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Probabilistic programming in sports analytics

Summary

A discussion and tutorial of how to use pymc to predict rugby results. Also will include an introduction to Bayesian statistics.

Probabilistic Programming and Bayesian Methods are called by some a new paradigm. There are numerous interesting applications such as to Quantitative Finance.I'll discuss what probabilistic programming is, why should you care and how to use PyMC and PyMC3 from Python to implement these methods. I'll be applying these methods to studying the problem of 'rugby sports analytics' particularly how to model the winning team in the recent Six Nations in Rugby. I will discuss the framework and how I was able to quickly and easily produce an innovative and powerful model as a non-expert.

Description

Using Pymc and the pydata stack to attack a problem in rugby analytics. Similar to my talk submitted to Berlin. Probabilistic Programming and Bayesian Methods are called by some a new paradigm. There are numerous interesting applications such as to Quantitative Finance. I'll discuss what probabilistic programming is, why should you care and how to use PyMC and PyMC3 from Python to implement these methods. I'll be applying these methods to studying the problem of 'rugby sports analytics' particularly how to model the winning team in the recent Six Nations in Rugby. I will discuss the framework and how I was able to quickly and easily produce an innovative and powerful model as a non- expert. I will go into more detail than normal, giving a few examples of Bayesian Programming, and a brief introduction to statistics and statistical thinking. My technical case study will be the Rugby Analytics, Football Analytics and FinTech friendly Quantitative Finance examples. Technology used: PyMC, PyMC3, Pandas, Pydata stack. I recommend Anaconda installed on your laptops to get everyone off the ground easily. Link to the Tutorial is here PyMC Tutorial I have the following dependencies for my tutorial. pip install patsy pandas pip install pymc - PyMC2 pip install git+https://github.com/pymc-devs/pymc3 - PyMC3 pip install seaborn

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