Best Alternatives to P. Mattsson

Top 3 Alternatives to P. Mattsson

1. 1.Magnus Mattsson89% DNA match·FC København€4.3M
2. 2.Jesper Karlström84% DNA match·Udinese€4.0M
3. 3.Mikael Egill Ellertsson83% DNA match·Genoa€3.5M

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

Playing Style Analysis

Mattsson is the Championship’s premier middle-third scavenger, an aerial titan trapped in a midfielder’s frame who dominates the sky and the grass with equal ferocity. While his 46.4 passes per minute place him comfortably in the league’s top 30%, his true value lies in the destructive arts; his 63.6% aerial win rate and 1.61 interceptions per 90 put him in the elite 5th and 10th percentiles respectively, marking him as a defensive sentinel who reads the game two beats ahead of the opposition. Counterintuitively, his high press intensity (top 10%) suggests he isn't just a sitting anchor, but a proactive hunter who forces turnovers high up the pitch. The three most similar players to P. Mattsson by playing style are:

• Magnus Mattsson(89% match) — A Creator. Statistically, he stands out as an elite creator (2.6 key passes/90), a regular goalscorer (0.39 goals/90), a reliable supplier (0.20 assists/90), meticulous in distribution (89% pass accuracy), creates high-quality scoring opportunities (0.59 big chances/90), heavily involved in play (65 touches/90), active off the ball (2.1 press score/90), contributing to defensive transitions and top 10% creator in the league. However, he loses possession under pressure (1.6 dispossessed/90).
• Jesper Karlström(84% match) — A Box-to-Box. Statistically, he stands out as active in the tackle (1.9 tackles/90), wins the physical battle (58% duel success), heavily involved in play (50 touches/90) and active off the ball (2.2 press score/90), contributing to defensive transitions.
• Mikael Egill Ellertsson(83% match) — A Balanced Midfielder. Statistically, he stands out as naturally left-footed.

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