The planning toolset is back live for the 25/26 season on https://t.co/FDVjbqsrf4!
- Upgraded to model Massive Data v4
- Editable penalty settings are now enabled
- Extended horizon up to 14GWs
- All new rules incorporated
- New kits/faces
- Documentation site
Agree, I also think it would mostly benefit modelers who can put shape on something hard to intuit long term like this and be a negative thing for 95% of the userbase who want to beat their friends in a ML and are more focused on the football itself
On top of that the season is too long, ~75% of teams are dead later in the season, so they'd probably need to switch to tracking active teams
@ujaanghosh Certainly not many, possibly a 1 in 1000 event to get that unlucky.
The worst in the world that pop up year on year tend to be negative 300-400 points of variance
๐FPL Review Data Based Champions 25/26
The Season Review dataset has completed it's validation, which means we can confirm this years leaders across a number of data based categories
https://t.co/uBJqGVlF8q
@FPLGuynwa Currently only for the overall ranks, certainly possible to add in for the other metrics though
I do think the Season Review is due a bit of an update next year tbh
That brings the season to an official close for https://t.co/h10ZWb0pTz. I've pasted the end of season updates from Patreon here as a screenshot
If you notice anyone you know who made these leaderboards please let them know!
A huge thanks you to all users of the site and the FPL community, time to enjoy the world cup!
Like last last year we can also take a look at the team with the most captain points, which is Team ID 3051866, who despite getting 706 captain points this season finished ~1.5M
Overall it looks like they rarely took wild gambles, but got the timing right with largely solid captaincy picks
In terms of the most/least lucky, the range this year was from +458 to -346, mostly fairly uninteresting teams loitering around the millions however
@terryflewars@FPLFocal I'd say there's basically nothing in it. Mo might be 0.1-0.2EV ahead which is fairly meaningless. What might influence things is if you think he'll be subbed off earlier or let play until the final moments
Hey, the algos for WC/FH are slightly different (transfer solver is handling the monster non-linear evaluation problem)- often you'll get the same team for this kind of situation, but sometimes they can be different
Using the linear optimiser you will get the same output either way, though it is the linearised evaluation of the problem
I am the best FPL manager over the past few years.
Decision-making, not data models, is what determines your outcomes.
I wrote some reflections on what fantasy sports teaches us about that.
https://t.co/Mh3tG8TXLK
Hey, the way that I'd read that image is that you're making solid picks and have maybe been slightly unlucky relative to other managers. Based on that kind of data you'd probably have a median outcome of ~80k at a guess, but as FPL has so much variance you could end up anywhere from 1k to 500k+ in practice
In terms of decision making, I can see you built high team value but more info will exist below this header image. Usually the biggest thing people trip up on is taking many hits, however that may not be the case here. Beyond that the best way to boost these numbers is a numerical approach to the game as it really is a game of numbers and chance
A call for users to submit anything they'd like to see added/fixed/changed to the sites suggestion box or directly via email
Finalising what will make into the Summer workplan for next season so now is a good time to get any feedback across
@FPL_BONES Diff EV => Reliance on the different picks relative to the Elite 1000 sample
Value => Team value, relative to the Elite 1000 sample
https://t.co/eeMSuyhCJR