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Goldman Sachs model to predict World Cup game results didn’t come close

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Re: Goldman Sachs model to predict World Cup game results didn’t come close

#51

Post by kgwgk »

raverbashing wrote: post #33
kgwgk wrote: post #28

Earlier quoted context omitted.

> had a 95% chance [...] but the confidence was low So she had 95% chance of winning with 50% probability or what?

it is captured in the 95% but that was probably a bit overestimated (and there are always unknown biases and improbable events can happen) What's wrong is thinking 95% chance of winning means they will win

So it was not captured in the (overestimated) 95% :-) But I agree, the most likely thing, even if the probability was perfectly known, is not always what happens.

Re: Goldman Sachs model to predict World Cup game results didn’t come close

#52

Post by anoncoward111 »

barrkel wrote: post #7

I put money on Belgium (12.0 decimal odds) and Croatia (15.0) after the group stages, where some form was visible, combined with knowledge that they had some of the world's best players. The odds shortened as the tournament progressed, I was able to hedge as the shortened odds made lay betting profitable. (High variance in football outcomes means there's no guarantee of profit, I don't bet big sums.)

This answer is very useful and contains proper strategy advice :)

If someone were to bet during the round of 16, if someone were to bet $1 on the bottom 8 and $2 on the top 8, the strategy would most likely yield a small profit or a small loss, rather than a total loss.

Re: Goldman Sachs model to predict World Cup game results didn’t come close

#53

Post by ghaff »

raverbashing wrote: post #21

People conflate statistics with actual results more often than not and I think those reporting on such stories and maybe even the original authors might fall for this. It was not wrong to say Hillary had a 95% chance of winning the presidential election, but the confidence was low and that value still allowed for the opposite result to happen . Also football has a lot of variance concerning team capability and end re…

Basketball has a lot of points scored so one or two freak plays or lucky bounces aren't likely to affect an outcome. And there are a lot of games so even a star player having an off night or two isn't likely to affect the outcome of a season.

Re: Goldman Sachs model to predict World Cup game results didn’t come close

#54

Post by crispyambulance »

I am somewhat shocked that GS would jump into the prediction business of the World Cup, even as joke. The risk of people getting the wrong idea about the prediction and GS itself is too great, even with a perfectly defensible model.

This is an enterprise for bookies, not Goldman Sachs.

Re: Goldman Sachs model to predict World Cup game results didn’t come close

#55

Post by rco8786 »

jbob2000 wrote: post #49
yk wrote: post #30

> And in any case, the model only generated probabilities of winning a game and advancing, and no team was given more than an 18.5 percent chance of winning the World Cup. > [...] > But Goldman Sach’s misfire is perhaps the most curious. The model said, that there is a lot of uncertainty, and as it happens, it was entirely correct. A World Cup chance of 18.5 percent means, that 4 out of 5 times the team will not win,…

But Goldman Sachs are the kings of predicting uncertainty! This is their whole business! They make billions predicting certainty through the murky, uncertain waters of the global economy. Would you argue that the global economy is more uncertain that soccer? I'd say so. How is it that they can find success in the market but not in soccer? I think this is a smoke signal. Soccer is corrupt; you can't predict the winner…

> you can't predict the winner unless you know what's being passed around under the table

Pretty sure you just inadvertently identified why GS is so “great” at predicting economic movements.

