xgEdge

Fantasy Premier League

Who defends for points

About half a defender's season comes from a clean sheet his club keeps and an award he clears on his own, and no board on this site has ever printed either. Every defender and midfielder the game would let you field, ranked on the defensive half of the round ahead, with the rate behind the award, the clean-sheet probability behind the sheet and what he does at the other end printed beside them.

The best defensive week

Vitaly Janelt

MID · BRE · 5.0m · owned by 2.5%

1.06

Def pts

The award rests on 12.0 defensive contributions per 90, shrunk towards what players in his position actually do, against the 12 actions the game pays for.

Gameweek 6 · 5-round window · feed of 01/10 11:39

Vitaly Janelt is the best defensive return on the board: 1.06 projected defensive points in gameweek 6 as a midfielder, of which 0.87 is the contribution award, on a 21% chance of a clean sheet.

The award rests on 12.0 defensive contributions per 90, shrunk towards what players in his position actually do, against the 12 actions the game pays for. Of the 68 your filters leave: 0 defenders and 68 midfielders, ranked against each other.

Def pts

1.06

The clean sheet and the contribution award together, in the round ahead, which is what this board is ranked on.

DC/90

0.87

What the contribution award is worth to him: how often the model has him clearing 12 in a match, priced.

CS

21%

How often the model has his side keeping the sheet clean in the round ahead.

The top five on this board

The board as your controls leave it — the same five that open the table below.

