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thathonkey

Comparing this to 538's (quite different) Analysis [1]:

* 538 - Brazil - 36.0%

* WOLF - Brazil - 32.2%

* 538 - Argentina - 17.0%

* WOLF - Netherlands - 23.5%

* 538 - Germany - 12.0%

* WOLF - Germany - 21.6%

This paints a pretty interesting picture about trying to use statistics and math to predict sporting tournaments like this. Seems like nobody has been very successful at this yet. Obviously it gets "easier" as the tournament progresses, though.

* [1] http://fivethirtyeight.com/interactives/world-cup/

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This is interesting but not surprising: the fact that scoring in (association) football is a relatively rare event means that it is less predictable at the individual match level than other team sports such as rugby, American football and basketball that feature more frequent scoring events; i.e. there is a greater likelihood of the underdog snatching a surprise win.

That is absolutely incorrect. Heavy underdogs in the group stages of this world cup had frequently had moneylines of +1300 and higher (ex Netherlands vs Austrailia). There is NEVER an NFL game in a typical season where the moneyline (ie without pointspread) on the underdog will pay out that high. So, the is a much SMALLER likelihood of the underdog snatching a surprise win.

Many pro sports leagues like the NFL are designed to have parity amongst the teams, to make it more exciting. There is no way to ensure parity in national teams. If there was an international American football competition, it would have even less parity than international basketball competitions (where the US is extremely heavily favored in nearly every game).

Perhaps the underlying process is just so noisy, better models are not really possible. It would be interesting to see confidence intervals on those predictions - I am relatively confident they would overlap. My intuition tells me that the confidence intervals would be huge and there is very little statistically significant differentiation between the best and worst teams in the tournament - upsets happen in soccer many times every tournament.

I think how successful a model is depends on your purpose too - if you have a model that predicts only 60% of games correctly, while technically you're not very "good", you're doing much better than those gambling on the sport (usually the favorite in sports betting wins at a rate of 52-54% I think) or probably conventional 'sports analysts' (no data to support the second point, that's an educated guess based on the gambling statistic).

Costa Rica and Algeria were given no chance of qualifying, while Spain, Portugal and England were right up there with Brazil.

http://blog.wolfram.com/2014/06/20/predicting-who-will-win-t...

Just goes to show, when it comes to sport, you can throw away most of these models until they start taking into account news and gossip from tabloids which probably has more bearing on team performance than raw numbers.

Their analysis is not quite different if they agree on 2 out of 3. Also, both are good, it's pretty much the prediction anyone into the World Cup would make at this point.

Someone would bet Argentina #2 if the have faith Messi will play what he's used to, or Netherlands if they consider the actual performance in this cup. This reflects 538's stronger bias for player skill score, while Wolfram seems to adjust more for the past results.

My simpler, Elo-based model gives (currently):

Brazil: 24.2% Germany: 23.0% Netherlands: 19.0% Argentina: 15.7%

France is also really good.. need to be on the top ones

They are quite different indeed. It would be interesting to compare, at the end of the tournament, the likelihoods of both models on all matches. This would give a pretty good idea on how good were the models.

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