2025/26 archive

Joël Veltman

2025/26 season archive

Veltman is not in a 2026/27 Premier League squad, so these figures are final rather than live. Browse 2026/27 players.

Brighton

Pace

1.3

points per gameweek

Minutes

38%

reached 60' · 9 of 24 starts

Market

Buying

227 net transfers

How he ranks

24 games · 119 defenders

Points

64th3.95

xGI

53rd0.12

xGC

33rd1.48

DefCon

66th8.5

BPS

64th15.1

Minutes

3rd1047

xGC is what drags him — 33rd of 119, against 64th for points.

Final price£4.3m

Form (10 GW)1.3

Pts / Match1.9

GW38 Pts0

Total Pts464.0 per 90

Total Bonus10.1 per 90

ICT Index39.6

Selected by %0.1%

xGI1.40.1 per 90

G+A − xGI−0.4underperforming

On dutyDefCon bonus3/24 apps

Minutes and bonus

Started

9/24

38% of appearances

Reached 60'

38%

9 of 24 games

Bonus won

in 1 of 24 games

BPS per game

7.3

4% bonus strike rate

Where the points come from

Appearance3361%

Clean sheets815%

Goals611%

DefCon611%

Bonus12%

Cards-5

Goals conceded-3

61% of his points earned came from appearance. That is a narrow base — if it stops, most of the return stops with it. 54 earned, 46 net

Are the returns real?

His goals and assists are in line with the chances behind them — −0.3 against expectation over 1047 minutes.

Full seasons on record

2024/25 −1.8

2023/24 +1.0

2022/23 −0.7

2021/22 +2.0

2020/21 +2.0

Goals and assists minus xGI, per season. Positive means he finished above the chances he had.

Defensive Contribution

He averages 4.1 against a line of 10, so DefCon is not a realistic source of points for him.

Cleared

3/24

13% of games

Average

4.1

line is 10

Versus the line

-5.9

short on average

Action mix

31% tackles · 69% CBI

Against each level of opponent

His return barely moves with the difficulty of the opponent.

too few games(2)

2.2 per game(15)

0.8 per game(5)

1 is the easiest opponent, 5 the hardest. Bracketed figure is appearances at that level.

Gameweek log

	Opponent
1	FUL (H)	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.5m
2	EVE (A)	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.5m
3	MCI (H)	90	1	0	0	1	5	0	5	0.0	0.0	0.0	1.8	1	£4.4m
4	BOU (A)	90	3	0	0	2	10	0	13	0.0	0.0	0.0	1.4	0	£4.4m
5	TOT (H)	90	3	0	0	2	15	0	11	0.0	0.0	0.0	1.2	0	£4.4m
6	CHE (A)	54	0	0	0	1	6	0	-1	0.0	0.0	0.0	1.3	1	£4.4m
7	WOL (A)	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.4m
8	NEW (H)	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.4m
9	MUN (A)	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.4m
10	LEE (H)	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.4m
11	CRY (A)	15	0	0	0	0	2	0	0	0.0	0.0	0.0	0.3	1	£4.3m
12	BRE (H)	1	1	0	0	0	2	0	5	0.0	0.0	0.0	0.8	0	£4.3m
13	NFO (A)	6	1	0	0	0	3	0	4	0.0	0.0	0.0	0.0	0	£4.3m
14	AVL (H)	12	1	0	0	1	0	0	-1	0.0	0.0	0.0	0.6	0	£4.3m
15	WHU (H)	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.3m
16	LIV (A)	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.3m
17	SUN (H)	45	1	0	0	0	4	0	13	0.0	0.1	0.1	0.6	0	£4.3m
18	ARS (A)	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.3m
19	WHU (A)	90	10	1	0	2	11	1	22	0.6	0.0	0.6	2.1	0	£4.3m
20	BUR (H)	90	6	0	1	0	9	0	30	0.3	0.0	0.3	0.3	0	£4.3m
21	MCI (A)	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.3m
22	BOU (H)	90	2	0	0	1	8	0	12	0.1	0.0	0.1	1.3	0	£4.3m
23	FUL (A)	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.3m
24	EVE (H)	20	1	0	0	1	3	0	0	0.0	0.0	0.0	0.8	0	£4.3m
25	CRY (H)	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.3m
26	AVL (A)	90	1	0	0	1	5	0	4	0.0	0.0	0.0	0.7	1	£4.3m
27	BRE (A)	25	1	0	0	0	2	0	4	0.0	0.0	0.0	0.9	0	£4.3m
28	NFO (H)	19	1	0	0	0	0	0	5	0.0	0.0	0.0	0.6	0	£4.3m
29	ARS (H)	13	1	0	0	0	3	0	4	0.0	0.0	0.0	0.0	0	£4.3m
30	SUN (A)	1	1	0	0	0	2	0	4	0.0	0.0	0.0	0.1	0	£4.3m
31	LIV (H)	1	1	0	0	0	0	0	3	0.0	0.0	0.0	0.0	0	£4.3m
32	BUR (A)	2	1	0	0	0	0	0	3	0.0	0.0	0.0	0.0	0	£4.3m
33	TOT (A)	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.3m
33	CHE (H)	45	1	0	0	0	4	0	6	0.0	0.0	0.0	0.3	0	£4.3m
35	NEW (A)	62	1	0	0	1	0	0	5	0.0	0.0	0.0	1.7	1	£4.3m
36	WOL (H)	32	1	0	0	0	1	0	3	0.0	0.0	0.0	0.2	0	£4.3m
37	LEE (A)	64	6	0	1	0	4	0	22	0.2	0.1	0.2	0.2	0	£4.3m
38	MUN (H)	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	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.

Expected per GW

1.9

points, average

Direction

+0.22

broadly steady

Sample

gameweeks behind it

Direction = last five gameweeks vs the five before. The model is injury-blind.

Points by gameweek · with model expectation

Points scoredModel expectation, set before kick-off

GW8–27: model expected 15 pts · he scored 4 (−11 vs expectation)

Market

Price History

Selected by %

0.1%

Net transfers, latest GW

+227

Joël Veltman

How he ranks?

Minutes and bonus?

Where the points come from?

Are the returns real??

Defensive Contribution?

Against each level of opponent?

Gameweek log

What the model expects

Points by gameweek · with model expectation?

Market

Price History?

How he ranks

Minutes and bonus

Where the points come from

Are the returns real?

Defensive Contribution

Against each level of opponent

Points by gameweek · with model expectation

Price History