Python for Fantasy Football – Random Forest and XGBoost Hyperparameter Tuning

Python for Fantasy Football – Random Forest and XGBoost Hyperparameter Tuning

Welcome to part 10 of my Python for Fantasy Football series! Since part 5 we have been attempting to create our own expected goals model from the StatsBomb NWSL and FA WSL data using machine learning. If you missed any...
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Python for Fantasy Football – Feature Engineering for Machine Learning

Python for Fantasy Football – Feature Engineering for Machine Learning

Welcome to part 9 of my Python for Fantasy Football series! Since part 5 we have been attempting to create our own expected goals model from the StatsBomb NWSL and FA WSL data using machine learning. If you missed any...
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Python for Fantasy Football – Understanding Random Forests

Python for Fantasy Football – Understanding Random Forests

Welcome to part 8 of my Python for Fantasy Football series! Since part 5 we have been attempting to create our own expected goals model from the StatsBomb NWSL and FA WSL data using machine learning. I wanted to move...
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Python for Fantasy Football – Addressing Class Imbalance Part 2

Python for Fantasy Football – Addressing Class Imbalance Part 2

Welcome to part 7 of my ‘Python for Fantasy Football’ series! Part 6 outlined some strategies for dealing with imbalanced datasets. Since publishing that article I’ve been diving into the topic further, and I think it’s worth writing a ...
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Python for Fantasy Football – Addressing Class Imbalance in Machine Learning

Python for Fantasy Football – Addressing Class Imbalance in Machine Learning

Welcome to part 6 of my ‘Python for Fantasy Football’ series! In this article we will be looking at strategies for addressing class imbalance in machine learning. In part 5 I introduced some basic machine learning concepts and explained why...
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Python for Fantasy Football – Introduction to Machine Learning

Python for Fantasy Football – Introduction to Machine Learning

Welcome to part 5 of the Python for Fantasy Football series! This article will be the first of several posts on machine learning, where I will use expected goals as an example to show you how to create your own...
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Python for Fantasy Football – APIs and JSON Data

Python for Fantasy Football – APIs and JSON Data

Welcome to part 4 of the Python for Fantasy Football series! As always, if you missed any of the previous parts, go back and check those out first before reading any further. In part 3 I mentioned that your first...
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Python for Fantasy Football – Getting and Cleaning Data

Python for Fantasy Football – Getting and Cleaning Data

Welcome to part 3 of the Python for Fantasy Football series! If you missed part 1 or 2, go back and check those out first before continuing. I’ve had a lot of positive comments on the series so far, and I...
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Python for Fantasy Football – Matchup Adjustment

Python for Fantasy Football – Matchup Adjustment

Welcome to part two ‘Python for Fantasy Football’ series! If you missed part 1, click here to go back and work through that first. In this article I’ll go through a few more useful things we can do with the...
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Python for Fantasy Football – Introduction

Python for Fantasy Football – Introduction

Welcome to the first article in the ‘Python for Fantasy Football’ series! Regular readers will be aware that I am a big advocate of using data to help better understand sports, and daily fantasy football lends itself particularly well to...
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