The start of a new season was complicated enough with both Manchester clubs blanking, and the uncertainty around players in our squads going in and out of quarantine against the backdrop of a global pandemic, but the fixture schedule has thrown us an additional curve ball if my spreadsheet predictions are anything to go by.
Some gameweeks see fewer goals, but the impact on our scores is usually offset (partially at least) by more clean sheet points being available. However, what my spreadsheet predicts for GW1, is the perfect storm of a shortage of goals and a scarcity of clean sheets.
One-one score draws are deemed the most probable scoreline in all but 1 of the matches, with only CHE and WHU reckoned to be more likely to score more than once (see below). Surely that’s a typo? I must mean all but 2, right? Wrong. The Hammers fall into a strange paradoxical position I’ve commented on previously. Namely, that whilst it’s true that WHU are more likely to score at least 2 goals than 1, they are less likely to score twice than once. Fried your brain yet? Then can I suggest some lighter reading on quantum entanglement, perhaps?
In a similar vein, 5 teams are forecast to have a higher than 40% chance of a clean sheet in GW2, whereas only 4 teams are rated to have a better than a one in three chance (33%) in GW1. Of those 4, only LIV cross the 36.7% threshold, which is significant because that is the point at which conceding zero goals becomes mathematically more likely than conceding one goal. Remember though, the likelihood of conceding two, three, four goals, etc., also needs to be factored in, so a clean sheet only becomes the likeliest outcome of all when the assigned probability is higher than 50%.
There are always caveats attached to my spreadsheets, and rightly so, for algorithms always have shortcomings, but there are additional ones to consider at the start of this season. Obviously, no algorithm can second guess the impact that COVID19 will have on team lineups and results. Likewise the impact of empty stadiums on players and teams.
The other ‘known unknown’ at the start of any new season is the transformative effect of new signings on teams, and one need only reflect back on the arrival of Fernandes in Manchester in January to know that this can be huge.
More pertinent to my spreadsheet, however, is the fact that these predictions are based on each teams xG performances in their last 8 home or away games (whichever is relevant), 4 or 5 of which will have come post-lockdown. And, as I showed in my recent review of last season, some teams prospered during this period, while others faltered dramatically.
LIV belong in the latter category, and as they face a promoted team whose defensive credentials in the top flight are yet to be tested (and so can only be best guessed at), it is possible that the probability of a clean sheet for the defending champions is being underestimated by my sheet.
The attacking and defending strength ratios attributed to the promoted teams, based solely on matches against the other six sides in the Championship’s top seven last season, have been scaled back by 20% to reflect the tougher competition they will face in the Premier League.
Unavoidably, this is somewhat arbitrary, but not random (never random!). Rather it is based on some research I’ve read, but I accept that it’s an inexact science. The point being that if you believe the transition from EFL to PL is more than 20% harder, then the probability of LIV keeping a clean sheet increases accordingly. For what it’s worth, the probability of LIV keeping a clean sheet only increased by 3% to 42% when I substituted the figures for the season as a whole, rather than taking their last 8 games only.
That all said, it’s quite conceivable that LEE will be like rabbits caught in the headlights of an oncoming juggernaut, and an early goal will open the floodgates, and demoralise them. Personally though, I’m not banking on it.
Bring on the new season, bring on the green arrows, but most of all, bring on the coronavirus vaccine!
Coley aka FPL Poker Player @barCOLEYna