Best Alternatives to Hamed Al-Ghamdi

Top 3 Alternatives to Hamed Al-Ghamdi

1. 1.Antoni Milambo81% DNA match·Brentford€20.0M
2. 2.Ramiz Zerrouki81% DNA match·FC Twente€7.2M
3. 3.Alex Scott81% DNA match·AFC Bournemouth€40.0M

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

Playing Style Analysis

Al-Ghamdi is the rare midfielder who wins the ball on the ground better than almost anyone in the Pro League, yet barely bothers to press when it isn't his. That duel win rate—top 5% in the division—tells you he picks his battles with surgical precision rather than frantic energy, which explains why his press intensity sits in the bottom 10%: this isn't a high-octane press machine, it's a chess player. His 75.3 passes per 90 places him among the league's most involved distributors, though the counterintuitive sting is that his progressive passing lags badly—he touches the ball constantly but rarely advances it vertically, suggesting a sideways-first mentality. The three most similar players to Hamed Al-Ghamdi by playing style are:

• Antoni Milambo(81% match) — A Creator. Statistically, he stands out as a capable chance creator (1.2 key passes/90), a reliable supplier (0.23 assists/90) and creates high-quality scoring opportunities (0.59 big chances/90).
• Ramiz Zerrouki(81% match) — A Metronome. Statistically, he stands out as an elite creator (1.6 key passes/90), active in the tackle (2.3 tackles/90), penetrates with forward passing (11.6 final-third passes/90), central to possession (73 touches/90), switches play with precision (7.7 long balls/90, 63% accuracy) and active off the ball (2.8 press score/90), contributing to defensive transitions.
• Alex Scott(81% match) — A Box-to-Box. Statistically, he stands out as active in the tackle (1.9 tackles/90), wins the physical battle (55% duel success), heavily involved in play (63 touches/90) and a high-intensity presser (press score 3.1/90), constantly disrupting opposition build-up.

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