  1. Ranked 1 Vitaly Janelt
    MID BRE vs
    1.06 Def pts
    DC/90
    12.0
    CS
    21%
    BPS/90
    21.8
    3.2
    1. AVL (A)
    2. LIV (H)
    3. HUL (A)
    4. NFO (H)
    5. BHA (A)
  2. Ranked 2 Anton Stach
    MID LEE vs
    0.92 Def pts
    DC/90
    11.6
    CS
    18%
    BPS/90
    17.3
    3.6
    1. ARS (A)
    2. MUN (H)
    3. SUN (A)
    4. BOU (A)
    5. TOT (H)
  3. Ranked 3 Alex Scott
    MID BOU vs
    0.91 Def pts
    DC/90
    11.5
    CS
    21%
    BPS/90
    26.0
    3.0
    1. CHE (A)
    2. SUN (H)
    3. MUN (A)
    4. LEE (H)
    5. IPS (A)
  4. Ranked 4 Ethan Ampadu
    MID LEE vs
    0.89 Def pts
    DC/90
    11.4
    CS
    18%
    BPS/90
    17.4
    3.6
    1. ARS (A)
    2. MUN (H)
    3. SUN (A)
    4. BOU (A)
    5. TOT (H)
  5. Ranked 5 Granit Xhaka
    MID SUN vs
    0.70 Def pts
    DC/90
    10.4
    CS
    21%
    BPS/90
    23.2
    2.8
    1. BHA (H)
    2. BOU (A)
    3. LEE (H)
    4. COV (A)
    5. CHE (H)
Position
Minutes played
Rounds ahead
Price
1 Vitaly Janelt 1.06
MID vs BRE · 5.0m · CS 21%
DC/90
12.0
DC pts
0.87
xGI
0.20
BPS/90
21.8
Start
92%
2 Anton Stach 0.92
MID vs LEE · 6.0m · CS 18%
DC/90
11.6
DC pts
0.75
xGI
0.26
BPS/90
17.3
Start
92%
3 Alex Scott 0.91
MID vs BOU · 6.1m · CS 21%
DC/90
11.5
DC pts
0.72
xGI
0.21
BPS/90
26.0
Start
92%
4 Ethan Ampadu 0.89
MID vs LEE · 5.4m · CS 18%
DC/90
11.4
DC pts
0.72
xGI
0.07
BPS/90
17.4
Start
92%
5 Granit Xhaka 0.70
MID vs SUN · 5.5m · CS 21%
DC/90
10.4
DC pts
0.51
xGI
0.27
BPS/90
23.2
Start
92%
MID vs MCI · 6.3m · CS 19%
DC/90
11.1
DC pts
0.48
xGI
0.17
BPS/90
20.7
Start
92%
7 Lewis Miley 0.56
MID vs NEW · 5.5m · CS 17%
DC/90
11.2
DC pts
0.41
xGI
0.04
BPS/90
15.5
Start
92%
MID vs TOT · 5.5m · CS 14%
DC/90
13.4
DC pts
0.45
xGI
0.03
BPS/90
16.8
Start
75%
MID vs MUN · 5.8m · CS 34%
DC/90
9.4
DC pts
0.19
xGI
0.27
BPS/90
20.8
Start
92%
10 Xaver Schlager 0.48
MID vs NFO · 5.0m · CS 24%
DC/90
11.1
DC pts
0.30
xGI
0.09
BPS/90
16.8
Start
75%
MID vs IPS · 5.0m · CS 21%
DC/90
12.9
DC pts
0.31
xGI
0.03
BPS/90
20.9
Start
70%
12 Bukayo Saka 0.41
MID vs ARS · 9.5m · CS 41%
DC/90
7.0
DC pts
0.04
xGI
0.91
BPS/90
29.6
Start
92%
13 Quinten Timber 0.40
MID vs CRY · 5.0m · CS 25%
DC/90
9.2
DC pts
0.18
xGI
0.11
BPS/90
16.0
Start
88%
14 Adam Wharton 0.39
MID vs CRY · 5.4m · CS 25%
DC/90
8.4
DC pts
0.16
xGI
0.15
BPS/90
15.9
Start
92%
MID vs HUL · 5.1m · CS 25%
DC/90
9.7
DC pts
0.20
xGI
0.26
BPS/90
25.4
Start
92%
MID vs EVE · 6.6m · CS 21%
DC/90
8.4
DC pts
0.19
xGI
0.37
BPS/90
22.0
Start
92%
MID vs ARS · 6.8m · CS 41%
DC/90
6.0
DC pts
0.01
xGI
0.58
BPS/90
32.7
Start
92%
MID vs BOU · 6.1m · CS 21%
DC/90
8.8
DC pts
0.18
xGI
0.56
BPS/90
32.5
Start
92%
19 Matt Grimes 0.37
MID vs COV · 4.9m · CS 28%
DC/90
7.8
DC pts
0.12
xGI
0.05
BPS/90
12.6
Start
92%
MID vs LIV · 7.0m · CS 22%
DC/90
8.4
DC pts
0.16
xGI
0.46
BPS/90
21.1
Start
92%
21 James Garner 0.35
MID vs EVE · 6.0m · CS 21%
DC/90
11.5
DC pts
0.19
xGI
0.10
BPS/90
19.5
Start
75%
22 Bruno Fernandes 0.34
MID vs MUN · 11.9m · CS 34%
DC/90
6.2
DC pts
0.03
xGI
0.77
BPS/90
29.6
Start
92%
23 Daichi Kamada 0.34
MID vs CRY · 5.0m · CS 25%
DC/90
7.8
DC pts
0.11
xGI
0.18
BPS/90
22.2
Start
92%
MID vs EVE · 5.0m · CS 21%
DC/90
8.1
DC pts
0.15
xGI
0.14
BPS/90
12.3
Start
92%
25 James McAtee 0.34
MID vs NFO · 5.5m · CS 24%
DC/90
8.4
DC pts
0.12
xGI
0.29
BPS/90
19.7
Start
92%
26 Bryan Mbeumo 0.33
MID vs MUN · 7.9m · CS 34%
DC/90
5.7
