Josh Laurent
2025/26 season archive
Laurent is not in a 2026/27 Premier League squad, so these figures are final rather than live. Browse 2026/27 players.
Burnley
How he ranks
33 games · 141 midfielders
Minutes and bonus
Where the points come from
75% of his points earned came from appearance. That is a narrow base — if it stops, most of the return stops with it. 65 earned, 56 net
Are the returns real?
His goals and assists are in line with the chances behind them — −0.3 against expectation over 1752 minutes.
Defensive Contribution
He averages 5.6 against a line of 12, so DefCon is not a realistic source of points for him.
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 | TOT (A) | 62 | 2 | 0 | 0 | 0 | 2 | 0 | 6 | 0 | 11 | 0.1 | 0.1 | 0.2 | 1.4 | 0 | 0 | £5.0m |
| 2 | SUN (H) | 21 | 1 | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 4 | 0.0 | 0.0 | 0.0 | 0.2 | 0 | 0 | £5.0m |
| 3 | MUN (A) | 14 | 0 | 0 | 0 | 0 | 1 | 0 | 4 | 0 | 1 | 0.0 | 0.0 | 0.0 | 1.1 | 1 | 0 | £5.0m |
| 4 | LIV (H) | 90 | 2 | 0 | 0 | 0 | 1 | 0 | 6 | 0 | 4 | 0.0 | 0.0 | 0.0 | 2.5 | 0 | 0 | £4.9m |
| 5 | NFO (H) | 90 | 2 | 0 | 0 | 0 | 1 | 0 | 5 | 0 | 11 | 0.0 | 0.0 | 0.0 | 1.1 | 0 | 0 | £4.9m |
| 6 | MCI (A) | 90 | 2 | 0 | 0 | 0 | 5 | 0 | 6 | 0 | 9 | 0.0 | 0.0 | 0.0 | 2.0 | 0 | 0 | £4.9m |
| 7 | AVL (A) | 81 | 2 | 0 | 0 | 0 | 2 | 0 | 9 | 0 | 13 | 0.0 | 0.0 | 0.0 | 1.1 | 0 | 0 | £4.9m |
| 8 | LEE (H) | 13 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 4 | 0.0 | 0.0 | 0.0 | 1.2 | 0 | 0 | £4.9m |
| 9 | WOL (A) | 21 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 7 | 0.0 | 0.0 | 0.0 | 0.3 | 0 | 0 | £4.9m |
| 10 | ARS (H) | 75 | 2 | 0 | 0 | 0 | 2 | 0 | 6 | 0 | 10 | 0.0 | 0.0 | 0.0 | 2.3 | 0 | 0 | £4.9m |
| 11 | WHU (A) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.9m |
| 12 | CHE (H) | 6 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 2 | 0.0 | 0.0 | 0.0 | 0.7 | 0 | 0 | £4.9m |
| 13 | BRE (A) | 15 | 1 | 0 | 0 | 0 | 3 | 0 | 1 | 0 | 7 | 0.0 | 0.0 | 0.0 | 1.6 | 0 | 0 | £4.9m |
| 14 | CRY (H) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.9m |
| 15 | NEW (A) | 25 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 3 | 0.0 | 0.0 | 0.0 | 0.3 | 1 | 0 | £4.8m |
| 16 | FUL (H) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.8m |
| 17 | BOU (A) | 90 | 4 | 0 | 0 | 0 | 1 | 0 | 15 | 0 | 8 | 0.0 | 0.0 | 0.0 | 1.4 | 0 | 0 | £4.8m |
| 18 | EVE (H) | 90 | 5 | 0 | 0 | 1 | 0 | 0 | 13 | 0 | 13 | 0.1 | 0.0 | 0.1 | 0.8 | 0 | 0 | £4.8m |
| 19 | NEW (H) | 90 | 10 | 1 | 0 | 0 | 3 | 0 | 15 | 1 | 36 | 0.2 | 0.0 | 0.2 | 2.3 | 0 | 0 | £4.8m |
| 20 | BHA (A) | 90 | 1 | 0 | 0 | 0 | 2 | 0 | 8 | 0 | 10 | 0.0 | 0.0 | 0.0 | 1.4 | 1 | 0 | £4.8m |
| 21 | MUN (H) | 90 | 4 | 0 | 0 | 0 | 2 | 0 | 14 | 0 | 17 | 0.0 | 0.0 | 0.0 | 2.5 | 0 | 0 | £4.8m |
| 22 | LIV (A) | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 3 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.8m |
| 23 | TOT (H) | 21 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.8 | 1 | 0 | £4.8m |
| 24 | SUN (A) | 45 | 1 | 0 | 0 | 0 | 1 | 0 | 4 | 0 | 12 | 0.0 | 0.0 | 0.0 | 0.8 | 0 | 0 | £4.8m |
| 25 | WHU (H) | 45 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 2 | 0.0 | 0.0 | 0.1 | 0.1 | 1 | 0 | £4.8m |
| 26 | CRY (A) | 90 | 2 | 0 | 0 | 0 | 2 | 0 | 6 | 0 | 5 | 0.1 | 0.0 | 0.1 | 1.8 | 0 | 0 | £4.8m |
| 27 | CHE (A) | 77 | 1 | 0 | 0 | 0 | 1 | 0 | 3 | 0 | 8 | 0.1 | 0.1 | 0.1 | 1.9 | 1 | 0 | £4.8m |
| 28 | BRE (H) | 45 | 1 | 0 | 0 | 0 | 3 | 0 | 4 | 0 | 9 | 0.0 | 0.0 | 0.0 | 1.8 | 0 | 0 | £4.8m |
| 29 | EVE (A) | 18 | 1 | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 3 | 0.0 | 0.0 | 0.0 | 0.1 | 0 | 0 | £4.8m |
| 30 | BOU (H) | 87 | 3 | 0 | 0 | 1 | 0 | 0 | 8 | 0 | 11 | 0.0 | 0.0 | 0.0 | 1.7 | 0 | 0 | £4.8m |
| 31 | FUL (A) | 90 | -1 | 0 | 0 | 0 | 3 | 0 | 6 | 0 | -9 | 0.3 | 0.0 | 0.3 | 2.1 | 0 | 1 | £4.8m |
| 32 | BHA (H) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.8m |
| 33 | NFO (A) | 7 | 1 | 0 | 0 | 0 | 1 | 0 | 3 | 0 | 7 | 0.0 | 0.0 | 0.0 | 0.2 | 0 | 0 | £4.8m |
| 33 | MCI (H) | 86 | 2 | 0 | 0 | 0 | 1 | 0 | 10 | 0 | 7 | 0.0 | 0.0 | 0.0 | 2.5 | 0 | 0 | £4.8m |
| 35 | LEE (A) | 53 | 1 | 0 | 0 | 0 | 2 | 0 | 2 | 0 | 1 | 0.0 | 0.0 | 0.0 | 0.9 | 0 | 0 | £4.8m |
| 36 | AVL (H) | 11 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 3 | 0.0 | 0.0 | 0.0 | 0.1 | 0 | 0 | £4.8m |
| 37 | ARS (A) | 19 | 1 | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.8m |
| 38 | WOL (H) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | £4.8m |
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
GW8–36: model expected 39 pts · he scored 23 (−16 vs expectation)