Yerson Mosquera Valdelamar
2025/26 season archive
Mosquera is not in a 2026/27 Premier League squad, so these figures are final rather than live. Browse 2026/27 players.
Wolves
How he ranks
27 games · 119 defenders
Minutes and bonus
Where the points come from
57% of his points earned came from appearance. That is a narrow base — if it stops, most of the return stops with it. 90 earned, 61 net
Are the returns real?
He is falling short of his expected numbers by −3.1 over 2137 minutes.
There is no full season on record to compare it against.
Defensive Contribution
He averages 8.1 against a line of 10 — close enough that a busy game gets him there, but not reliably.
Against each level of opponent
His return barely moves with the difficulty of the opponent.
1 is the easiest opponent, 5 the hardest. Bracketed figure is appearances at that level.
Gameweek log
| Opponent | ||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | MCI (H) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.5m |
| 2 | BOU (A) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.5m |
| 3 | EVE (H) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.5m |
| 4 | NEW (A) | 65 | 2 | 0 | 0 | 0 | 1 | 0 | 6 | 0 | 4 | 0.0 | 0.0 | 0.0 | 1.4 | 0 | 0 | £4.4m |
| 5 | LEE (H) | 71 | 1 | 0 | 0 | 0 | 3 | 0 | 3 | 0 | 5 | 0.1 | 0.0 | 0.1 | 0.5 | 0 | 0 | £4.4m |
| 6 | TOT (A) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.4m |
| 7 | BHA (H) | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 4 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.4m |
| 8 | SUN (A) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.4m |
| 9 | BUR (H) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.4m |
| 10 | FUL (A) | 45 | -3 | 0 | 0 | 0 | 2 | 0 | 2 | 0 | -11 | 0.0 | 0.0 | 0.0 | 1.1 | 1 | 0 | £4.4m |
| 11 | CHE (A) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.3m |
| 12 | CRY (H) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.3m |
| 13 | AVL (A) | 76 | 1 | 0 | 0 | 0 | 1 | 0 | 3 | 0 | 3 | 0.1 | 0.0 | 0.1 | 0.9 | 1 | 0 | £4.3m |
| 14 | NFO (H) | 80 | 1 | 0 | 0 | 0 | 1 | 0 | 6 | 0 | 9 | 0.0 | 0.0 | 0.0 | 0.7 | 1 | 0 | £4.3m |
| 15 | MUN (H) | 90 | -1 | 0 | 0 | 0 | 4 | 0 | 9 | 0 | -1 | 0.0 | 0.1 | 0.1 | 4.1 | 1 | 0 | £4.3m |
| 16 | ARS (A) | 90 | 0 | 0 | 0 | 0 | 2 | 0 | 10 | 0 | 1 | 0.0 | 0.0 | 0.0 | 1.1 | 1 | 0 | £4.3m |
| 17 | BRE (H) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.3m |
| 18 | LIV (A) | 78 | 3 | 0 | 0 | 0 | 2 | 0 | 12 | 0 | 5 | 0.0 | 0.0 | 0.0 | 1.5 | 0 | 0 | £4.3m |
| 19 | MUN (A) | 90 | 4 | 0 | 0 | 0 | 1 | 0 | 14 | 0 | 14 | 0.5 | 0.1 | 0.6 | 0.8 | 0 | 0 | £4.3m |
| 20 | WHU (H) | 90 | 6 | 0 | 0 | 1 | 0 | 0 | 9 | 0 | 31 | 0.0 | 0.0 | 0.1 | 0.3 | 0 | 0 | £4.3m |
| 21 | EVE (A) | 90 | 3 | 0 | 0 | 0 | 1 | 0 | 13 | 0 | 16 | 0.0 | 0.0 | 0.0 | 0.9 | 1 | 0 | £4.3m |
| 22 | NEW (H) | 90 | 8 | 0 | 0 | 1 | 0 | 0 | 11 | 1 | 28 | 0.1 | 0.0 | 0.1 | 0.9 | 1 | 0 | £4.3m |
| 23 | MCI (A) | 90 | 0 | 0 | 0 | 0 | 2 | 0 | 8 | 0 | 2 | 0.3 | 0.0 | 0.3 | 0.9 | 1 | 0 | £4.3m |
| 24 | BOU (H) | 90 | 0 | 0 | 0 | 0 | 2 | 0 | 3 | 0 | -1 | 0.1 | 0.0 | 0.1 | 1.4 | 1 | 0 | £4.3m |
| 25 | CHE (H) | 90 | 1 | 0 | 0 | 0 | 3 | 0 | 9 | 0 | -2 | 0.2 | 0.0 | 0.2 | 3.4 | 0 | 0 | £4.3m |
| 26 | NFO (A) | 90 | 6 | 0 | 0 | 1 | 0 | 0 | 9 | 0 | 24 | 0.0 | 0.0 | 0.0 | 2.5 | 0 | 0 | £4.3m |
| 26 | ARS (H) | 90 | 3 | 0 | 0 | 0 | 2 | 0 | 10 | 0 | 11 | 0.0 | 0.0 | 0.0 | 1.9 | 0 | 0 | £4.3m |
| 27 | CRY (A) | 90 | 4 | 0 | 0 | 0 | 1 | 0 | 10 | 0 | 11 | 0.1 | 0.1 | 0.2 | 1.4 | 0 | 0 | £4.3m |
| 28 | AVL (H) | 90 | 9 | 0 | 0 | 1 | 0 | 0 | 10 | 2 | 33 | 0.0 | 0.1 | 0.1 | 1.0 | 1 | 0 | £4.3m |
| 29 | LIV (H) | 31 | 1 | 0 | 0 | 0 | 1 | 0 | 3 | 0 | 4 | 0.0 | 0.0 | 0.0 | 0.7 | 0 | 0 | £4.3m |
| 30 | BRE (A) | 90 | 1 | 0 | 0 | 0 | 2 | 0 | 9 | 0 | 7 | 0.0 | 0.0 | 0.0 | 2.6 | 0 | 0 | £4.3m |
| 32 | WHU (A) | 70 | 0 | 0 | 0 | 0 | 3 | 0 | 6 | 0 | -1 | 0.1 | 0.1 | 0.1 | 1.7 | 1 | 0 | £4.3m |
| 33 | LEE (A) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.3m |
| 34 | TOT (H) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.3m |
| 35 | SUN (H) | 90 | 2 | 0 | 0 | 0 | 1 | 0 | 8 | 0 | 8 | 0.1 | 0.0 | 0.1 | 0.7 | 0 | 0 | £4.3m |
| 36 | BHA (A) | 90 | 3 | 0 | 0 | 0 | 3 | 0 | 17 | 0 | -2 | 0.2 | 0.0 | 0.2 | 1.6 | 0 | 0 | £4.3m |
| 37 | FUL (H) | 90 | 2 | 0 | 0 | 0 | 1 | 0 | 5 | 0 | -2 | 0.3 | 0.0 | 0.4 | 1.6 | 0 | 0 | £4.3m |
| 38 | BUR (A) | 90 | 3 | 0 | 0 | 0 | 1 | 0 | 13 | 0 | 9 | 0.2 | 0.0 | 0.3 | 1.0 | 1 | 0 | £4.3m |
What the model expects
From the same expected-points model that runs across the whole player pool — an estimate per gameweek, not a prediction of any single one.
Direction = last five gameweeks vs the five before. The model is injury-blind.
Points by gameweek · with model expectation
GW15–38: model expected 46 pts · he scored 58 (+12 vs expectation)