Best Alternatives to Josh Brownhill

Top 3 Alternatives to Josh Brownhill

1. 1.Will Hughes84% DNA match·Crystal Palace€6.0M
2. 2.Tijjani Reijnders83% DNA match·Manchester City€60.0M
3. 3.Josh Cullen83% DNA match·Burnley€6.0M

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

Playing Style Analysis

Brownhill is the rare box-to-box midfielder who earns his wage not through elegance but through a quietly ruthless efficiency in the spaces most players ignore. His goals-per-90 sits in the top 10% of the league — remarkable for someone who touches the ball below average in volume, suggesting he's doing far more with far less possession time than his peers. His interception numbers (top 20%) reveal a midfielder who reads the game structurally, anticipating rather than reacting, which partly explains why his ground duel win rate looks poor on the surface — he's often intercepting before the duel even happens. The three most similar players to Josh Brownhill by playing style are:

• Will Hughes(84% match) — A Box-to-Box. Statistically, he stands out as naturally left-footed, a capable chance creator (1.2 key passes/90), heavily involved in play (55 touches/90) and active off the ball (2.0 press score/90), contributing to defensive transitions.
• Tijjani Reijnders(83% match) — A Midfielder. Statistically, he stands out as a capable chance creator (1.0 key passes/90), a constant goal threat (2.6 shots/90), a regular goalscorer (0.29 goals/90), meticulous in distribution (89% pass accuracy) and heavily involved in play (61 touches/90).
• Josh Cullen(83% match) — A Balanced Midfielder. Statistically, he stands out as active in the tackle (1.8 tackles/90), wins the physical battle (55% duel success), penetrates with forward passing (9.2 final-third passes/90), heavily involved in play (64 touches/90), uses long balls frequently (5.7/90) and active off the ball (2.5 press score/90), contributing to defensive transitions.

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