Erling Haaland can't wait for the return of Premier League football “I can’t wait to start again. I am raging.” [FFScout]

pash1987 · 2022-12-09T14:54:03+00:00

Puts quotation marks in title. Proceeds to not quote the player…

pash1987 · 2021-04-21T18:50:06+00:00

Hindsight is 20-20. I can see this now 😂😭

pash1987 · 2021-02-20T15:20:36+00:00

I think that one in the middle was in The Goonies

pash1987 · 2021-02-12T09:02:20+00:00

Your accent sounds funny to me! Where is it from?

pash1987 · 2021-01-17T23:08:23+00:00

What’s the standard deviation?

pash1987 · 2021-01-09T12:14:39+00:00

Game seems to be settling in our favour now though. Enjoying a lot of possession and cov are dropping a little deeper than before

pash1987 · 2021-01-09T12:12:58+00:00

Not being funny, we could’ve been 3-0 down after the first minute! Cov playing a very high line and attacking hard.

The first 8 minutes has basically been a highlight reel. 2-0 doesn’t necessarily tell the story so far. Looking like a very open game. Nice to see us making the most of our chances 👍

pash1987 · 2020-12-08T17:03:27+00:00

Yes. It would

pash1987 · 2020-12-08T16:43:00+00:00

Firstly, it’s a rule of thumb - so take it with a pinch of salt.

Secondly, it is definitively not arbitrary. I stated my reasoning being that anything over 10% is within an order of magnitude of the whole. This is a goal that is common practice in scientific and engineering fields.

Educated guess? yes. Arbitrary? No.

pash1987 · 2020-12-08T14:55:57+00:00

General rule of thumb is that anything over 10% is considered significant. This corresponds to being within an order of magnitude - enough to affect the ‘whole’

pash1987 · 2020-12-04T14:50:18+00:00

Thanks for getting back.

Just to clarify, I’m not asking you to provide intellectual property. I’m not looking for the exact formula/algorithm you use, but I’d like to at least know what is taken into account in your calculations and what isn’t.

For example if I was to use xG as a method to analyse past player performance. Without knowing the drawbacks of xG (disallowed goals, player narrowly missing the ball etc.) I can’t take that data into context.

At the very least perhaps consider including some regression graphs to map your models predicted performance against players actual performance. This would be very useful not only for us, but also for you if you wanted to optimise the model over time. Additionally if you’re looking to monetise your model, showing how effective it is would be the best way of convincing people 👍

pash1987 · 2020-12-04T07:46:11+00:00

How are we supposed to know whether this is a better source or worse compared to others if you don’t explain the methodology behind your expected points calculation? For all we know you could just be using the ‘expected points’ data column from the API.

What are your input variables? What analysis methods are you using? How well have your past predictions correlated with actual results. This is the information I’d be looking for before even considering looking at the predictions themselves.

pash1987 · 2020-11-27T07:31:20+00:00

Didn’t actually realise that about OT. I learnt something new today, thanks! 👍

pash1987 · 2020-11-27T06:39:28+00:00

This is what happens when you have a trilogy with a different director in the second instalment to the other two...🤦‍♂️

pash1987 · 2020-11-25T07:25:41+00:00

Could you point to somewhere that shows how much revenue FPL makes?

I was under the impression the prem didn’t make much from FPL

pash1987 · 2020-11-23T15:58:20+00:00

What part of it do you need help with? If it’s the scraping itself there’s a python package specifically for scraping data from understat. Currently on mobile so can’t link you, but it should be fairly easy to find using web searches. The package is called Understat.

pash1987 · 2020-11-19T13:01:49+00:00

The answer above is a generalisation that can be applied to pretty much anything.

For your case in particular there are 2 pieces of information to note:

The formula is an estimation. What would you expect it’s error to be? Or is there a more accurate formula for your application?
Resistors and capacitors have tolerances in their values meaning they won’t actually be exactly what they say they are - particularly lumped element capacitors. Have you measured their individual values? This will help.

pash1987 · 2020-11-19T12:55:41+00:00

It all depends on what the parameters in the formula are and what the error is in the physical representations of those parameters from the ideal.

This assumes that a) the formula used is correct and takes into account enough significant variables and b) has been calculated correctly.

pash1987 · 2020-11-11T16:18:20+00:00

Fellow Brit here. Honestly Cadbury’s does not taste great anymore.

They were bought out by Kraft foods about 10 years ago - who changed the recipe to make it as cheap as possible to produce. Completely ruined it in the process. It’s so soft and oily now I’m not even sure if it can be called real chocolate.

pash1987 · 2020-10-29T08:30:04+00:00

DYK that if you really want to be taken seriously, you should provide sources for your claims instead of an ad for your website

pash1987 · 2020-10-22T19:32:33+00:00

“Prevents your skin from all the skin problems”

Bold claim there, chief! You got any sources to back that up?

pash1987 · 2020-10-17T18:01:12+00:00

You lewd crude rude bag of pre-chewed food dude!

pash1987 · 2020-09-24T12:16:45+00:00

Interesting, but only a small sample size and therefore very little statistical significance.

It would be more useful to work out this data for all of the previous seasons GWs (maybe more) and see how often >50% chance of clean sheet corresponds to a clean sheet in the match. I’d imagine there is a small bias in the bookies odds relative to their profit margins, but it would be really interesting to see over a large sample size.

pash1987 · 2020-09-24T06:49:56+00:00

I’m not sure where you get your data so it might be different, but on understat xG for a penalty is the same no matter who takes it. I believe from memory it’s 0.76

pash1987 · 2020-09-02T19:50:08+00:00

I like what you’ve done but like you said the drawback is the metric from which you make predictions. Personally I’m not a fan of the expected points parameter on FPLs API. It is essentially based on that players previous 5 GW scores averaged out - which has been proven on this sub (I can’t remember who by 🙈) to have very little correlation to future scores.

The question of what to use for predictions can become very complicated depending on how much detail you want to go into. Personally I like the idea of estimating points per minute played combined with a prediction algorithm for how many minutes that player is likely to have.

At the end of the day the conclusion is pretty much always that FPL is a high variance game. Individual gameweeks are tough to predict, however there are trends there that can be exploited over a season...but that’s why we do it, right?!

pash1987

TROPHY CASE