José Malheiro de Sá
2025/26 season archive
José Sá 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
23 games · 23 goalkeepers
Minutes and bonus
Where the points come from
55% of his points earned came from appearance. That is a narrow base — if it stops, most of the return stops with it. 83 earned, 68 net
Are the returns real?
His goals and assists are in line with the chances behind them — −0.0 against expectation over 2070 minutes.
Goals and assists minus xGI, per season. Positive means he finished above the chances he had.
Against each level of opponent
He scores 2.2 more per game against the easiest opponents he faced than the hardest — a fixture-dependent asset.
1 is the easiest opponent, 5 the hardest. Bracketed figure is appearances at that level.
Gameweek log
| Opponent | ||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | MCI (H) | 90 | 0 | 0 | 0 | 0 | 4 | 0 | 0 | 0 | -8 | 0.0 | 0.0 | 0.0 | 2.5 | 0 | 0 | £4.5m |
| 2 | BOU (A) | 90 | 3 | 0 | 0 | 0 | 1 | 3 | 0 | 0 | 14 | 0.0 | 0.0 | 0.0 | 1.3 | 0 | 0 | £4.5m |
| 3 | EVE (H) | 90 | 1 | 0 | 0 | 0 | 3 | 1 | 0 | 0 | 1 | 0.0 | 0.0 | 0.0 | 1.9 | 0 | 0 | £4.5m |
| 4 | NEW (A) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.5m |
| 5 | LEE (H) | 90 | 1 | 0 | 0 | 0 | 3 | 1 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.5 | 0 | 0 | £4.5m |
| 6 | TOT (A) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.5m |
| 7 | BHA (H) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 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) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 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) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.3m |
| 14 | NFO (H) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.3m |
| 15 | MUN (H) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.3m |
| 16 | ARS (A) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.2m |
| 17 | BRE (H) | 90 | 2 | 0 | 0 | 0 | 2 | 4 | 0 | 0 | 14 | 0.0 | 0.0 | 0.0 | 1.3 | 0 | 0 | £4.2m |
| 18 | LIV (A) | 90 | 1 | 0 | 0 | 0 | 2 | 2 | 0 | 0 | 7 | 0.0 | 0.0 | 0.0 | 1.5 | 0 | 0 | £4.2m |
| 19 | MUN (A) | 90 | 4 | 0 | 0 | 0 | 1 | 5 | 0 | 1 | 22 | 0.0 | 0.0 | 0.0 | 0.8 | 0 | 0 | £4.2m |
| 20 | WHU (H) | 90 | 6 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 23 | 0.0 | 0.0 | 0.0 | 0.3 | 0 | 0 | £4.2m |
| 21 | EVE (A) | 90 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 4 | 0.0 | 0.0 | 0.0 | 0.9 | 1 | 0 | £4.2m |
| 22 | NEW (H) | 90 | 7 | 0 | 0 | 1 | 0 | 2 | 0 | 1 | 28 | 0.0 | 0.0 | 0.0 | 0.9 | 0 | 0 | £4.2m |
| 23 | MCI (A) | 90 | 1 | 0 | 0 | 0 | 2 | 2 | 0 | 0 | 5 | 0.0 | 0.0 | 0.0 | 0.9 | 0 | 0 | £4.2m |
| 24 | BOU (H) | 90 | 1 | 0 | 0 | 0 | 2 | 2 | 0 | 0 | 10 | 0.0 | 0.0 | 0.0 | 1.4 | 0 | 0 | £4.2m |
| 25 | CHE (H) | 90 | 2 | 0 | 0 | 0 | 3 | 3 | 0 | 0 | 10 | 0.0 | 0.0 | 0.0 | 3.4 | 0 | 0 | £4.2m |
| 26 | NFO (A) | 90 | 12 | 0 | 0 | 1 | 0 | 10 | 0 | 3 | 50 | 0.0 | 0.0 | 0.0 | 2.5 | 0 | 0 | £4.2m |
| 26 | ARS (H) | 90 | 1 | 0 | 0 | 0 | 2 | 2 | 0 | 0 | 7 | 0.0 | 0.0 | 0.0 | 1.9 | 0 | 0 | £4.2m |
| 27 | CRY (A) | 90 | 2 | 0 | 0 | 0 | 1 | 2 | 0 | 0 | 11 | 0.0 | 0.0 | 0.0 | 2.0 | 0 | 0 | £4.2m |
| 28 | AVL (H) | 90 | 8 | 0 | 0 | 1 | 0 | 4 | 0 | 1 | 31 | 0.0 | 0.0 | 0.0 | 1.0 | 0 | 0 | £4.2m |
| 29 | LIV (H) | 90 | 3 | 0 | 0 | 0 | 1 | 5 | 0 | 0 | 20 | 0.0 | 0.0 | 0.0 | 1.8 | 0 | 0 | £4.2m |
| 30 | BRE (A) | 90 | 0 | 0 | 0 | 0 | 2 | 1 | 0 | 0 | 4 | 0.0 | 0.0 | 0.0 | 2.6 | 1 | 0 | £4.2m |
| 32 | WHU (A) | 90 | 1 | 0 | 0 | 0 | 4 | 3 | 0 | 0 | 2 | 0.0 | 0.0 | 0.0 | 2.4 | 0 | 0 | £4.2m |
| 33 | LEE (A) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.2m |
| 34 | TOT (H) | 90 | 2 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 9 | 0.0 | 0.0 | 0.0 | 0.9 | 0 | 0 | £4.2m |
| 35 | SUN (H) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.2m |
| 36 | BHA (A) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.2m |
| 37 | FUL (H) | 90 | 3 | 0 | 0 | 0 | 1 | 4 | 0 | 0 | 14 | 0.0 | 0.0 | 0.0 | 1.6 | 0 | 0 | £4.2m |
| 38 | BUR (A) | 90 | 6 | 0 | 0 | 0 | 1 | 7 | 0 | 2 | 25 | 0.0 | 0.0 | 0.0 | 1.0 | 0 | 0 | £4.2m |
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
GW8–38: model expected 56 pts · he scored 60 (+4 vs expectation)