Per-90 performance rankings · Rising Transfers DNA Analysis · 25 players ranked
Based on per-90 statistics across 25 Ligue 1 midfielders in 2025/26, Vitinha leads the ranking as a Metronome with a composite score of 3.45. Kang-in Lee (Creator) ranks second at 2.95, followed by Pierre-Emile Højbjerg (Metronome) at 2.78. All rankings are calculated using Rising Transfers' 47-dimension per-90 analysis methodology.
Methodology: Per-90 stats explained · DNA matching
29 games · Portugal
27 games · South Korea
| # | Player | Style | KP/90 | Goals/90 | TW/90 | Games | |
|---|---|---|---|---|---|---|---|
| 1 | Vitinha | Metronome | 1.44 | 0.04 | 0.73 | 29 | Similar → |
| 2 | Kang-in Lee | Creator | 3.55 | 0.18 | 0.49 | 27 | Similar → |
| 3 | Pierre-Emile Højbjerg | Metronome | 1.46 | 0.13 | 0.85 | 32 | Similar → |
| 4 | Maxime Lopez | Metronome | 1.97 | 0.00 | 0.80 | 26 | Similar → |
| 5 | Valentin Rongier | Metronome | 1.44 | 0.07 | 1.58 | 31 | Similar → |
| 6 | Cristian Cásseres Jr. | Ball-Winner | 1.43 | 0.07 | 1.58 | 31 | Similar → |
| 7 | Aron Dønnum | Box-to-Box | 2.34 | 0.15 | 1.16 | 28 | Similar → |
| 8 | Adrien Thomasson | Ball-Winner | 2.77 | 0.10 | 1.61 | 31 | Similar → |
| 9 | Mamadou Sangaré | Metronome | 1.53 | 0.12 | 2.22 | 28 | Similar → |
| 10 | Johann Lepenant | Ball-Winner | 1.39 | 0.00 | 2.57 | 28 | Similar → |
| 11 | Corentin Tolisso | Box-to-Box | 1.33 | 0.43 | 0.95 | 30 | Similar → |
| 12 | Tyler Morton | Ball-Winner | 1.03 | 0.07 | 1.15 | 29 | Similar → |
| 13 | Laurent Abergel | Metronome | 0.62 | 0.04 | 0.91 | 28 | Similar → |
| 14 | Benjamin André | Ball-Winner | 0.92 | 0.08 | 1.36 | 26 | Similar → |
| 15 | Pierre Lees-Melou | Ball-Winner | 0.81 | 0.05 | 1.93 | 22 | Similar → |
| 16 | Charles Vanhoutte | Box-to-Box | 0.76 | 0.00 | 1.34 | 26 | Similar → |
| 17 | Hákon Arnar Haraldsson | Creator | 1.99 | 0.30 | 0.50 | 31 | Similar → |
| 18 | Hugo Magnetti | Box-to-Box | 0.60 | 0.03 | 1.55 | 33 | Similar → |
| 19 | Tom Louchet | Box-to-Box | 1.39 | 0.20 | 0.79 | 27 | Similar → |
| 20 | Tanner Tessmann | Ball-Winner | 0.60 | 0.05 | 0.95 | 29 | Similar → |
| 21 | Joris Chotard | Ball-Winner | 0.39 | 0.07 | 1.17 | 33 | Similar → |
| 22 | Noah Doriann Cadiou | Metronome | 0.53 | 0.14 | 0.94 | 28 | Similar → |
| 23 | Aleksandr Golovin | Creator | 1.28 | 0.27 | 0.92 | 25 | Similar → |
| 24 | Hicham Boudaoui | Box-to-Box | 0.90 | 0.05 | 0.81 | 25 | Similar → |
| 25 | Morgan Sanson | Balanced Midfielder | 0.66 | 0.00 | 1.30 | 31 | Similar → |
KP = Key passes · TW = Tackles won · Int = Interceptions · Clr = Clearances · GC = Goals conceded
Based on per-90 data in 2025/26, Vitinha is the top-ranked midfielder in the Ligue 1. Vitinha is classified as a Metronome by Rising Transfers' DNA analysis system.
Rising Transfers ranks midfielders using a composite per-90 score across key performance dimensions specific to the position. All statistics are normalised per 90 minutes of play to allow fair comparison between players with different minutes. Only players with 1,350+ minutes (equivalent to approximately 15 full matches) are included to ensure statistical reliability.
Each player is assigned a DNA archetype (e.g. Creator, Ball-Winner, Pressing Forward) based on their playing style vector — a 768-dimensional representation of their per-90 performance across 47 metrics. The archetype describes how the player plays, not just their position.
Rankings are recalculated weekly as new match data is processed into Rising Transfers' DNA pipeline. The underlying per-90 statistics are sourced from live match data across the Ligue 1 season.
Rankings are generated by Rising Transfers using per-90 statistics from the 2025/26 Ligue 1 season. Only players with 1,350+ minutes in the current season are included to ensure statistical reliability. Scores are computed using a position-specific composite formula across 47 performance dimensions. Data is refreshed weekly. Learn more about our methodology →
Some players may be excluded due to data availability (e.g. mid-season transfers, injury absences, or cup-only appearances). Rankings reflect on-pitch statistical performance and do not account for team defensive structure or shot quality — elite players on dominant teams may rank lower on volume-based metrics.
