Earlier quoted context omitted.
Where did you get player/club data from?
We scraped it from soccerway.com.
Are there any plans to make the clean dataset public? It would be nice to be able to play with it.
Show HN: Euro 2016 predictions using Bayesian inference
31–40 of 59 posts
Re: Show HN: Euro 2016 predictions using Bayesian inference
#32The predictions look good to me except Wales vs Slovakia because of Gareth Bale.
You're right. We took Wales' last lineup, but it will very probably be a different lineup against Slovakia. We'll update the prediction shortly before the game, when we know who's going to play.
Re: Show HN: Euro 2016 predictions using Bayesian inference
#33I can say right off the bat this is completely wrong. The sum of probabilities of each team winning cannot be 100%. Why? Because draws exist. Worse yet, the concept of "playing for a draw" based on your current position in the group also exists. Also, the concept of "nothing to play for", when the team is already guaranteed the first place in the group and might not play at full strength in the final game.
Yes, the draws exist, but every other argument you've posted cannot be applied to the first round of group games. Chances are huge that all of the times are going to want to start strong.
As the researchers said multiple times, they're going to be updating their algorithms all of the time and take into account the things they've missed in the current version.
Re: Show HN: Euro 2016 predictions using Bayesian inference
#34Cool 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…
It is my personal opinion that soccer has a very high luck component. Often four or five plays decide the game. Frequently enough it is even decided by a referee call. It makes the game attractive because even an inferior team has a decent chance against a superior team. It may be just a lucky shot and then you close your defense.
Re: Show HN: Euro 2016 predictions using Bayesian inference
#35I can say right off the bat this is completely wrong. The sum of probabilities of each team winning cannot be 100%. Why? Because draws exist. Worse yet, the concept of "playing for a draw" based on your current position in the group also exists. Also, the concept of "nothing to play for", when the team is already guaranteed the first place in the group and might not play at full strength in the final game.
Yes, for now we only predict win / lose. It is fairly reasonable to assume that draws are more likely to arise if the winning probabilities are close to 50/50 (and less likely if there is a big difference) - but you are also right that there are some contextual factors that influence this.
You know the saying, "all models are wrong, but some are useful" - our model is clearly too simple to encode many of these complex patterns, but we believe that's alright!
Re: Show HN: Euro 2016 predictions using Bayesian inference
#36I think the fundamental assumption that a team's performance is the sum of the individual players' past record is wrong.
If you studied how a pundit would judge outcomes for these games, I'm sure they'd be talking about current form, whether the players play well together, tactics, playing styles etc. Take England for example, they've given Rooney a far higher score than either Vardy or Kane, even though any sane pundit is clammering for Rooney to not start, saying the other strikers are on far better form and that Rooney's presence detracts from the overall performance of the team.
As a technical project it's pretty cool, I just doubt its accuracy. I guess we'll soon find out!
Re: Show HN: Euro 2016 predictions using Bayesian inference
#37I think the fundamental assumption that a team's performance is the sum of the individual players' past record is wrong. If you studied how a pundit would judge outcomes for these games, I'm sure they'd be talking about current form, whether the players play well together, tactics, playing styles etc. Take England for example, they've given Rooney a far higher score than either Vardy or Kane, even though any sane pun…
Man Utd fan here. Agree completely with assessment of Rooney.
Re: Show HN: Euro 2016 predictions using Bayesian inference
#38Earlier 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...
Excellent point - this one is definitely on our todo list. There are several simple extensions of the Elo model that take draws into consideration (i.e., give a non-zero probability to draws), for example the Rao-Kupper model. There are only minimal changes needed w.r.t. the original model, but still we didn't manage to make the changes in time for this version of the site. In short: at its core, the "Elo assumption"…
The thing is that football is a time based sport, so draw is an outcome with pretty good chances.
Usually weak teams will try to delay as much as they can to get the draw. Given enough time, the strong team would have much bigger chances to win. Also, depending on the context ( points needed for each time ) a team might have bigger motive to go for a draw than a win.
Predicting outcome possibility in football is a very complicated story, I doubt it can be solved in a simple way like elo ranking the players or teams.
That said, the knock-out phase might be more suitable for that model.
Kudos for the effort anyway, and nice UI.
Re: Show HN: Euro 2016 predictions using Bayesian inference
#39Great base for future development of the idea. Some things to take into account though: - Friendly games are sometimes about fitness rather than winning at all costs - Weather greatly effects results. For example, in heavy rain and high wind, the likelihood of the game yielding more than 2.5 goals reduces massively. - How does the algorithm take into account substitutions? - If a team in the group has already won 2 g…
Thanks a lot for the comments!
- about friendly games: agreed, in the future we'd like to downweight them (as well as downweight older games over newer ones)
- about substitutions: at training time, we look at the number of minutes each player has spent on the field. At test time, we assume there will be no substitution. Could certainly be improved :-)
- about teams that are already qualified: true, our model does not encode all these contextual factors, and arguably they are very important for certain games. If the lineup changes (e.g. star players resting) it does impact the prediction.
Re: Show HN: Euro 2016 predictions using Bayesian inference
#40This is similar to the stuff GoalImpact does:
https://twitter.com/Goalimpact/status/740657055841816577
It's true most predictive models work at the team level, but it's interesting to point out that one of the more successful models over the last season was Chad Murphy (@soccermetric)'s MOTSON, an SVM trained over a bunch of stats per player: