Profile
Season stats
Full career & schedule →Domestic-league season · Lyn.
Performance data · by competition
| Competition | Apps | G | A | Min | Match |
|---|---|---|---|---|---|
 1. Division | 14 | 3 | 0 | 986 | 6.42 |
 NM Cupen | 1 | 0 | 0 | 74 | 6.64 |
Scout report
M. Alassane Niang is a 20-year-old centre-forward at Lyn, rated 33.4 overall by Field Insider's model, ranking 9th of 161 on scout potential in the 1. Division and 815th of 995 U-21 players tracked. A young player, he has been a rotation option this season (36.5% of available minutes). He brings 0.27 goal contributions per 90 (0.27 goals, 0 assists). Below: strengths, watch-points, market-value outlook and the latest transfer news on Niang.
Judged on this season alone, Niang graded 12 — a workmanlike campaign that ranks 13th of 26 of the 26 centre-forwards in the 1. Division, on 3 goals and 0 assists in 14 appearances (0.274 involvements per 90).
Year-on-year, that's a clear step up on last season (Season 0 → 12).
On long-term talent our Rating reads 33, top 16% of the 26 centre-forwards in the 1. Division. At 20 Niang is still climbing toward his ceiling, and a market index of 3.3 reflects that trajectory.
Output in context · Lyn finished 7th of 16 · a mid-table side
3 goals in 14 appearances (0.21 per game) — light end product the role wants to see climb.
Watch points
- Game time. Only 36.5% of available minutes — needs a settled run to prove the level.
- Output. 0.27 contributions per 90 is light for an attacking role — end product needs to climb.
- Level. Rates below a nailed-on top-tier starter on our model.
Outlook
With a Rating of 33.4, Niang carries the 4th-highest potential of the centre-forwards in the 1. Division of 26 — though on just 14 appearances this season, so the standing rests on a small sample. In the final third he profiles as a work-in-progress on end product (0.27 goal contributions per 90). At 20 the trajectory points up — potential sits near its ceiling (98/100) and market value should climb as minutes and output follow.
Generated from Field Insider's rating model · AI-written analysis to follow.
