8 long balls/90, 70% accuracy), a high-intensity presser (press score 3.5/90), constantly disrupting opposition build-up and top 10% tackler in the league. The three most similar players to David Ayala by playing style are:

  • Kevin Paredes(84% match)A Ball-Winner. Statistically, he stands out as naturally left-footed, a capable chance creator (1.1 key passes/90), an aggressive ball-winner (2.6 tackles/90), reads the game exceptionally (1.5 interceptions/90), wins the physical battle (63% duel success) and top 10% tackler in the league.
  • Johnny Cardoso(84% match)A Ball-Winner. Statistically, he stands out as an aggressive ball-winner (4.0 tackles/90), reads the game exceptionally (1.5 interceptions/90), meticulous in distribution (88% pass accuracy), wins the ball cleanly (1.9 successful tackles/90), heavily involved in play (69 touches/90), active off the ball (2.7 press score/90), contributing to defensive transitions and top 10% tackler in the league. However, he loses possession under pressure (1.6 dispossessed/90).
  • Malik Tillman(84% match)A Creator. Statistically, he stands out as a capable chance creator (1.4 key passes/90), a regular goalscorer (0.20 goals/90), an aggressive ball-winner (2.7 tackles/90), wins the ball cleanly (2.0 successful tackles/90), heavily involved in play (55 touches/90) and active off the ball (2.2 press score/90), contributing to defensive transitions. However, he loses possession under pressure (1.8 dispossessed/90).

Transfer Intelligence

Kevin Paredes delivers 84% of the same playing style, at 25% lower cost (€3.0M vs €4.0M), with 1.02 key passes per 90 at age 23.

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

D
Comparison Base
David Ayala
MidfielderArgentina€4.0M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
K
Kevin Paredes
VfL Wolfsburg · Bundesliga
United States23yContract 2026
KP/901.02
G/900.19
Ball-WinnerDefensive
84% match
€3.0M
#2
J
Johnny Cardoso
Atlético Madrid · La Liga
Brazil24yContract 2030
KP/900.28
G/900.00
Ball-WinnerDefensive
Last 5: ↓ Dip
vs Ayala: €18M more expensive
84% match
€22.0M
#3
M
Malik Tillman
Bayer 04 Leverkusen · Bundesliga
United States23yContract 2030
KP/900.84
G/900.34
CreatorDefensive
Last 5: ↑ Hot
vs Ayala: €31M more expensive
84% match
€35.0M
#4
A
Aleix García
Bayer 04 Leverkusen · Bundesliga
Spain28yContract 2026
KP/900.72
G/900.18
MetronomeSmall Sample
Last 5: ↑ Hot
82% match
€20.0M
#5
E
Ezequiel Fernández
Bayer 04 Leverkusen · Bundesliga
Argentina23yContract 2030
KP/901.03
G/900.00
Ball-WinnerDefensive
Last 5: ↓ Dip
83% match
€25.0M
#6
F
Federico Redondo
Elche · La Liga
Argentina23yContract 2030
KP/901.09
G/900.27
Chance CreatorDeep Distributor
83% match
€4.0M
#7
K
Kenneth Taylor
Lazio · Serie A
Netherlands23yContract 2030
KP/901.66
G/900.14
CreatorCreative
Last 5: ↓ Dip
82% match
€23.0M
#8
S
Santi Comesaña
Villarreal · La Liga
Spain29yContract 2028
KP/900.73
G/900.10
Box-to-Box
Last 5: → Stable
82% match
€8.0M
#9
M
Marc Roca
Real Betis · La Liga
Spain29yContract 2029
KP/900.95
G/900.00
Balanced Midfielder
Last 5: ↑ Hot
82% match
€4.0M
#10
J
Jon Moncayola
Osasuna · La Liga
Spain27yContract 2031
KP/900.98
G/900.00
Last 5: ↓ Dip
81% match
€7.0M
#11
B
Brais Méndez
Real Sociedad · La Liga
Spain29yContract 2028
KP/901.17
G/900.31
Creator
81% match
€12.0M
#12
M
Morten Hjulmand
Sporting CP · Liga Portugal
Denmark26yContract 2028
KP/901.13
G/900.08
Metronome
Last 5: → Stable
81% match
€45.0M

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 David Ayala.

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Frequently Asked Questions

Who are the best alternatives to David Ayala?
The top alternatives to David Ayala based on AI DNA playing style analysis include: Kevin Paredes, Johnny Cardoso, Malik Tillman, Aleix García, Ezequiel Fernández. 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 David Ayala in 2026?
Players with a similar profile to David Ayala in 2026 include Kevin Paredes (€3.0M), Johnny Cardoso (€22.0M), Malik Tillman (€35.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does David Ayala play and who plays similarly?
David Ayala plays as a Midfielder. Players with a comparable positional profile include Kevin Paredes (United States, €3.0M); Johnny Cardoso (Brazil, €22.0M); Malik Tillman (United States, €35.0M); Aleix García (Spain, €20.0M).
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.