21–30 of 32 posts
Remember, 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.
The 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…
The 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…
Earlier quoted context omitted.
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…
Any pointers or papers for someone who's just getting into this?
https://www.academia.edu/37585525/Flexible_Regression_Models...
I do generally find these top-down team-strength models quite primitive though. Teams are made up of players, plans, all sorts of under-studied interactions. I would also say that there are enough quant jobs in football now that you don't really need to gamble to make a living. :)
Earlier quoted context omitted.
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…
The thing is, the size of the wager and the payouts are just as important. I was never a sports gambler, but spent two years counting cards at blackjack in rural casinos as my job. This plays out with the Kelly Criterion: https://en.wikipedia.org/wiki/Kelly_criterion So you can have inefficient odds as the house, and still win. Did the models also provide optimal bet size given the probability of winning?
Earlier quoted context omitted.
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…
Any pointers or papers for someone who's just getting into this?
I would also think carefully about what you are doing and why. Most people fail because they try to bet on markets that are, for them, unbeatable (for example, football data is expensive). It is far easier to pick off obscure markets (I did not do this because I had a junior high school maths education and needed some guidance).
Earlier quoted context omitted.
The thing is, the size of the wager and the payouts are just as important. I was never a sports gambler, but spent two years counting cards at blackjack in rural casinos as my job. This plays out with the Kelly Criterion: https://en.wikipedia.org/wiki/Kelly_criterion So you can have inefficient odds as the house, and still win. Did the models also provide optimal bet size given the probability of winning?
Larger syndicates also have the problem that it's not always easy to wager as much money as they'd like on a small handful of leagues. So it becomes about how you can accumulate data and insight into a broader set of competitions.
I have heard that the largest syndicate has groups that only cover one football team. I have no idea whether this is true or how/where you get the liquidity to justify this.
Earlier quoted context omitted.
The thing is, the size of the wager and the payouts are just as important. I was never a sports gambler, but spent two years counting cards at blackjack in rural casinos as my job. This plays out with the Kelly Criterion: https://en.wikipedia.org/wiki/Kelly_criterion So you can have inefficient odds as the house, and still win. Did the models also provide optimal bet size given the probability of winning?
Larger syndicates also have the problem that it's not always easy to wager as much money as they'd like on a small handful of leagues. So it becomes about how you can accumulate data and insight into a broader set of competitions.
Perhaps 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!
Perhaps 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!