Wildcard · Gameweek 1

The Gameweek 1 wildcard draft

A 3-5-2 projecting 54.85 xPts, inside a squad costing £98.5m of the £100.0m budget.

eBy the evmax model · 4 August 2026

The draft is a 3-5-2 projecting 54.85 xPts from the starting eleven, wrapped in a legal fifteen — two goalkeepers, five defenders, five midfielders, three forwards — that spends £98.5m of the £100.0m budget and leaves £1.5m in the bank.

5.6Thiago5.2Watkins7.4B.FernandesC5.0Ndiaye5.0E.Le Fée4.9Gibbs-White4.9Saka4.5Senesi4.4Virgil4.3Tarkowski3.7Raya3-5-2
The model's optimal XI · number = projected points (xPts)

The four bench places are budget, not squad depth: every pound parked there is a pound the eleven that actually scores never gets to spend.

Which is why the bench is the cheapest legal one available — O'Shea, Dubravka, Davis and Destan, £16.5m between them. They exist to make the fifteen legal, not to be picked.

No club is at the three-player cap in this draft, which is rarer than it sounds — the cap is usually what stops a wildcard from simply buying the best side's entire defence.

The money is concentrated in B.Fernandes (£12.0m), Saka (£9.5m) and Thiago (£8.0m). The pick doing the most per pound is O'Shea, 0.92 xPts per million at £4.0m.

The data

#PlayerxPtsPriceCaptain EVCeilingOwned %
1B.Fernandes MUN7.4212.014.8416.8248.7%
2Thiago BRE5.628.011.2413.7316.0%
3Watkins AVL5.208.010.3913.6712.2%
4Ndiaye EVE5.046.010.0714.9020.0%
5E.Le Fée SUNDifferential4.956.09.9113.369.9%
6Gibbs-White NFO4.928.09.8413.7112.3%
7Saka ARS4.899.59.7815.6410.7%
8Senesi TOT4.456.08.8910.6811.3%
9Virgil LIV4.376.58.7410.8615.8%
10Tarkowski EVEDifferential4.316.08.6310.719.9%
11Raya ARS3.686.07.368.0730.2%
12O'Shea IPSDifferentialBench3.664.07.329.391.2%
13Dubravka TOTBench2.854.05.696.9824.8%
14Davis IPSDifferentialBench2.624.05.247.874.1%
15Destan HULDifferentialBench1.044.52.075.902.7%

Bottom line

Field a 3-5-2 projecting 54.85 xPts: £98.5m spent, £1.5m banked, and a bench that does nothing but keep the squad legal.

Get the next round the moment odds drop

50,000 simulations per matchday — captains, EV and match predictions in your inbox before lock.

Double opt-in. No spam, no tracking. Unsubscribe anytime.

How we get these numbers. Player scoring rates (goals, assists, defensive contributions) come from each player's own FPL data, not betting markets; match outcomes (de-vigged market odds, or a team-strength rating when a fixture isn't priced) drive 50k Monte-Carlo simulations, scored on the official Fantasy Premier League points table. Ceiling = the 85th-percentile outcome across our 50,000 simulations — the score when a player's best realistic game happens, not a fantasy cap. Every figure here is machine-readable at /api/fpl/gw1/wildcard.json.