Brighton & Hove Albion FPL projections and fixtures

Projected points, expected minutes and fixture-by-fixture expected goals for the Brighton & Hove Albion squad, from gameweek 6 onwards.

Rebuilt .

What the model makes of them

1.36goals scored against an average opponent
1.05goals conceded against an average opponent
6thattack, of 20
5thdefence, of 20

The model rates Brighton & Hove Albion's attack 6th of 20 and its defence 5th: against an average opponent it projects 1.36 goals scored and 1.05 conceded.

Across the next 8 fixtures the kindest is Hull City in gameweek 11 (away), where the model has them +0.61 goals better off; the hardest is Manchester City in gameweek 9 at -0.76.

Taken as a run rather than a fixture at a time, that schedule ranks 8th of 20 in the league for attacking upside over the same window.

Groß is the model's pick of the squad on 39.6 points over the run, 16.1 clear of Vuskovic.

The next fixtures

GameweekOpponentVenueTeam xGOpponent xGDifference
GW6SunderlandAway1.331.14+0.19
GW7Crystal PalaceHome1.601.14+0.46
GW8LiverpoolAway1.191.77-0.58
GW9Manchester CityAway1.091.84-0.76
GW10BrentfordHome1.621.31+0.31
GW11Hull CityAway1.560.96+0.61
GW12Newcastle UnitedHome1.591.33+0.26
GW13BournemouthAway1.391.56-0.17
The model's own expected goals for each side of the fixture, not FPL's difficulty colours.

Brighton & Hove Albion players, ranked

PlayerPosPricexMinsStartsGW6 xPtsCeilingHaulBlankRun total
GroßMID£5.8m8897%5.0510.415%9%39.6
VuskovicDEF£5.0m8088%3.387.42%53%23.5
De CuyperDEF£4.9m6786%3.397.66%61%23.0
KostoulasFWD£5.5m5564%3.118.26%47%22.2
F.KadıoğluDEF£4.4m8393%3.256.63%60%21.8
VerbruggenGKP£4.5m8796%3.026.30%51%21.5
GomezMID£5.0m7088%3.227.34%29%21.5
AyariMID£5.4m6271%2.675.23%39%18.8
DunkDEF£4.5m7170%2.787.03%64%18.3
BoscagliDEF£4.5m6469%2.546.42%68%17.0
StruijkDEF£4.9m5248%2.126.42%72%14.6
YalcouyéMID£4.5m4350%2.226.34%56%12.8
MitomaMID£5.9m2118%1.043.12%81%12.1
HinshelwoodMID£5.9m2119%0.983.11%82%11.8
AzeezMID£5.5m2222%1.043.11%80%11.3
AndrésMID£5.5m2927%1.303.11%75%10.4
DavidFWD£5.9m1515%0.862.41%87%8.7
GeorginioFWD£5.3m2122%1.102.41%80%7.8
SvobodaDEF£5.0m1010%0.451.00%95%5.7
O'RileyMID£5.4m88%0.431.00%93%5.2
WiefferDEF£4.9m--0%--------4.2
HadjamDEF£4.5m76%0.321.00%96%3.0
FergusonFWD£5.0m55%0.281.20%96%3.0
CoppolaDEF£4.5m77%0.321.00%96%3.0
CostinhaDEF£4.5m55%0.241.00%97%2.5
MintehMID£5.8m--0%--------2.3
SteeleGKP£4.0m34%0.110.00%98%1.9
IbrahimMID£4.5m55%0.251.00%96%1.7
OsmanMID£5.0m33%0.170.00%97%1.5
OriolaMID£4.5m43%0.190.00%97%1.5
YohannaMID£4.9m22%0.120.00%98%1.5
TzimasFWD£5.4m--0%--------1.3
Ordered by projected points across gameweeks 6–13. Blank is the chance of two points or fewer.

Plan transfers in the app

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About these figures

These figures are produced automatically from our own projection model and rebuilt as new data arrives — team news, results, prices and fixtures. Last rebuilt .

These are averages over thousands of simulated gameweeks, not predictions of what will happen: a single week can land a long way from the average, in either direction. The model reads published data only — it has no access to press conferences or leaked team sheets. Graded by walk-forward testing across a completed season, its average error is 1.05 points per player per gameweek over 25,750 graded player-gameweeks. That grading is blind to team news by design: each week is rebuilt from match results alone, so every player in it is scored as though he was fit and available.

The method, and where the model is measurably wrong, are set out in full on how it works.