xgEdge

Fantasy Premier League

Best value in the game

Every player the game would let you field, projected over the rounds ahead and priced against them. The board is ranked on the model's own currency; the value column is one click away.

Best value in the game

Gianluigi Donnarumma

GKP · MCI · 5.5m · owned by 7.6%

2.09

Value

every bar on one axis of 0 to 2.5

That is 11.5 projected points over the rounds ahead, weighted so the round in front of him counts for most.

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

Gianluigi Donnarumma is the best value on the board: 2.09 points per million, from 11.5 over 5 rounds at 5.5m.

Price

5.5m

What the game charges for him today, which is what the value column divides by.

Ahead

11.5

His weighted score over the next 5 rounds, and the currency this board is ranked in.

Own

7.6%

The share of managers already holding him.

The top five on this board

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

  1. Ranked 1 Erling Haaland
    FWD MCI vs
    16.7 Ahead
    Value
    1.07
    Price
    15.6m
    Own
    74%
    2.8
    1. LIV (A)
    2. IPS (H)
    3. AVL (A)
    4. BHA (H)
    5. NFO (A)
  2. Ranked 2 Marc Guéhi
    DEF MCI vs
    11.5 Ahead
    Value
    1.92
    Price
    6.0m
    Own
    18%
    2.8
    1. LIV (A)
    2. IPS (H)
    3. AVL (A)
    4. BHA (H)
    5. NFO (A)
  3. Ranked 3 Gianluigi Donnarumma
    GKP MCI vs
    11.5 Ahead
    Value
    2.09
    Price
    5.5m
    Own
    7.6%
    2.8
    1. LIV (A)
    2. IPS (H)
    3. AVL (A)
    4. BHA (H)
    5. NFO (A)
  4. Ranked 4 Elliot Anderson
    MID MCI vs
    11.4 Ahead
    Value
    1.81
    Price
    6.3m
    Own
    4.0%
    2.8
    1. LIV (A)
    2. IPS (H)
    3. AVL (A)
    4. BHA (H)
    5. NFO (A)
  5. Ranked 5 Joško Gvardiol
    DEF MCI vs
    11.1 Ahead
    Value
    1.94
    Price
    5.7m
    Own
    27%
    2.8
    1. LIV (A)
    2. IPS (H)
    3. AVL (A)
    4. BHA (H)
    5. NFO (A)
Position
All GKP DEF MID FWD
Minutes played
Any 90+ 270+ 450+ 900+
At least
Any Very safe Safe Rotation risk
Rounds ahead
3 rounds 5 rounds 8 rounds
Price
Enter your squad to mark what you already own and what you could afford →
Showing 25 of 25 players 25 of 487 match your filters Clear filters
1 Erling Haaland 16.7
FWD vs MCI · 15.6m 92%
Value
1.07
Pts
4.6
xGI
0.99
Own
74%
Mins
450
  1. LIV (A)
  2. IPS (H)
  3. AVL (A)
  4. BHA (H)
  5. NFO (A)
2 Marc Guéhi 11.5
DEF vs MCI · 6.0m 92%
Value
1.92
Pts
3.1
xGI
0.27
Own
18%
Mins
450
  1. LIV (A)
  2. IPS (H)
  3. AVL (A)
  4. BHA (H)
  5. NFO (A)
3 Gianluigi Donnarumma 11.5
GKP vs MCI · 5.5m 92%
Value
2.09
Pts
3.3
xGI
0.00
Own
7.6%
Mins
450
  1. LIV (A)
  2. IPS (H)
  3. AVL (A)
  4. BHA (H)
  5. NFO (A)
4 Elliot Anderson 11.4
MID vs MCI · 6.3m 92%
Value
1.81
Pts
3.2
xGI
0.17
Own
4.0%
Mins
413
  1. LIV (A)
  2. IPS (H)
  3. AVL (A)
  4. BHA (H)
  5. NFO (A)
5 Joško Gvardiol 11.1
DEF vs MCI · 5.7m 92%
Value
1.94
Pts
3.0
xGI
0.20
Own
27%
Mins
434
  1. LIV (A)
  2. IPS (H)
  3. AVL (A)
  4. BHA (H)
  5. NFO (A)
6 Rúben Dias 9.9
DEF vs MCI · 5.5m 92%
Value
1.80
Pts
2.7
xGI
0.21
Own
1.9%
Mins
450
  1. LIV (A)
  2. IPS (H)
  3. AVL (A)
  4. BHA (H)
  5. NFO (A)
7 Iliman Ndiaye 9.4
MID vs MCI · 5.8m 75%
Value
1.62
Pts
2.6
xGI
0.23
Own
6.7%
Mins
385
  1. LIV (A)
  2. IPS (H)
  3. AVL (A)
  4. BHA (H)
  5. NFO (A)
8 Rayan Cherki 8.9
MID vs MCI · 7.8m 75%
Value
1.15
Pts
2.5
