Donald Trump
Full Member
That's some good stuff there Phil.
I wouldn't mind having the skills to pull this together so easily.I played about in python to scrape game-by-game stats from understat and build some basic formulae to work out how much each team was overperforming or underperforming xG on a 3 and 5 game basis (e.g. over the past 5 games Leeds have, on average, a goal difference of 1 goal higher per game than the xG and xGA numbers would suggest).
For the nerdier amongst us, I used Chat GPT to help build the formulae which cycle through the fixtures & compute the rolling 3 and 5 game averages.
The tables are sorted based on their xG over/under performance in the last 3 games
- The higher a team is on these rankings: the worse their goal difference is relative to xG/xGA
- The lower a team is on these rankings: the better their goal difference is relative to xG/xGA
Obviously there's no info here that the betting market hasn't already priced in, but it might put some teams on your radar to consider backing or opposing if you think they might return to the norm in terms of being efficient / inefficient at each end .
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Fulham are the perfect example here. You'd expect them to underperform for a while. Not saying they definitely will or anything but you wouldn't want to be putting too much faith in them either.There's a huge amount of useful resources out there which can be cobbled together to do some handy stuff - and once it's coded & proven it's pretty much one-click to get fresh snapshot views.
That said, there'd be a bit of a learning curve alright for anyone who hasn't had any programming experience. Mine was for a limited time and quite a few years ago, but the core concepts stick & are handy in dealing with error-fixing & adapting existing chunks of code.
A good point. I've added that in below and made some tweaks to make it more readable.
It's interesting to contrast the trends of Leicester, Leeds, Fulham & Forest here - who each have quite different profiles.