DC pts
0.02
xGI
0.77
BPS/90
22.0
Start
92%
MID vs BRE · 5.6m · CS 21%
DC/90
12.3
DC pts
0.21
xGI
0.29
BPS/90
21.3
Start
75%
28 Christos Tzolis 0.31
MID vs ARS · 6.3m · CS 41%
DC/90
6.2
DC pts
0.01
xGI
0.19
BPS/90
20.1
Start
92%
29 Matheus Cunha 0.31
MID vs MUN · 7.9m · CS 34%
DC/90
3.8
DC pts
0.00
xGI
0.32
BPS/90
21.0
Start
92%
30 Sandro Tonali 0.30
MID vs TOT · 5.3m · CS 14%
DC/90
8.7
DC pts
0.18
xGI
0.18
BPS/90
18.1
Start
92%
31 Regan Slater 0.29
MID vs HUL · 4.5m · CS 25%
DC/90
7.0
DC pts
0.06
xGI
0.16
BPS/90
13.8
Start
92%
32 Saša Lukić 0.29
MID vs IPS · 4.9m · CS 21%
DC/90
8.3
DC pts
0.09
xGI
0.09
BPS/90
15.3
Start
92%
33 Boubacar Kamara 0.28
MID vs AVL · 5.0m · CS 21%
DC/90
7.5
DC pts
0.09
xGI
0.05
BPS/90
17.3
Start
92%
34 Florian Wirtz 0.28
MID vs LIV · 7.3m · CS 22%
DC/90
8.1
DC pts
0.08
xGI
0.31
BPS/90
20.6
Start
92%
35 Iliman Ndiaye 0.27
MID vs MCI · 5.8m · CS 19%
DC/90
9.9
DC pts
0.12
xGI
0.23
BPS/90
25.7
Start
75%
MID vs BRE · 5.5m · CS 21%
DC/90
8.4
DC pts
0.11
xGI
0.45
BPS/90
18.8
Start
92%
37 Kevin Schade 0.26
MID vs BRE · 6.2m · CS 21%
DC/90
7.1
DC pts
0.07
xGI
0.37
BPS/90
27.8
Start
92%
38 Morgan Rogers 0.26
MID vs CHE · 7.7m · CS 24%
DC/90
6.7
DC pts
0.04
xGI
0.60
BPS/90
27.8
Start
92%
39 Diego Gómez 0.25
MID vs BHA · 5.0m · CS 18%
DC/90
7.6
DC pts
0.09
xGI
0.32
BPS/90
16.6
Start
92%
MID vs AVL · 5.9m · CS 21%
DC/90
7.7
DC pts
0.06
xGI
0.26
BPS/90
16.4
Start
92%
41 Jack Rudoni 0.25
MID vs COV · 4.9m · CS 28%
DC/90
9.8
DC pts
0.03
xGI
0.62
BPS/90
15.5
Start
75%
42 Frank Onyeka 0.23
MID vs COV · 4.9m · CS 28%
DC/90
8.1
DC pts
0.02
xGI
0.02
BPS/90
9.7
Start
75%
43 John McGinn 0.23
MID vs AVL · 5.4m · CS 21%
DC/90
6.6
DC pts
0.03
xGI
0.21
BPS/90
13.5
Start
92%
44 Julio Enciso 0.23
MID vs IPS · 5.5m · CS 21%
DC/90
7.0
DC pts
0.04
xGI
0.46
BPS/90
18.1
Start
92%
MID vs ARS · 5.4m · CS 41%
DC/90
5.5
DC pts
0.00
xGI
0.13
BPS/90
12.3
Start
75%
46 Harvey Barnes 0.22
MID vs NEW · 6.1m · CS 17%
DC/90
6.9
DC pts
0.06
xGI
0.22
BPS/90
21.0
Start
92%
MID vs NFO · 8.0m · CS 24%
DC/90
4.9
DC pts
0.01
xGI
0.59
BPS/90
23.2
Start
92%
48 Noah Sadiki 0.22
MID vs SUN · 4.9m · CS 21%
DC/90
6.7
DC pts
0.03
xGI
0.15
BPS/90
16.5
Start
92%
49 Enzo Le Fée 0.20
MID vs SUN · 5.7m · CS 21%
DC/90
5.0
DC pts
0.01
xGI
0.70
BPS/90
18.5
Start
92%
50 Pedro Neto 0.20
MID vs CHE · 6.5m · CS 24%
DC/90
7.7
DC pts
0.02
xGI
0.34
BPS/90
22.0
Start
75%
51 Alex Iwobi 0.19
MID vs FUL · 5.4m · CS 18%
DC/90
6.7
DC pts
0.03
xGI
0.36
BPS/90
20.7
Start
92%
52 Josh King 0.19
MID vs FUL · 5.5m · CS 18%
DC/90
6.3
DC pts
0.02
xGI
0.43
BPS/90
23.1
Start
92%
53 Rayan 0.19
MID vs BOU · 6.3m · CS 21%
DC/90
4.0
DC pts
0.00
xGI
0.27
BPS/90
9.3
Start
92%
54 Oscar Bobb 0.18
MID vs FUL · 5.5m · CS 18%
DC/90
7.5
DC pts
0.02
xGI
0.44
BPS/90
13.9
Start
92%
55 Pascal Groß 0.18
MID vs BHA · 5.8m · CS 18%
DC/90
5.7
DC pts
0.02
xGI
0.52
BPS/90
33.2
Start
92%
56 Ross Barkley 0.18
MID vs AVL · 5.0m · CS 21%
DC/90
8.2
DC pts
0.02
xGI
0.15
BPS/90
19.3
Start
75%
57 Roméo Lavia 0.16
MID vs CHE · 5.0m · CS 24%
DC/90
10.1
DC pts
0.03
xGI
0.30
BPS/90
21.3
Start
75%
58 Tyrique George 0.16
MID vs EVE · 5.5m · CS 21%
DC/90
5.9
DC pts
0.00
xGI
0.19
BPS/90
22.4
Start
75%
MID vs CRY · 5.5m · CS 25%
DC/90
7.8
DC pts
0.01
xGI
0.31
BPS/90
20.5
Start
75%
60 Noah Okafor 0.14
MID vs LEE · 5.8m · CS 18%
DC/90
6.1
DC pts
0.00
xGI
0.13
BPS/90
24.7
Start
75%
each row's Def pts, drawn to scale every bar on one axis of 0 to 2.0

