2025/26 archive

Marcus Edwards

Free kicks #3

2025/26 season archive

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

Burnley

Pace

0.8

points per gameweek

Minutes

48%

reached 60' · 11 of 23 starts

Market

Selling

207 net transfers

How he ranks

23 games · 141 midfielders

Points

56th4.34

xGI

53rd0.28

DefCon

13th5.7

BPS

28th16.1

Minutes

1st1058

DefCon is what drags him — 13th of 141, against 56th for points.

Final price£4.7m

Form (10 GW)0.8

Pts / Match2.2

GW38 Pts1

Total Pts514.3 per 90

Total Bonus20.2 per 90

ICT Index68.9

Selected by %0.1%

xGI3.30.3 per 90

G+A − xGI+0.7overperforming

On dutyFree kicks#3DefCon bonus0/23 apps

Minutes and bonus

Started

11/23

48% of appearances

Reached 60'

48%

11 of 23 games

Bonus won

in 1 of 23 games

BPS per game

8.2

4% bonus strike rate

Where the points come from

Appearance3467%

Assists918%

Goals510%

Bonus24%

Clean sheets12%

67% of his points earned came from appearance. That is a narrow base — if it stops, most of the return stops with it. 51 earned

Are the returns real?

His goals and assists are in line with the chances behind them — +0.7 against expectation over 1058 minutes.

Defensive Contribution

He averages 2.9 against a line of 12, so DefCon is not a realistic source of points for him.

Cleared

0/23

0% of games

Average

2.9

line is 12

Versus the line

-9.1

short on average

Action mix

16% tackles · 9% CBI · 75% recoveries

Against each level of opponent

His return barely moves with the difficulty of the opponent.

too few games(1)

too few games(2)

2 per game(14)

3.17 per game(6)

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

Gameweek log

	Opponent
1	TOT (A)	5	1	0	0	0	0	0	0	3	0.0	0.0	0.0	0.0	£5.0m
2	SUN (H)	0	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	£5.0m
3	MUN (A)	0	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	£4.9m
4	LIV (H)	0	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	£4.9m
5	NFO (H)	0	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	£4.8m
6	MCI (A)	0	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	£4.8m
7	AVL (A)	0	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	£4.8m
8	LEE (H)	0	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	£4.8m
9	WOL (A)	0	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	£4.7m
10	ARS (H)	8	1	0	0	0	0	0	0	0	0.1	0.0	0.1	0.1	£4.7m
11	WHU (A)	9	1	0	0	0	1	0	0	5	0.1	0.0	0.1	1.0	£4.7m
12	CHE (H)	0	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	£4.7m
13	BRE (A)	0	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	£4.7m
14	CRY (H)	32	1	0	0	0	0	2	0	5	0.2	0.1	0.3	0.0	£4.7m
15	NEW (A)	1	1	0	0	0	0	0	0	8	0.0	0.2	0.2	0.0	£4.7m
16	FUL (H)	28	1	0	0	0	0	1	0	4	0.0	0.1	0.1	0.2	£4.7m
17	BOU (A)	13	4	0	1	0	0	2	0	15	0.0	0.3	0.3	0.3	£4.7m
18	EVE (H)	87	3	0	0	1	0	8	0	15	0.0	0.4	0.4	0.8	£4.7m
19	NEW (H)	90	2	0	0	0	3	6	0	8	0.3	0.1	0.4	2.3	£4.7m
20	BHA (A)	35	1	0	0	0	0	0	0	1	0.0	0.2	0.2	0.1	£4.7m
21	MUN (H)	90	5	0	1	0	2	5	0	26	0.1	0.0	0.1	2.5	£4.7m
22	LIV (A)	89	9	1	0	0	1	4	2	27	0.1	0.0	0.2	3.2	£4.7m
23	TOT (H)	84	2	0	0	0	1	7	0	4	0.0	0.1	0.1	1.6	£4.7m
24	SUN (A)	68	2	0	0	0	2	3	0	7	0.0	0.0	0.0	1.1	£4.7m
25	WHU (H)	66	2	0	0	0	2	1	0	3	0.4	0.0	0.5	1.0	£4.7m
26	CRY (A)	72	5	0	1	0	2	4	0	18	0.0	0.1	0.1	1.5	£4.7m
27	CHE (A)	90	2	0	0	0	1	8	0	6	0.2	0.0	0.2	2.0	£4.7m
28	BRE (H)	0	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	£4.7m
29	EVE (A)	0	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	£4.7m
30	BOU (H)	24	1	0	0	0	0	4	0	4	0.0	0.0	0.0	1.4	£4.7m
31	FUL (A)	12	1	0	0	0	1	1	0	2	0.0	0.0	0.0	1.3	£4.7m
32	BHA (H)	74	2	0	0	0	1	3	0	9	0.0	0.0	0.0	1.8	£4.7m
33	NFO (A)	63	2	0	0	0	1	7	0	7	0.0	0.0	0.0	0.9	£4.7m
33	MCI (H)	3	1	0	0	0	0	0	0	3	0.0	0.0	0.0	1.1	£4.7m
35	LEE (A)	0	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	£4.7m
36	AVL (H)	0	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	£4.7m
37	ARS (A)	0	0	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	£4.7m
38	WOL (H)	15	1	0	0	0	0	1	0	9	0.0	0.1	0.1	0.5	£4.7m

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

2.7

points, average

Direction

−0.18

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

GW22–30: model expected 24 pts · he scored 23 (−1 vs expectation)

Market

Price History

Selected by %

0.1%

Net transfers, latest GW

−207

Marcus Edwards

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