Don’t Blame the Data - Blog Posts

Deploying an R Shiny App on Heroku via GitHub Actions and Dockerfile to Access Private GitHub Repositories

R

Shiny

Heroku

GitHub Actions

Docker

Deploying an R Shiny App on Heroku when Github Secrets are Needed to access private GitHub repositories

Rating the Difficulty of the Big 3’s Grand Slam Wins

R

elo

tennis analytics

Using Elo to understand the difficulty of the Big 3 grand slam wins

ANALYSE FOOTBALL (SOCCER) DATA IN R WITH ZERO R EXPERIENCE

R

worldfootballR

Going from absolutely zero R coding experience to being able to extract data using the R package worldfootballR.

Passing in the Top Five European Domestic Leagues

worldfootballR

soccer

Using the worldfootballR R package to analyse different passing behaviour in the top five domestic European Soccer leagues

Liverpool’s Earlier Subsititutions - an Introduction to worldfootballR

worldfootballR

soccer

Using the worldfootballR R package to analyse Premier League substitutions

Expected Goals and Liverpool - An Intro to worldfootballR

worldfootballR

soccer

Using the worldfootballR R package to analyse Liverpool expected goals in the EPL

The Agony and the Ecstasy of my first open source contribution

R

fitzRoy

My first open source contribution wasn’t all smooth sailing, but it sure was thoroughly rewarding

Effectively Simplifying AFL Tipping

R

afl

gganimate

No need to overthink footy tipping with this simple, yet competitive tipping method

Building a Linear Regression Model in R to Predict AFL Crowds

R

afl

regression

There is a lot of talk about crowd behaviour and crowd issues with the modern day AFL. I personally feel the crowd issues are a case of business-as-usual; I’ve been going to…

Using Data To Determine Which AFL Fans Jump On The Bandwagon

R

afl

This post is the first in a two-part series on AFL crowds. This analysis will be a thorough look at AFL crowd numbers over the last 20 years, and will aim to discover which…