Re: Goldman Sachs model to predict World Cup game results didn’t come close

#56

Post by trump_supporter »

jbob2000 wrote: post #49
yk wrote: post #30

> And in any case, the model only generated probabilities of winning a game and advancing, and no team was given more than an 18.5 percent chance of winning the World Cup. > [...] > But Goldman Sach’s misfire is perhaps the most curious. The model said, that there is a lot of uncertainty, and as it happens, it was entirely correct. A World Cup chance of 18.5 percent means, that 4 out of 5 times the team will not win,…

But Goldman Sachs are the kings of predicting uncertainty! This is their whole business! They make billions predicting certainty through the murky, uncertain waters of the global economy. Would you argue that the global economy is more uncertain that soccer? I'd say so. How is it that they can find success in the market but not in soccer? I think this is a smoke signal. Soccer is corrupt; you can't predict the winner…

You’re really, really dumb

Re: Goldman Sachs model to predict World Cup game results didn’t come close

#57

Post by CoryG89 »

learnstats2 wrote: post #26
jasode wrote: post #18

Leonid Bershidsky and a lot of other journalists laughing at Goldman Sachs' incorrect predictions seem to miss the point. The World Cup predictions from Goldman Sachs (and also UBS) are a form of recreation and entertainment with machine learning. It's an expression of quant nerd humor. Analogous intellectual games would be engineers devising ridiculous Rube Goldberg contraptions[1] or programmers building "enterpris…

On the other hand, this is a predictive task that has defined outcomes and clear historical data - by my understanding, it is easier than commercial uses of machine learning [at least, easier to measure the effectiveness]. It's also Goldman Sachs and UBS choosing to attach their names to these and stake some reputation on these predictions. If they had hit the bullseye, they would be lauding these results.

It may be easier to measure the effectiveness (give a confidence level for the prediction), but just because there is clear historical data and defined outcomes, that does not mean you will be able to predict a particular outcome with any high level of certainty.

For example, imagine a tournament with a large number of participants, where the winner is picked simply by fairly choosing a single random participant.

If I then gave you all the perfect historical data going back decades, you could do statistical analysis and determine that the winner is completely random and therefore the probability of success, for any particular participant, is p~=(1/n), where n is the number of participants. Your confidence in correctly predicting any particular outcome will drop as n rises.

Not everything can be easily predicted just because you have enough data.

Re: Goldman Sachs model to predict World Cup game results didn’t come close

#58

Post by ufo »

systoll wrote: post #25
gtr wrote: post #9

Earlier quoted context omitted.

As there are relatively few goals, anything that can turn a goal into not a goal or vice versa can have a massive impact on the game. For example the penalty decision against Croatia in the final. Another thing that adds to the randomness is the chance that a key player may be sent off or injured.

To make that be specific -- in 44 of 64 games, and in every single penalty shoot-out, turning one goal into not a goal or vice-versa would've changed the outcome.

It is not so simple because goals in football are not independent from each other. A team that scores first has the opportunity to play more cautiously and go for more counter attacks.

Re: Goldman Sachs model to predict World Cup game results didn’t come close

#59

Post by trump_supporter »

yk wrote: post #30

> And in any case, the model only generated probabilities of winning a game and advancing, and no team was given more than an 18.5 percent chance of winning the World Cup. > [...] > But Goldman Sach’s misfire is perhaps the most curious. The model said, that there is a lot of uncertainty, and as it happens, it was entirely correct. A World Cup chance of 18.5 percent means, that 4 out of 5 times the team will not win,…

To generalize what you’re saying, internet journalists are not mathematicians or knowledgeable of the industries they’re covering and they want to cater to popular public sentiments for their own self gain.

To sum up what happened: some quants at goldman started a fun side project and goldman released it in good fun, and most people hate goldman

Re: Goldman Sachs model to predict World Cup game results didn’t come close

#60

Post by keiferski »

jasode wrote: post #18

Leonid Bershidsky and a lot of other journalists laughing at Goldman Sachs' incorrect predictions seem to miss the point. The World Cup predictions from Goldman Sachs (and also UBS) are a form of recreation and entertainment with machine learning. It's an expression of quant nerd humor. Analogous intellectual games would be engineers devising ridiculous Rube Goldberg contraptions[1] or programmers building "enterpris…

Yeah, I don't know...this feels a bit like if we ended up correct, we were clearly serious, but if we ended up incorrect, it was clearly a joke.
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