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Ok, so as per a very good suggestion by
Joe Clash
I'm starting a thread to contain the pollution of stats/analytics discussion in other threads, while making sure it was visible enough that people were aware of it.
We have another, generic thread on the general football section: Evil Number Wizards Taking the Fun Out of the Game, and
paddy spur
and I have made ourselves look silly by trying to predict the league here: The model versus Paddy's gut
If you are interesting in stats, and would like to know where to go for actually intelligent use of them, good places are StatsBomb , Analytics FC , HOME , Objective Football Blog , 11tegen11 and Football in the Clouds . Statsbomb and Analytics FC both do podcasts as well, with Analytics FC doing one with Damien Comolli this week. Statsbomb is also good because it links directly to Paul Riley's expected goals and chance creation maps for the Premier League.
Michael Caley is probably the most prominent Spurs-related stats guy, and he's easiest to keep track of via twitter (@MC_of_A), since he publishes at various places, irregularly.
If you think all of this stuff is complete bullshit, that's totally alright, and no one would ever suggest that this stuff is mandatory to an enjoyment of the game (actually, the complete opposite at times), but if you think they're completely without merit, then give this video a watch (it changed Alan Shearer's mind):
Joe Clash
I'm starting a thread to contain the pollution of stats/analytics discussion in other threads, while making sure it was visible enough that people were aware of it. We have another, generic thread on the general football section: Evil Number Wizards Taking the Fun Out of the Game, and
paddy spur
and I have made ourselves look silly by trying to predict the league here: The model versus Paddy's gutIf you are interesting in stats, and would like to know where to go for actually intelligent use of them, good places are StatsBomb , Analytics FC , HOME , Objective Football Blog , 11tegen11 and Football in the Clouds . Statsbomb and Analytics FC both do podcasts as well, with Analytics FC doing one with Damien Comolli this week. Statsbomb is also good because it links directly to Paul Riley's expected goals and chance creation maps for the Premier League.
Michael Caley is probably the most prominent Spurs-related stats guy, and he's easiest to keep track of via twitter (@MC_of_A), since he publishes at various places, irregularly.
If you think all of this stuff is complete bullshit, that's totally alright, and no one would ever suggest that this stuff is mandatory to an enjoyment of the game (actually, the complete opposite at times), but if you think they're completely without merit, then give this video a watch (it changed Alan Shearer's mind):
I don't think you understand how they work.I've got fat thumbs... I meant to click on the "just faaakin' run araaand a bit" thread, but missed!
:avbfacepalm:
Nah, I'm not denying statistics' usefulness in life.. Many people make a very decent living out of them I'm sure.. it just always makes me laugh that ANY football predictions based on statistics can be rendered useless simply cos I didn't wear my lucky pants the right way round for a statistical home banker... and the next thing you know, Newcastle have a last minute winner and if that wasnt proof enough, Palace score for the first time in 8 HOURS!
Statistics said that SHOULDN'T HAPPEN!!!!
Does that mean statistics are bunkem when Spurs are involved???
There are two things. Statistics which are simple counting of actions taken (like shots, passes, goals), and calculations of probability based on past actions. The latter is what you seem to be talking about, but you don't seem to really understand how they work.
They don't say what will or won't happen. They don't "predict" things. They measure what is more, or less, likely to happen. Something really unlikely to happen (like Leicester winning the League) can still happen. It just isn't something which is a common or easily repeatable event.
That's how the bookies work. They use statistics to calculate what are the most probable outcomes, and then you bet against how likely or unlikely the bookies think those things are. Given that the bookies make good money, and punters usually lose a fair bit, it's safe to say that using statistics to measure what is likely or unlikely to happen in a football game is a real, and useful tool.
We do not need another stats thread. It's already been established that there are people on here who:
- Understand stats and appreciate that we can use them to improve our understanding of the game
- Think they understand stats but actually do not, leading them to draw wrong conclusions and argue that stats are useless
- Do not understand stats and do not want to understand them, as they prefer thinking about the game in the same way they always have done for the x years they've been following it
Agree, they do look good but worse they are improving.
However, there is another way to look at it, they have had a worse start than last year, after last year they hadn't conceded a single goal and had averaged 4 goals per game. This season they have conceded 4 goals and averaged 3 per game.
Looking at this in closer detail who have they played? Stoke, West Ham, Sunderland, Bournemouth these four teams occupy the four lowest positions in the league table!!! Stoke, Sunderland, West Ham have scored against them!!!! Stoke, Sunderland & Bournemouth have the joint worst goals for in the League!! The other team they have played is Manure, who look like they did last year.
