Part 2 Application Of Analytics In Rugby League With @Carlosthedwarf

Part 2 Application Of Analytics In Rugby League With @Carlosthedwarf

What are some recent examples of work you’ve done?

We discussed added points from kicking data that I recently tweeted. How many extra Supercoach points a player gets from kicking goals is mostly a function of how many goals that team kicks, then how well that player kicks them. If you’re looking just at individual players, you don’t get the full picture. Context is everything.  

My article on Medium looking at Tackle percentage came from a similar position. Things like Steal and Rebound percentages are common advanced stats for the NBA and I just applied that to similar situations in rugby league. We know middle forwards make the most tackles, but does one position make more than others? And if so at what rate? You can’t make a tackle if your opponent doesn’t have the ball. Were players making more tackles just because their opponents had the ball more often? The results weren’t ground-breaking but being less wrong is just as important as unearthing something insightful. 

What are your favourite resources to tap into for inspiration in this space?

Without hesitation, if I could recommend one site it’s Pythago NRL run by Liam. He consistently puts out amazing content and his NRL season previews are always a highlight. A few years back he managed to put out a pre-season article that basically covered a whole years’ worth of things on my to do list and did it significantly better than I probably would have done. Part of that is why I moved to looking at things like tackle percentages and involvement rates as I didn’t want to replicate what he’d done and tried to find something more unique to look at. If you’re not reading Liam’s work you’re missing out.

What tools and modelling/analysis methods do you use? 


Most of what I use is pretty standard – Excel, SQL, Tableau and Python (mainly for automation). I’ve been trying to teach myself R as well but I’m a time poor at the moment.

Any cool visualisations for us less technical folk?

Trellis charts in Tableau are a favourite of mine right now, especially since there’s 16 NRL teams so they fit nicely in a 4×4 grid. The below one for the split of conversion and penalty goals for NRL clubs over the past six season works well.

https://twitter.com/carlosthedwarf_/status/1237202562215862273

The barbell chart I put together for Supercoach scores depending on odds came out a lot better than I expected as well, and clearly shows the data points.  

https://twitter.com/carlosthedwarf_/status/1225615560454504449
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