Skills

R

Python

Matlab

Visualisation

Machine Learning

Optimisation

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I used mathematics to create an alternative 2018 fixture, one that is predicted to increase total annual attendance by ~300K, while still sticking within the fixturing rules. In the article discuss how I created the solution, the final results and the impact of certain fixturing rules. Amongst other things, the study demonstrates that optimal number of Friday night matches for Carlton is indeed 5, and that the AFL foregoes ~100k per year to ensure league parity.

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I made a machine learning algorithm to predict AFL matches before they started. When I simulated my results on 2017 matches and used it for betting, I managed to get a net positive return on my investments.

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In this article, I’ll present a basic introduction to what machine learning is and why it is so powerful and a little toy example of how I inferred that free-kick differential has nothing to do with your chances of winning (statistically).

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