2025/26 archive

Axel Tuanzebe

2025/26 season archive

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

Burnley

Pace

0.7

points per gameweek

Minutes

93%

reached 60' · 14 of 14 starts

Market

Buying

2,023 net transfers

How he ranks

14 games · 119 defenders

Points

7th2.55

xGI

14th0.05

xGC

0th2.23

DefCon

74th9

BPS

4th7.6

Minutes

8th1201

Final price£3.9m

Form (10 GW)0.7

Pts / Match2.4

GW38 Pts2

Total Pts342.5 per 90

Total Bonus00.0 per 90

ICT Index34.1

Selected by %0.9%

xGI0.70.1 per 90

G+A − xGI+0.3overperforming

On dutyDefCon bonus5/14 apps

Minutes and bonus

Started

14/14

100% of appearances

Reached 60'

93%

13 of 14 games

Bonus won

in 0 of 14 games

BPS per game

7.3

0% bonus strike rate

He is a different player by venue. 3.57 per game at home (7), 1.29 away (7).

Where the points come from

Appearance2757%

DefCon1021%

Goals613%

Clean sheets49%

Goals conceded-10

Own goals-2

Cards-1

57% of his points earned came from appearance. That is a narrow base — if it stops, most of the return stops with it. 47 earned, 34 net

Are the returns real?

His goals and assists are in line with the chances behind them — +0.3 against expectation over 1201 minutes.

Full seasons on record

2024/25 +0.5

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

Defensive Contribution

He averages 8.6 against a line of 10, so he is about one action short in a typical week.

Cleared

5/14

36% of games

Average

8.6

line is 10

Versus the line

-1.4

short on average

Action mix

12% tackles · 88% CBI

Against each level of opponent

His return barely moves with the difficulty of the opponent.

too few games(1)

3.33 per game(3)

2 per game(6)

2.67 per game(3)

too few games(1)

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

Gameweek log

	Opponent
1	TOT (A)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.0m
2	SUN (H)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.0m
3	MUN (A)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£4.0m
4	LIV (H)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£3.9m
5	NFO (H)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£3.9m
6	MCI (A)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£3.9m
7	AVL (A)	90	1	0	0	2	7	6	0.0	0.0	0.0	1.4	0	£3.9m
8	LEE (H)	90	8	0	1	0	11	23	0.0	0.0	0.0	2.6	0	£3.9m
9	WOL (A)	90	1	0	0	2	9	4	0.0	0.0	0.0	2.5	0	£3.9m
10	ARS (H)	90	3	0	0	2	19	20	0.0	0.0	0.0	2.4	0	£3.9m
11	WHU (A)	90	3	0	0	3	10	5	0.0	0.0	0.0	3.0	0	£3.9m
12	CHE (H)	90	1	0	0	2	7	6	0.0	0.0	0.0	1.7	0	£3.9m
13	BRE (A)	90	0	0	0	3	7	-9	0.0	0.0	0.0	3.1	1	£3.9m
14	CRY (H)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£3.9m
15	NEW (A)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£3.9m
16	FUL (H)	76	1	0	0	3	4	4	0.0	0.1	0.1	2.2	0	£3.9m
17	BOU (A)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£3.9m
18	EVE (H)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£3.9m
19	NEW (H)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£3.9m
20	BHA (A)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£3.9m
21	MUN (H)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£3.9m
22	LIV (A)	90	4	0	0	1	11	7	0.0	0.0	0.0	3.2	0	£3.9m
23	TOT (H)	90	7	1	0	2	7	18	0.6	0.0	0.6	2.0	0	£3.9m
24	SUN (A)	45	-2	0	0	2	5	-3	0.0	0.0	0.0	0.7	0	£3.9m
25	WHU (H)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£3.9m
26	CRY (A)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£3.9m
27	CHE (A)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£3.9m
28	BRE (H)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£3.9m
29	EVE (A)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£3.9m
30	BOU (H)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£3.9m
31	FUL (A)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£3.9m
32	BHA (H)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£3.9m
33	NFO (A)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£3.9m
33	MCI (H)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£3.9m
35	LEE (A)	0	0	0	0	0	0	0	0.0	0.0	0.0	0.0	0	£3.9m
36	AVL (H)	90	3	0	0	2	10	2	0.0	0.0	0.0	1.4	0	£3.9m
37	ARS (A)	90	2	0	0	1	5	8	0.0	0.0	0.0	1.3	0	£3.9m
38	WOL (H)	90	2	0	0	1	8	11	0.0	0.0	0.0	2.1	0	£3.9m

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

1.8

points, average

Direction

0.00

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

GW9–38: model expected 29 pts · he scored 9 (−20 vs expectation)

Market

Price History

Selected by %

0.9%

Net transfers, latest GW

+2023

Axel Tuanzebe

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