xGI
0.67
Own
28%
Mins
302
  1. LIV (A)
  2. IPS (H)
  3. AVL (A)
  4. BHA (H)
  5. NFO (A)
9 Antoine Semenyo ! 8.6
MID vs MCI · 8.4m 69%
Value
1.02
Pts
2.4
xGI
0.30
Own
15%
Mins
450
  1. LIV (A)
  2. IPS (H)
  3. AVL (A)
  4. BHA (H)
  5. NFO (A)
10 Enzo Fernández 7.1
MID vs MCI · 6.9m 58%
Value
1.03
Pts
2.0
xGI
0.30
Own
3.6%
Mins
271
  1. LIV (A)
  2. IPS (H)
  3. AVL (A)
  4. BHA (H)
  5. NFO (A)
11 Abdukodir Khusanov 6.0
DEF vs MCI · 5.4m 58%
Value
1.11
Pts
1.6
xGI
0.02
Own
1.4%
Mins
268
  1. LIV (A)
  2. IPS (H)
  3. AVL (A)
  4. BHA (H)
  5. NFO (A)
12 Nico O'Reilly 5.0
DEF vs MCI · 6.3m 42%
Value
0.80
Pts
1.3
xGI
0.72
Own
11%
Mins
163
  1. LIV (A)
  2. IPS (H)
  3. AVL (A)
  4. BHA (H)
  5. NFO (A)
13 Matheus Nunes 4.4
DEF vs MCI · 5.9m 42%
Value
0.75
Pts
1.2
xGI
0.03
Own
1.0%
Mins
213
  1. LIV (A)
  2. IPS (H)
  3. AVL (A)
  4. BHA (H)
  5. NFO (A)
14 Rico Lewis 3.1
DEF vs MCI · 4.4m 25%
Value
0.71
Pts
0.8
xGI
0.30
Own
0.2%
Mins
56
  1. LIV (A)
  2. IPS (H)
  3. AVL (A)
  4. BHA (H)
  5. NFO (A)
15 Allan 2.8
MID vs MCI · 6.0m 13%
Value
0.46
Pts
0.8
xGI
0.00
Own
0.0%
Mins
0
  1. LIV (A)
  2. IPS (H)
  3. AVL (A)
  4. BHA (H)
  5. NFO (A)
16 Floyd Samba 2.8
MID vs MCI · 4.5m 13%
Value
0.61
Pts
0.8
xGI
0.00
Own
0.0%
Mins
0
  1. LIV (A)
  2. IPS (H)
  3. AVL (A)
  4. BHA (H)
  5. NFO (A)
17 Ryan McAidoo 2.6
MID vs MCI · 4.5m 10%
Value
0.57
Pts
0.7
xGI
0.82
Own
0.1%
Mins
11
  1. LIV (A)
  2. IPS (H)
  3. AVL (A)
  4. BHA (H)
  5. NFO (A)
18 Ayyoub Bouaddi 2.5
MID vs MCI · 5.5m 10%
Value
0.46
Pts
0.7
xGI
0.49
Own
0.2%
Mins
22
  1. LIV (A)
  2. IPS (H)
  3. AVL (A)
  4. BHA (H)
  5. NFO (A)
19 Jérémy Doku 2.5
MID vs MCI · 7.4m 8.3%
Value
0.33
Pts
0.7
xGI
3.30
Own
0.7%
Mins
15
  1. LIV (A)
  2. IPS (H)
  3. AVL (A)
  4. BHA (H)
  5. NFO (A)
20 Mateo Kovačić 2.4
MID vs MCI · 5.4m 8.3%
Value
0.44
Pts
0.7
xGI
0.04
Own
0.1%
Mins
42
  1. LIV (A)
  2. IPS (H)
  3. AVL (A)
  4. BHA (H)
  5. NFO (A)
21 Gerónimo Rulli 2.0
GKP vs MCI · 5.0m 8.3%
Value
0.39
Pts
0.6
xGI
0.00
Own
0.0%
Mins
0
  1. LIV (A)
  2. IPS (H)
  3. AVL (A)
  4. BHA (H)
  5. NFO (A)
22 Marcus Bettinelli 2.0
GKP vs MCI · 4.5m 8.3%
Value
0.44
Pts
0.6
xGI
0.00
Own
0.0%
Mins
0
  1. LIV (A)
  2. IPS (H)
  3. AVL (A)
  4. BHA (H)
  5. NFO (A)
23 Kaden Braithwaite 1.8
DEF vs MCI · 4.0m 10%
Value
0.45
Pts
0.5
xGI
0.00
Own
0.2%
Mins
1
  1. LIV (A)
  2. IPS (H)
  3. AVL (A)
  4. BHA (H)
  5. NFO (A)
24 Rayan Aït-Nouri 1.7
DEF vs MCI · 5.3m 8.3%
Value
0.31
Pts
0.4
xGI
0.00
Own
0.4%
Mins
0
  1. LIV (A)
  2. IPS (H)
  3. AVL (A)
  4. BHA (H)
  5. NFO (A)
25 Vitor Reis 1.7
DEF vs MCI · 4.5m 8.3%
Value
0.37
Pts
0.4
xGI
0.00
Own
0.0%
Mins
1
  1. LIV (A)
  2. IPS (H)
  3. AVL (A)
  4. BHA (H)
  5. NFO (A)
each row's Ahead, drawn to scale every bar on one axis of 0 to 20

What this board is, and what it is not

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.

Bonus points are projected nowhere on this site, so they are in none of these figures.

The window score is points times weight rather than points. The 5 weights sum to 3.36, so a window score is never a total anybody could add up from the per-round figures beside it.

The price is what he costs today. What the game would pay for a player who has risen is less, so a value figure is an estimate of a purchase rather than of a sale.

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.

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