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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

#91

Post by usgroup »

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,…

Model totally sucked against betting odds and if you used the model probabilities to price bets you would have lost a lot of money vs even an average bookmaker.

Score it yourself against implied probabilities from Betfair for example and marvel at the suckage.

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

#92

Post by kgwgk »

fny wrote: post #67
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?

So this is something that people don't seem to grok quite well, and it really depends on the type of statistical analysis used. Say you make the assumption that the quantity being estimated is truly fixed: that there's some true value for the force of gravity or some true value for the number of people that vote for X or Y. The second assumption that comes along is that the stochasticity observed comes from your pers…

If you expect to get it right (in this particular prediction, Clinton to win) with 95% probability, what does it mean to say that this 95% is with low confidence or with high confidence?

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

#93

Post by Sean1708 »

ernesth wrote: post #82
Sean1708 wrote: post #73

In case anyone was interested here is a table of how likely the model thought each team was to make it through any particular stage[0] along with the stage that that team went out in and the probability that the model gave for that particular outcome (i.e. [probability of making it through the final stage they made it through] - [probability of making it through the stage they went out in]). Groups Round_16 Quarters…

Japan went out in Round_16 Croatia went out in Finals And I do not understand what the last column means (except for France and teams out in group phase)

Urgh, I hate that you can't edit HN comments.

First two were just me making a mistake because I write that in manually.

That last column makes no sense. It was supposed to be the probability that the model gave to the outcome that occurred, but I got the maths wrong.

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

#94

Post by TuringNYC »

soVeryTired wrote: post #84
TuringNYC wrote: post #64

Earlier quoted context omitted.

FYI - I worked at Goldman Sachs and then a hedge fund for a decade. On the Capital Markets / Trading side, you are literally a bookie. In fact the nomenclature is "you have a book." You are setting trading spreads based on where you think things will go. Depending on the market, your work may be more or less statistical and you're trying to gain a statistical advantage.

Surely your book is meant to be hedged though?

Well, you've got exposures on both sides (and you keep the tiny bit in difference between what you buy at and what you sell at, in aggregate.) I'm not sure how gambling bookies work, but I'm assuming it is very simple principles...arent gambling bookies essentially market makers just like Wall Street market makers?

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

#96

Post by sctb »

Sean1708 wrote: post #93
ernesth wrote: post #82

Earlier quoted context omitted.

Japan went out in Round_16 Croatia went out in Finals And I do not understand what the last column means (except for France and teams out in group phase)

Urgh, I hate that you can't edit HN comments. First two were just me making a mistake because I write that in manually. That last column makes no sense. It was supposed to be the probability that the model gave to the outcome that occurred, but I got the maths wrong.

There's an edit window of a couple hours, which has probably just past. We've opened it up again so you can go ahead and edit.

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

#97

Post by bambax »

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,…

> 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, and that that is the highest chance does not say much about the model.

But do you need a sophisticated model and lots of so-called "AI" to arrive at the conclusion that there's a lot of uncertainty?? The point of the model is to reduce uncertainty, not find that it's there and do nothing about it.

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

#98

Post by rossdavidh »

In addition to the many other problems with this article, I would like to point out that if, somehow, Goldman Sachs had managed to create a model that could accurately predict the results, the game of soccer would have to be changed to make it more unpredictable somehow. It is intrinsic to the nature of sport that, in order to be entertaining, there has to be a realistic chance for more than one team to win. Not many people (even from the winning country) would bother watching if it were accurately predictable.

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

#99

Post by toolslive »

PaulRobinson wrote: post #76
basch wrote: post #62

Earlier quoted context omitted.

Their model also had France at 2nd most likely, Belgium at 5th, and England at 7th. 3 of their top 7 made the Semi-Finals, and they called the eventual winner as Second Most Likely, and more likely than Germany. They actually predicted the Brazil/Belgium game in the Quarter Finals, but got the winner wrong. Brazil had 27 shots and 9 on target with 59% posession. Belgium only had three shots on target, and made two of…

> Brazil had 27 shots and 9 on target with 59% posession. Belgium only had three shots on target, and made two of them to win. A modern model would accommodate for the fact that those numbers alone mean nothing, because they don't. Those are the numbers broadcasters reluctantly put on a screen for entertainment value, but they don't have real analytical power because they have no comparative metric. How up or down we…

Some teams/coaches like possession, others do not. If a team plays a dominance based game, eventually, their defenders will be (almost) on the opponents half. When this happens, it becomes edgy, and a loss of possession can be punished by a counter. That counter needs to be executed as fast as possible. Teams that are ahead often retreat and let the opponent have the ball to be able to break out like that. It just means possession doesn't really say anything. Belgium went ahead against Brazil with a bit of luck, and then let Brazil have the ball. Belgium's second goal was a classic counter punch. After that Brazil was allowed to have the ball while Belgium tried to control the game. Regarding odds, Belgium was number 3 in the world when the game was played, Brazil was number 2. Obviously, it would not be a `walk over` for anyone.

If you look at both Belgium/England games, you see number 2 against number 12. The ranking was respected there.

https://www.fifa.com/fifa-world-ranking/ranking-table/men/in...

Used to be a silly ranking system, but it's elo based these days, so it's not too shabby.

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

#100

Post by neuromantik8086 »

fwdpropaganda wrote: post #50
denzil_correa wrote: post #16

The "Ludic Fallacy" strikes again [0]. > The ludic fallacy, identified by Nassim Nicholas Taleb in his 2007 book The Black Swan, is "the misuse of games to model real-life situations." ... > The alleged fallacy is a central argument in the book and a rebuttal of the predictive mathematical models used to predict the future – as well as an attack on the idea of applying naïve and simplified statistical models in compl…

Damn, do I disliked Nassim Taleb. I don't think I've ever heard him say anything deep. That wikipedia article is an excellent. In [0] you have the following: > The ludic fallacy, identified by Nassim Nicholas Taleb in his 2007 book The Black Swan, is "the misuse of games to model real-life situations." And he gives an example of this: > One example given in the book is the following thought experiment. Two people are…

Nassim Taleb is basically a stopped clock. He's pretty big on pointing on how we're all prone to find illusory correlations (not his discovery) and he's a great promoter for Kahneman and Tversky, but there are other areas where he clearly is out of his depth. It's beyond obvious, for instance, that he's never gotten past Popper in his studies of philosophy of science. Unfortunately, his disciples are (ironically) quite terrible at thinking for themselves and buy into his demagoguery.

Basically a book by Nassim Taleb is an incoherent summary of the books that Nassim Taleb has read within the past year, with a few morsels of recycled insight here and there.

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