They play Swansea in the League next then us. Just like last year they will turn up full of themselves, dicks swinging between their knees. They will look to blow us away in the first 20mins, however we will stand firm, take the onsluaght and play on the physiological scars we inflicted on them last year, we will pick at that scab and make it bleed.
Someone explained it pretty well in another thread, and you open a new one where all you're proving is that you still don't understand what stats does and means
Disagree. Two stats threads means a larger sample size. Therefore we're more likely to determine if the pro or anti-stats people are right.
Yes, but you're missing my point. I understand that's what the table says. What it doesn't say is how you got there.
West Ham this year is probably the best example, although we're a good one too. James York explained it best at week 6, I felt with this: (Elephants In The Room: West Ham, Leicester and Man Utd)
“In their last three games, all of which they won, West Ham have taken the lead inside ten minutes and in these games and the victory against Woolwich they have added to the score to make it 2-0.”
“Okay, that seems unlikely, but not entirely remarkable…”
“How about this then? In their four wins, West Ham have scored with their first shot on target.”
“Right… that’s interesting and sounds like a kind of thing that won’t repeat.”
“For sure, it won’t, it isn’t a skill. And you know what else? In each of those games, they also scored with their second shot on target.”
“Wow, Bilic for Prime Minister, right? I mean there may be a vacancy…”
What we find then is West Ham have spent more time this season at 2-0 than any other scoreline. They have spent 299 minutes leading, a full 76 minutes more than anyone else. With such regular and solid leads, it is arguable that they have been shelling for long periods of time, but this positive skew hasn’t stopped at their rate of scoring, the opposition are taking a ton of shots but only converting them at 7%, and the overall save percentage is a high 78%. It’s flowing right for West Ham at both ends. The problem being that these metrics have been shown not to sustain. West Ham’s underlying metrics have powered a freak run, will definitely decline and this is likely to be as good as it gets for them.
So, the results were the results, but how they got them suggested that it had more to do with having a horseshoe up their ass than actually being good at football. In contrast, at week 6, Spurs were mired in 9th, looking like mid-table mediocrity. Yet, according to ways of measuring shot quality, Tottenham were one of the 3 best teams in the land, in terms of how many chances we created, the quality of those chances, and the lack of quality and quantity of the chances we allowed. But our conversion rate was extremely low (around 6%). So, although we were playing better than almost anyone, the ball just wasn't going in the net for us.
This is where things get messy. The stats I tend to blather about talk about how probable something is. So, measuring shot quality talks about how likely the shots taken/created are to go in. There's no guarantee they really will.
But a team or a player's conversion rate (so, how many shots actually get scored) is something which has been shown to be very uneven. Generally, teams or players can score from 30% of their shots on target. But that's the average, over the long-term. In the short-term, it could be anywhere. From 6% (like for us at the start of the year) to 45% (Leicester up until this point). But in the long-term, things just about always average out to that 30% range. Some really good teams can do better than that, but not much.
But if you have a shit-hot conversion rate in your first 6 games and things are flying in, you'll look like Champions. Right up until you don't. The table doesn't lie, but it doesn't tell you anything about how teams play, either. And how they do it matters more, for the future, than what's actually happened in the past.
Christ, so much to unpack here.
Which ones? Goals and points are statistics too. Are they bullshit? Do you mean counting events, or do you mean trying to calculate probability?
For that matter, why only run a simulation 60,000 times? That's a really small sample for a supercomputer, since most laptop-using stats people seem to prefer sample sizes of 1 million simulated seasons, that I've seen. Does this supercomputer say "Casio" on the top and fit in your pocket?
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Which ones? Goals and points are statistics too. Are they bullshit? Do you mean counting events, or do you mean trying to calculate probability?
From what? Whose "simulator" is this? What model are they using, and what sources are they relying on for data?
Not sure what this even means. We have some real subject/object disagreement and misuse of the OED definition of the word chance. And numbers have substance? You mean some are imaginary like Hobbes said?
By whom? We aren't favourite in most models that I have seen, simply because either the model rates the players lower (for those who do ratings based on player value) or they rate other teams higher, based on things like strength of remaining schedule or the regressions they use (like payroll). That said, Paul Riley's model does rate us highest, and has done for over 2 months at this point: | Tableau Public
For that matter, why only run a simulation 60,000 times? That's a really small sample for a supercomputer, since most laptop-using stats people seem to prefer sample sizes of 1 million simulated seasons, that I've seen. Does this supercomputer say "Casio" on the top and fit in your pocket?
So, what even is this? Expected final points? Final finishing positions? By who? The only thing you've done is started an entirely new thread for a topic we already had 3 different threads for, while showing that you actually don't understand what either "statistics" or probability are.