What these columns are, and which of them is measured

Nothing on this page is derived here. Every column is a component the round-ahead projection has computed since the model was written — the clean sheet off the modelled scoreline, the concession off the same distribution, and the contribution award off the rate below — and the total beside them is those components added up rather than a second opinion about them.

The per-90 rate is shrunk towards what players in that position actually do, in proportion to how little football is behind it. A defender with one busy half has a raw per-90 above anybody's and would head a table sorted on it; that failure is why the shrinkage exists, and it is why the number here is smaller than the one the game publishes for him.

The award does not stack and it is not a rate: it is a threshold cleared once, 10 actions for a defender and 12 for a midfielder, which the game counts differently for the two — a midfielder's recoveries are in his total and a defender's are not. What the column holds is how likely he is to clear it, priced at what the game pays.

A clean sheet here is the probability that the opponent scores exactly zero, off the same fitted scoreline the rest of this site prices matches with. It is not one minus an average, and it is the reason this model exists rather than reading the game's own one-to-five fixture rating.

A dash in the rate column means the game publishes no defensive contribution total for that player at all. It is not a nought: nought would say he has produced none, where the dash says the figure is not in the feed.

The bonus column is the one measured figure on the board — his stored bonus points system total over the minutes he played for it, highlighted above 25 per 90, which is roughly where the three-per-match award starts arriving. This site projects bonus nowhere, so it is a reading of his season rather than a claim about the round.

Goalkeepers and forwards are not here. A goalkeeper cannot earn the contribution award at all and a forward is paid nothing for a clean sheet, so neither has a defensive half this board could rank him on.

Every ranking here is in expected points or in the weighted score for the rounds ahead, which are the units this model is measured in. The value column is those figures restated over a price — it is a way of scanning the board, and nothing on this site backtests it.

The board is every player the game would let you field, the flagged included — whether a doubtful player is worth picking is a judgement the projection makes with his published chance of playing, not one made by hiding him.

What is measured here, and what is not

  • Measured The projected points

    Replayed against gameweek 2 after it was played: an average miss of 1.617 points a player, against 1.842 for “predict what he has averaged so far”, over 456 players. Recorded Sunday, 6 September 2026 and refreshed by hand, so the date is part of the claim.