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
#2I watched quite a few matches and among the things I saw in the matches but not in any statistics are:
- motivation (Germany and Croatia were the two extremes here, no idea how to measure it)
- team cohesion (number of articles in a few journals questioning the team cohesion, maybe also articles about individual players)
- creativity in offense (maybe measurable via "target missed from close distance" + "ball passed front of the goal")
- number of errors in defense that didn't lead to a goal
- percentage of times ball possession was lost from own goal to enemy's area (England was really bad here against Croatia)
Re: Goldman Sachs model to predict World Cup game results didn’t come close
#3The World Cup is about the worst sporting event for data led predictions like this, far too much can rely on a few events that are basically a coin flip. It would be interesting to see how the predictions went for something like the Premiere League tables.
Re: Goldman Sachs model to predict World Cup game results didn’t come close
#4If anything, this is a clear illustration of poor use of probabilistic prediction. When used for investments you have many outcomes. If the model is any good, you will most of them right. In the World Cup you have very few. Even if you count all games played. Definitely not excusing Goldman Sachs here, they should have known better than to try to predict this. There was only a tiny chance this could be great advertisement for their model.
Re: Goldman Sachs model to predict World Cup game results didn’t come close
#5This site is a good counter-example for website optimization: While it uses many assets, so a CDN domain makes sense, it spreads them out thinly. It loads over 100 CSS files, most of which are below 1K. Similarly it loads approximately 30 JS scripts, most of which are just a few K each. This is mitigated to a large extent by using HTTP/2.0, which permits a few dozen or so parallel requests, but it still means that a repeated load of the page takes 2-3 seconds. (Without HTTP/2.0 this probably takes ages, since browsers open only a few connections to each origin at most). There is also almost no difference between reloading with and without the cache.
Re: Goldman Sachs model to predict World Cup game results didn’t come close
#6The World Cup is about the worst sporting event for data led predictions like this, far too much can rely on a few events that are basically a coin flip. It would be interesting to see how the predictions went for something like the Premiere League tables.
> far too much can rely on a few events that are basically a coin flip
Can you give us some examples?
Re: Goldman Sachs model to predict World Cup game results didn’t come close
#7I 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.)
Re: Goldman Sachs model to predict World Cup game results didn’t come close
#8The World Cup is about the worst sporting event for data led predictions like this, far too much can rely on a few events that are basically a coin flip. It would be interesting to see how the predictions went for something like the Premiere League tables.
I'd like to see some scientific evidence of this (i.e. using multiple experiments, null hypothesis, etc.)
Re: Goldman Sachs model to predict World Cup game results didn’t come close
#9The World Cup is about the worst sporting event for data led predictions like this, far too much can rely on a few events that are basically a coin flip. It would be interesting to see how the predictions went for something like the Premiere League tables.
> far too much can rely on a few events that are basically a coin flip Can you give us some examples?
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.
Re: Goldman Sachs model to predict World Cup game results didn’t come close
#10The World Cup is about the worst sporting event for data led predictions like this, far too much can rely on a few events that are basically a coin flip. It would be interesting to see how the predictions went for something like the Premiere League tables.
> far too much can rely on a few events that are basically a coin flip Can you give us some examples?
Someone deciding to handball the ball out of the way, a tackle that goes harder in a temper flare. A penalty that is saved/missed