Just before the FIFA World Cup tournament had begun, Goldman Sachs had famously (now infamously rather) predicted the scores of each of the matches leading upto the Final. Now that the group matches are over, if you check back the predictions you would find that out of the 16 teams projected in the GS list, 7 has lost out already. Roughly that makes the success rate of the prediction as 9 out of 16, i.e. 56%, which is as good as flipping a coin (50% theoretically).
And if you check the predicted line-ups of Round of 16, none of the combinations did match. So if you had put your bet solely based on the Goldman Sachs prediction, you might have lost a few cents already. But did you really put your money based on the Goldman Sachs prediction alone? Then you not only have ignored your common sense, but also the basic principles of probability.
If you have studied or used statistics in any part of your life, you must be aware of Bayes’ Theorem. Even if you have not heard about it, it hardly matters, as you can get the fundamentals from your common sense. Principally it suggests that the probability of an event changes from its Prior Probability due to another event that has occurred in between. The new probability is called Posterior probability. Let’s see how this common sense can be applied to the FIFA World Cup.
Spain was the 2010 World Cup winner, and the probability of them winning it back again this year was quite high, that is before the game started. Accordingly Goldman Sachs had put them in the Semifinal lineup. In Probability theory parlance, the Prior probability for Spain of winning the World cup before the first match was predictably high.
However Spain lost the first match to Netherlands 1-5! This is quite an event, and if you are going to predict the winner of the tournament, you must have been taken into account before updating the probability of Spain winning the World Cup still (Posterior probability). The key to that calculation is to finding the probability that Spain really messed up the first match instead of it being a fluke. If you are a follower of the game, you must have noticed that it was not a fluke by Netherlands. That reduced the chance of Spain to quite a large extent.
And then came the second match. The Prior probability of Spain winning the cup before the second match was already lower (as equal to the Posterior probability after Netherlands match). Spain lost the match against Chile. After this match, the Posterior probability of Spain still going on to win World cup became much thinner. Finally Spain went out of the tournament.
The key learning of these events is, if you are into the prediction of the tournament, you need to consider each of the events that are happening daily and impacting the final outcome. It may sound pretty common sense, but somehow as it has been told by some intelligent men, "Common sense is not so common."
Till that time, follow Bayes’ theorem to update the predictions and enjoy the FIFA World Cup.
Also published in LinkedIn blog.
Also published in LinkedIn blog.
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Thank you for checking this article. I contribute regularly on Technology & Management related stuff. Apart from this blog, you can follow me at
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About me: I have been working in the areas of IT strategy & usage of Digital technology to deliver business growth. My areas of interest include Enterprise Mobility, Cloud Solution Architecture, Enterprise Architecture, Social Media and Big Data. I am an alumni of Indian Statistical Institute (MTech Computer Science) and also attended Harvard Business School Executive Education on Innovation and Driving Growth.
Thank you for checking this article. I contribute regularly on Technology & Management related stuff. Apart from this blog, you can follow me at
Twitter: https://twitter.com/csubhamoy
Facebook: https://www.facebook.com/csubhamoy
Linkedin: https://www.linkedin.com/in/csubhamoy
About me: I have been working in the areas of IT strategy & usage of Digital technology to deliver business growth. My areas of interest include Enterprise Mobility, Cloud Solution Architecture, Enterprise Architecture, Social Media and Big Data. I am an alumni of Indian Statistical Institute (MTech Computer Science) and also attended Harvard Business School Executive Education on Innovation and Driving Growth.
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