Best Alternatives to Will Vaulks
Players most similar to Will Vaulks (Midfielder, €2.4M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.
Top 3 Alternatives to Will Vaulks
- 1.Ethan Ampadu82% DNA match·Leeds United€20.0M
- 2.Morgan Gibbs-White81% DNA match·Nottingham Forest€65.0M
- 3.Anton Stach81% DNA match·Leeds United€20.0M
Ranked by AI DNA similarity — 768 dimensions across playing style, pressing intensity, and tactical fit.
Intelligence Verdict
“A Box-to-Box....”
See Full Verdict + Share Card →Playing Style Analysis
A Box-to-Box. Statistically, he stands out as a capable chance creator (1.2 key passes/90), active in the tackle (2.3 tackles/90), wins the physical battle (55% duel success), penetrates with forward passing (12.6 final-third passes/90), central to possession (71 touches/90), uses long balls frequently (10.1/90) and a high-intensity presser (press score 3.2/90), constantly disrupting opposition build-up. The three most similar players to Will Vaulks by playing style are:
- Ethan Ampadu(82% match) — A Box-to-Box. Statistically, he stands out as active in the tackle (2.4 tackles/90), meticulous in distribution (85% pass accuracy), wins the physical battle (63% duel success), heavily involved in play (68 touches/90) and active off the ball (3.0 press score/90), contributing to defensive transitions.
- Morgan Gibbs-White(81% match) — A Creator. Statistically, he stands out as a capable chance creator (1.4 key passes/90), a proven goalscorer (0.40 goals/90) and heavily involved in play (50 touches/90).
- Anton Stach(81% match) — A Box-to-Box. Statistically, he stands out as an elite creator (2.5 key passes/90), a regular goalscorer (0.20 goals/90), active in the tackle (2.4 tackles/90), heavily involved in play (58 touches/90), active off the ball (2.5 press score/90), contributing to defensive transitions and top 10% creator in the league.
Transfer Intelligence
Ethan Ampadu delivers 82% of the same playing style, at a 751% premium over Will Vaulks, with 0.58 key passes per 90 at age 25.
Similarity is calculated using per-90 performance data across multiple playing style dimensions. How Player DNA matching works →
Similar Players — Ranked by DNA Similarity
Ask AI: Why are these players similar?
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