This is a guest post by Ola Lidmark Eriksson, CTO at Wide Ideas.

Two years ago, I asked myself if it would be possible to use machine learning to better predict the outcome of soccer games.

I decided to give it a serious try and today, two years and contextual data from 30,000 soccer games later, I’ve gained lots of interesting insights.

Here goes:

The Big Data Challenge: Let The Data Mining Begin

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To begin with, I harvested as many data points as possible.

I mined old game data from every different source and API I could find. Some of the more important ones were Football-data, Everysport, and Betfair.

I then merged these data points with their corresponding results, quantified it, and put everything into one database. …


Doktor Spinn

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