Show HN: Euro 2016 predictions using Bayesian inference
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Re: Show HN: Euro 2016 predictions using Bayesian inference
#2For those who are interested in the details: we model the strength of teams using the well-know Elo model (used e.g., for official chess ratings).
We innovated on two aspects of the traditional Elo model, in which every team has an independent parameter:
1) We actually model the strength of players instead of teams. This makes it possible to learn from games that were played in championships between clubs, and transfer this knowledge to games between countries
2) There is a not-so-widely-known connection between Elo-type comparison models and Gaussian process classification. We leverage this, and get a full posterior distribution for each team's strength. (Information on the uncertainty of our estimates helps a lot in coming up with sensible predictions)
If anyone wants to know more (explanations on the web page are very superficial at the moment), please drop me a line!
Re: Show HN: Euro 2016 predictions using Bayesian inference
#3Cool work! Appreciate it's not your mission to say 'this will or won't happen' and is just a bit of fun.
But the great thing about football is that interesting as this is, I won't be placing any bets off the back of it. Too many variables in human nature, playing conditions, external factors, and maybe even luck. It's what keeps the game interesting and millions watching.
It would be interesting as a question to wonder what parts of human behaviour can be predicted accurately in this way though!
Re: Show HN: Euro 2016 predictions using Bayesian inference
#4For those who are interested in the details: we model the strength of teams using the well-know Elo model (used e.g., for official chess ratings). We innovated on two aspects of the traditional Elo model, in which every team has an independent parameter: 1) We actually model the strength of players instead of teams. This makes it possible to learn from games that were played in championships between clubs, and transf…
I'm interested in how you model the strength of players, is that for the whole squad or the expected starting eleven? The prediction that stood out for me was the Wales vs Slovakia which FIFA rankings and betting odds would both suggest will be closer, would love to hear more about the factors behind that particular prediction.
Re: Show HN: Euro 2016 predictions using Bayesian inference
#5Cool work! Appreciate it's not your mission to say 'this will or won't happen' and is just a bit of fun. But the great thing about football is that interesting as this is, I won't be placing any bets off the back of it. Too many variables in human nature, playing conditions, external factors, and maybe even luck . It's what keeps the game interesting and millions watching. It would be interesting as a question to won…
>> "I won't be placing any bets off the back of it. Too many variables in human nature, playing conditions, external factors, and maybe even luck"
That's what makes betting on it fun! If you can reliably predict who's going to win it's not gambling :)
Re: Show HN: Euro 2016 predictions using Bayesian inference
#6For those who are interested in the details: we model the strength of teams using the well-know Elo model (used e.g., for official chess ratings). We innovated on two aspects of the traditional Elo model, in which every team has an independent parameter: 1) We actually model the strength of players instead of teams. This makes it possible to learn from games that were played in championships between clubs, and transf…
But how does that make sense in a game where you can have a draw? By definition 100% cannot cover only home/away. Draw must be factored in. So doesn't that make all the Elo assumptions false?
Just wondering how you can take draw into consideration...
Re: Show HN: Euro 2016 predictions using Bayesian inference
#7For those who are interested in the details: we model the strength of teams using the well-know Elo model (used e.g., for official chess ratings). We innovated on two aspects of the traditional Elo model, in which every team has an independent parameter: 1) We actually model the strength of players instead of teams. This makes it possible to learn from games that were played in championships between clubs, and transf…
Is there a reason you opted to use Elo rather than other rating systems commonly used in baseball analysis like log5 or Pythagorean (e.g. https://summerofjeff.wordpress.com/2010/12/05/serving-agains...)?
I'd also be interested in knowing a bit more about point 2 as well.
Re: Show HN: Euro 2016 predictions using Bayesian inference
#8For those who are interested in the details: we model the strength of teams using the well-know Elo model (used e.g., for official chess ratings). We innovated on two aspects of the traditional Elo model, in which every team has an independent parameter: 1) We actually model the strength of players instead of teams. This makes it possible to learn from games that were played in championships between clubs, and transf…
But how does that make sense in a game where you can have a draw? By definition 100% cannot cover only home/away. Draw must be factored in. So doesn't that make all the Elo assumptions false? Just wondering how you can take draw into consideration...
In chess you can also have a draw.
Either by having the player agree to a draw, or by killing every piece that is not the kings.
Re: Show HN: Euro 2016 predictions using Bayesian inference
#9For those who are interested in the details: we model the strength of teams using the well-know Elo model (used e.g., for official chess ratings). We innovated on two aspects of the traditional Elo model, in which every team has an independent parameter: 1) We actually model the strength of players instead of teams. This makes it possible to learn from games that were played in championships between clubs, and transf…
I'm interested in how you model the strength of players, is that for the whole squad or the expected starting eleven? The prediction that stood out for me was the Wales vs Slovakia which FIFA rankings and betting odds would both suggest will be closer, would love to hear more about the factors behind that particular prediction.
The Wales starting lineup is missing Gareth Bale (arguably in the top 5 best players in the world). His 'kickscore' is listed as higher than any of the welsh players so I don't understand why the model has excluded him from the starting lineup. See also Portugal and Ronaldo (kickscore 100!).
Interesting but perhaps needs some tweaking to match the expected starting lineups.
Re: Show HN: Euro 2016 predictions using Bayesian inference
#10Earlier quoted context omitted.
But how does that make sense in a game where you can have a draw? By definition 100% cannot cover only home/away. Draw must be factored in. So doesn't that make all the Elo assumptions false? Just wondering how you can take draw into consideration...
In chess you can also have a draw. Either by having the player agree to a draw, or by killing every piece that is not the kings.
Right.
But then again, you cannot say it's 100% that player A or player B will win, right? There's a chance for draw that is not negligible.