Best Alternatives to Tanner Tessmann

Top 3 Alternatives to Tanner Tessmann

1. 1.Adrien Thomasson87% DNA match·Lens€4.5M
2. 2.Hugo Magnetti85% DNA match·Brest€6.0M
3. 3.Kévin Danois84% DNA match·Auxerre€10.0M

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

Playing Style Analysis

A Box-to-Box. Statistically, he stands out as a capable chance creator (1.0 key passes/90), active in the tackle (1.9 tackles/90), meticulous in distribution (85% pass accuracy), heavily involved in play (63 touches/90) and active off the ball (2.3 press score/90), contributing to defensive transitions. Note: this profile is based on 617 minutes of playing time this season. The three most similar players to Tanner Tessmann by playing style are:

• Adrien Thomasson(87% match) — A Box-to-Box. Statistically, he stands out as an elite creator (2.6 key passes/90), a prolific assist provider (0.45 assists/90), an aggressive ball-winner (2.6 tackles/90), creates high-quality scoring opportunities (0.60 big chances/90), heavily involved in play (70 touches/90), a high-intensity presser (press score 3.6/90), constantly disrupting opposition build-up and top 10% creator in the league. However, he can be exposed in 1v1 situations and loses possession under pressure (1.8 dispossessed/90).
• Hugo Magnetti(85% match) — A Balanced Midfielder. Statistically, he stands out as active in the tackle (2.4 tackles/90), reads the game exceptionally (1.5 interceptions/90), meticulous in distribution (87% pass accuracy), heavily involved in play (53 touches/90) and a high-intensity presser (press score 3.2/90), constantly disrupting opposition build-up.
• Kévin Danois(84% match) — A Box-to-Box. Statistically, he stands out as an elite creator (1.6 key passes/90), active in the tackle (2.3 tackles/90), meticulous in distribution (86% pass accuracy), heavily involved in play (67 touches/90) and active off the ball (2.9 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 →