Perhaps include "(soccer)" in the title for those of us in the USA?
I think it's reasonable for someone in the USA to expect that "Football" could refer to 1 of 3 popular games -- American football, soccer, or rugby.
Predicting Football Results with Statistical Modelling
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Re: Predicting Football Results with Statistical Modelling
#12Perhaps include "(soccer)" in the title for those of us in the USA?
The author is from London and the internet is global. Expecting an author to cater to every other culture with everything they do is a bit self-centered, IMO. It should be on the reader to understand that there are differences, not on the writer to make sure every single cultural difference is pointed out. It seems kind of weird to expect him to alter his headline to cater to a country he doesn't live in. If you were…
In fairness, it's not uncommon to specify "American football" for international audiences, so I don't think it's totally unreasonable. But on balance, adding a parenthetical word into a headline is just a little too much to ask. There's not much harm in bringing in someone who was expecting one but got the other anyway.
Re: Predicting Football Results with Statistical Modelling
#13Perhaps include "(soccer)" in the title for those of us in the USA?
That's like saying 'Perhaps include "(France)" in the title' when talking about Paris. Football is well known all over the world and perahps the most popular spectator sport.
Re: Predicting Football Results with Statistical Modelling
#14I just read this whole thing to find out it didn't work... :(
If it had worked. Do you think he would have blogged about it? :)
Re: Predicting Football Results with Statistical Modelling
#15Perhaps include "(soccer)" in the title for those of us in the USA?
Not the rest of the world's problem you called a game that mainly involves throwing 'foot' ball for some incomprehensible reason. Are you sure about the name basketball? Don't want to call it sackball or something like that? Or maybe shuttlebasket? I always chortle at your "world" series too!
> Don't want to call it sackball or something like that? Or maybe shuttlebasket?
What?
Re: Predicting Football Results with Statistical Modelling
#16Remember, no one wins at gambling by picking winners, you need to look for value and find where the bookmakers have miss-priced a team in a match.
Then you have to deal with all the corrupt behaviours the sports internet bookies will deploy to limit their exposure to you, which is the other reason why you won’t win.
Re: Predicting Football Results with Statistical Modelling
#17Remember, no one wins at gambling by picking winners, you need to look for value and find where the bookmakers have miss-priced a team in a match. Then you have to deal with all the corrupt behaviours the sports internet bookies will deploy to limit their exposure to you, which is the other reason why you won’t win.
time for a cryptographically secure and open betting platform that probably already exists but nobody is using!
Re: Predicting Football Results with Statistical Modelling
#18Perhaps include "(soccer)" in the title for those of us in the USA?
Why? Does it really matter what shape the ball is?
Re: Predicting Football Results with Statistical Modelling
#19The same author does seem to go on and build a slightly more realistic Dixon-Coles model: https://dashee87.github.io/football/python/predicting-footba... But even that is very dated - one of the authors, Stuart Coles has worked at a gambling syndicate for many years. They at the very least incorporate expected goals into the model, but no doubt have all sorts of esoteric models by now.
Yep, Dixon-Coles is way out now. Generally, Poisson-based models don't work that well. They model some aspects of the game correctly but not others. And when it is bad, it is terrible (their paper was genius though, and changed the industry). You also wouldn't do the one-hot/regression stuff on teams, as there is so much player-level data...some kind of online, off/def model is useful though.
You also have the issue of modelling a bivariate as two independent univariates. The adjustments made by the authors were intended to get around this problem but there has been a lot more work on this aspect of the problem since then, and a few new solutions.
And you are right, expected goals was cutting-edge back in ~2011-12 but even some clubs have caught on now. Most gambling syndicates, afaik, actually produce their own datasets (the largest ones employ a huge number of people, I know one that started up five years ago and already has ~10 PHds on staff + traders + data people, etc.).
I will say though, it is surprising how inefficient betting markets were until recently. In the early part of the 2010s, I imagine that large syndicates were making, conservatively, 300-400%/year in the largest markets that were, apparently, "unbeatable". I am aware of very simple models, similar to DC, that could beat retail bookies on Brier for EPL as recently as 2017. And, ofc, smaller markets are far softer (or other sports). At the cutting edge, yes...it probably is complex (I have no idea). But a surprising amount is actually just doing the simple things well.
Re: Predicting Football Results with Statistical Modelling
#20Perhaps include "(soccer)" in the title for those of us in the USA?
Not the rest of the world's problem you called a game that mainly involves throwing 'foot' ball for some incomprehensible reason. Are you sure about the name basketball? Don't want to call it sackball or something like that? Or maybe shuttlebasket? I always chortle at your "world" series too!
Surely it should be called netball, since baskets haven't been involved for more than a century.