2025/26 archive

Freddie Potts

2025/26 season archive

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

West Ham

Pace

0.3

points per gameweek

Minutes

45%

reached 60' · 12 of 22 starts

Market

Selling

722 net transfers

How he ranks

22 games · 141 midfielders

Points

2nd2.87

xGI

9th0.1

DefCon

61st9.2

BPS

37th16.7

Minutes

7th1162

Points is what drags him — 2nd of 141, against 2nd for points.

Final price£4.3m

Form (10 GW)0.3

Pts / Match1.7

GW38 Pts0

Total Pts372.9 per 90

Total Bonus00.0 per 90

ICT Index37.1

Selected by %0.5%

xGI1.30.1 per 90

G+A − xGI−0.3underperforming

On dutyDefCon bonus1/22 apps

Minutes and bonus

Started

12/22

55% of appearances

Reached 60'

45%

10 of 22 games

Bonus won

in 0 of 22 games

BPS per game

9.8

0% bonus strike rate

Where the points come from

Appearance3284%

Assists38%

DefCon25%

Clean sheets13%

Cards-1

84% of his points earned came from appearance. That is a narrow base — if it stops, most of the return stops with it. 38 earned, 37 net

Are the returns real?

His goals and assists are in line with the chances behind them — −0.3 against expectation over 1162 minutes.

Defensive Contribution

He averages 5.4 against a line of 12, so DefCon is not a realistic source of points for him.

Cleared

1/22

5% of games

Average

5.4

line is 12

Versus the line

-6.6

short on average

Action mix

24% tackles · 43% CBI · 33% recoveries

Against each level of opponent

His return barely moves with the difficulty of the opponent.

too few games(2)

1.25 per game(4)

1.78 per game(9)

1.6 per game(5)

too few games(2)

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

Gameweek log

	Opponent
1	SUN (A)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.5m
2	CHE (H)	45	1	0	0	2	4	2	0.0	0.0	0.0	1.1	0	£4.5m
3	NFO (A)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.5m
4	TOT (H)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.4m
5	CRY (H)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.4m
6	EVE (A)	31	1	0	0	0	5	7	0.0	0.0	0.0	0.1	0	£4.4m
7	ARS (A)	29	1	0	0	1	1	3	0.0	0.0	0.0	1.0	0	£4.4m
8	BRE (H)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.4m
9	LEE (A)	26	1	0	0	0	4	10	0.0	0.0	0.0	0.0	0	£4.4m
10	NEW (H)	90	2	0	0	1	11	18	0.0	0.0	0.0	0.5	0	£4.4m
11	BUR (H)	61	4	0	0	1	13	19	0.0	0.1	0.1	0.4	0	£4.4m
12	BOU (A)	90	2	0	0	2	7	11	0.0	0.0	0.0	4.0	0	£4.4m
13	LIV (H)	87	2	0	0	1	6	16	0.0	0.0	0.0	0.9	0	£4.4m
14	MUN (A)	82	2	0	0	1	10	13	0.0	0.0	0.1	1.2	0	£4.4m
15	BHA (A)	26	0	0	0	1	1	3	0.0	0.1	0.1	1.1	1	£4.4m
16	AVL (H)	87	5	1	0	3	6	29	0.0	0.0	0.1	0.6	0	£4.4m
17	MCI (A)	78	2	0	0	3	6	19	0.1	0.0	0.1	1.6	0	£4.4m
18	FUL (H)	90	2	0	0	1	11	14	0.0	0.0	0.0	1.6	0	£4.4m
19	BHA (H)	90	2	0	0	2	7	9	0.0	0.0	0.0	2.9	0	£4.4m
20	WOL (A)	45	1	0	0	3	2	10	0.0	0.0	0.0	1.6	0	£4.4m
21	NFO (H)	10	1	0	0	1	2	3	0.0	0.0	0.0	0.8	0	£4.4m
22	TOT (A)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.4m
23	SUN (H)	15	1	0	0	0	3	6	0.0	0.6	0.6	0.1	0	£4.4m
24	CHE (A)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.4m
25	BUR (A)	33	1	0	0	0	4	4	0.0	0.0	0.0	0.1	0	£4.4m
26	MUN (H)	79	3	0	1	0	9	10	0.0	0.0	0.0	0.3	0	£4.4m
27	BOU (H)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.4m
28	LIV (A)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.4m
29	FUL (A)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.4m
30	MCI (H)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.4m
31	AVL (A)	45	1	0	0	1	4	3	0.0	0.0	0.0	1.1	0	£4.4m
32	WOL (H)	12	1	0	0	0	0	3	0.0	0.0	0.0	0.1	0	£4.4m
33	CRY (A)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.3m
34	EVE (H)	11	1	0	0	1	3	3	0.0	0.0	0.0	0.1	0	£4.3m
35	BRE (A)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.3m
36	ARS (H)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.3m
37	NEW (A)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.3m
38	LEE (H)	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

2.1

points, average

Direction

−0.16

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

GW13–23: model expected 23 pts · he scored 18 (−5 vs expectation)

Market

Price History

Selected by %

0.5%

Net transfers, latest GW

−722

Freddie Potts

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