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Show HN: Euro 2016 predictions using Bayesian inference

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Re: Show HN: Euro 2016 predictions using Bayesian inference

#11

Post by vicow »

benrjackson wrote: post #9
peeky wrote: post #4

Earlier quoted context omitted.

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.

Hi! I'm Victor, one of the researchers behind this project. We used the most recent lineups (up to yesterday) to do the predictions you see on the web page. We will update them with the latest friendlies (e.g., Portugal indeed) and before every game, as soon as we have the official lineups!

Re: Show HN: Euro 2016 predictions using Bayesian inference

#12

Post by galfarragem »

lum wrote: post #2

For 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…

One specific criticism regarding Portugal-Iceland: main squad will not be exactly as considered there. E.g. Cristiano Ronaldo is considered a substitute.. Does it make a difference to your predictions?

Re: Show HN: Euro 2016 predictions using Bayesian inference

#13

Post by tremon »

lum wrote: post #2

For 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…

Has there been any work (by you or others) towards factoring in the performance effect of the coaches on the teams?

Re: Show HN: Euro 2016 predictions using Bayesian inference

#14

Post by Grue3 »

I 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.

Re: Show HN: Euro 2016 predictions using Bayesian inference

#16

Post by solids »

"Informally, we assume that the performance of a team is defined by the performance of its players on the field. () Why do we do this? We do it because it enables us to take advantage of data from matches between clubs, and there is a lot (we mean really a lot!) more matches between clubs than between national teams."

IMHO this is wrong. Performance in club have little to do with performance in national team. Ask any Argentinian what they think about Messi.

Re: Show HN: Euro 2016 predictions using Bayesian inference

#17

Post by benrjackson »

vicow wrote: post #11
benrjackson wrote: post #9

Earlier quoted context omitted.

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.

Hi! I'm Victor, one of the researchers behind this project. We used the most recent lineups (up to yesterday) to do the predictions you see on the web page. We will update them with the latest friendlies (e.g., Portugal indeed) and before every game, as soon as we have the official lineups!

Thanks for the clarification and great project!

It will be interesting to see how things change when you get the official lineups. As I'm sure you are aware, teams often rest their 'star' players in friendlies immediately prior to a tournament in order to minimize the risk of injury.

Re: Show HN: Euro 2016 predictions using Bayesian inference

#18

Post by alexroan »

vicow wrote: post #11
benrjackson wrote: post #9

Earlier quoted context omitted.

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.

Hi! I'm Victor, one of the researchers behind this project. We used the most recent lineups (up to yesterday) to do the predictions you see on the web page. We will update them with the latest friendlies (e.g., Portugal indeed) and before every game, as soon as we have the official lineups!

It may be worth taking competitive matches into account over friendly matches, as the purpose of competitive matches is to win at all cost. Friendly matches, on the other hand, tend to be used primarily for match fitness (especially leading up to tournaments), and for trialling new tactics before the competitive games begin.

Re: Show HN: Euro 2016 predictions using Bayesian inference

#19

Post by ancymon »

lum wrote: post #2

For 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…

Where did you get player/club data from?

Re: Show HN: Euro 2016 predictions using Bayesian inference

#20

Post by alexroan »

Great 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 games, they may have already won. In that case they may rest many players or try new tactics

- Not all leagues (and levels of those leagues) are taken into account

Very much looking forward to seeing where this goes!

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