Don’t Blame the Data started off as a place for me to share my thoughts in the form of short-form blog posts but has since evolved to be a website that holds various R libraries and Shiny apps that I have built, and more recently now also includes team ratings and match predictions from models I have built for various sporting leagues across the globe.

The one constant is that the data will tell the story. If you don’t agree with it, please, please don’t blame the data.

Importantly, all views expressed here are my own.

To get started, you can check out my most popular content below.

Projects

Below are some R libraries I have created. See more details of each by clicking the links. Additionally, I have built an in-game NBL win probability application that can be used to both view the in-game win probability of past and live, in play matches. See here for more details.

Blogs

The blog generally focuses on sports analytics and R programming (usually a mix of both), but will touch on other parts of life also, using data visualisations to tell the story. What I can promise though is it will be filled with my own selfish pleasures. I hope they align with my readers’ interests.

• Rating the Difficulty of the Big 3’s Grand Slam Wins
• Deploying R Shiny Apps to Heroku
• Set up R and get using worldfootballR

Models

Various models have been built with the aim of estimating team strengths and estimating match predictions. Model outputs - including match predictions, season simulations and player and team ratings - for the following leagues can be found by following the links provided below:

• AFLM
• NBL
• A-League Women
• A-League Men