Weighted predictor variables and performance trend analysis

The first 10 matchdays of the current season in the Bundesliga revealed some clear disadvantages of my Poisson model. The predictor variables attack and defence strength respond too slowly to performance changes of single teams. This was clearly shown by the loss produced by the poorly performing FC Cologne. A normal SMA (simple moving average) does not use a weight. So latest results, which represent the current form, have not a higher priority over older results. As I looked for solution for this problem I stumbled over the EMA (exponential moving average). This post will explain the use of the EMA and how you can implement it inside the Exasol, so that it is usable as an analytical function for the predictor variables. On top I will show you, how you can analyse the team performance with help of MACD (Moving Average Convergence/Divergence oscillator ).

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How To: Kicktipp strategy simulation

I don’t know, how many of you know Kicktipp. Kicktipp is a very popular betting game in Germany, where everybody can start an own small betting community and can invite people to this community. This is very popular with friends and in companies especially during the big tournaments like the world cup. My company has also a yearly betting game for the German Bundesliga. The rules are very simple: You have to tip every match and you get 4 points for the correct result, 3 points for the correct goal difference and 2 points for the correct trend. In this post I will show you different betting strategies for Kicktipp and test, whether they are useful to win your personal Kicktipp betting game.

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How To: Install TensorFlow for Windows

I currently started to test machine learning algorithms to predict the results of football matches. I especially tried to use neural networks. But I soon realized, that the possibilities of R regarding neural networks are a little bit limited. So I want to take a look at TensorFlow. TensorFlow is a machine learning library provided by Google, which was already used for many different use-cases and proved its suitability.

As the installation process for TensorFlow was not self-explanatory, I thought, it would be a good idea to provide a small installation guide. I want to explain, how I installed TensorFlow and the Python GUI PyCharm.

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How to beat the bookie: Value Betting

There are many ways to beat a bookie. One of the well known methods is arbitrage betting, where you try to find price differences between different bookies. Some years ago this was a really good method, but today, as every single information about sports is available throw the internet, it is hard to find difference between bookies.

I will mainly focus on the so-called Value Betting. But what is Value Betting and how does it work?

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