In our chat with Dave, we discuss his background, interesting approach to various sport analytics problems and advice on how to get started. If you enjoy the article, check out his blog and Twitter handle for more quality content!

Tell us about your background

I’m based in Melbourne. I started off working as an Animal Welfare Officer in a research facility. After getting bored of that, I decided to go to University. I did a Bachelor of Health Science majoring in Applied Statistics at Swinburne. While I was studying there, I worked for Perform Group doing live updates for local soccer games. Last year I started the Masters of Sports Analytics at La Trobe University and recently I just did some work for Cricket Australia in their community cricket sector, mostly looking at participation numbers.

How did you get into data analysis in sport

As cliché as this may sound, seeing the movie Moneyball. I was in a job I didn’t really enjoy and was under utilised in. I saw Moneyball and it just made sense to try to pursue a career like that because I loved sport and was always pretty good with maths and statistics.

Which sports do you analyse and what types of problems have you tried to solve

A lot of my analysis has been for university assignments. Unfortunately by the time I’ve put my time into school for the last couple of years, it hasn’t left me with a whole lot of time for my own analysis. I wrote a paper on the in-game factors that predict success in professional level competition for the video game DOTA2. Some other examples include creating measures for ranking the best shooter in the NBA and making models to predict the 2019 AFL finals.

I’m currently working on my master’s thesis which is creating a model for predicting a player’s future career success. Other than that, just little projects like passing maps for players or the positions where teams score goals from.

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

I tend to recreate other people’s work but using a different sport or league just to teach myself a new technique. If there isn’t a question that I want to answer for myself I will ask friends for things they want to know about in sport. Which also makes me think of how I present my models or visualisations for people with no technical background.

Would be cool to see the AFL or NRL copy what some of the American sports do with their data contests…this may also lead to more interesting and innovative work for other problems

Dave Matteo

Which tools and methods of analysis do you use

I mostly use R as my analysis tool. As for methods it will really depend on the task. As a rule I just try to use the most interpretable method that sacrifices the least accuracy.

Any cool visualisations for us less technical folk

These are maps of the goals and assists created by Melbourne Victory in the 18/19 season. Not the most stunning thing to look at but the pitch is drawn completely by co-ordinates using the ggplot package in R.

How do you think the Sport Tech space in Australia compares with the global landscape

I think a lot of the growth is now just getting accepted by the wider Australian sports market because the expertise is here. Would be cool to see the AFL or NRL copy what some of the American sports do with their data contests, so more people with data interests could apply different ideas to solve the solutions. This may also lead to more interesting and innovative work for other problems.

What advice do you have for the couch fan who wants to start playing around with some data

Just do it I guess. Find any data you think is interesting and start a small project. Use excel to start with to get some confidence with data if you’re new to it all. A lot of the first data projects I ever did before starting to study statistics and analytics was doing fantasy team spreadsheets and playing with different ways to value the players.

Follow people on twitter who have sports analytics content. Lots of accounts have good learning resources and from my experience people in the sports analytics community are happy to give advice to people.

If you could use data analysis to work on a problem with any sporting code or team, what would it be and why?

Absolute dream would be working in recruitment for Melbourne Victory. With the way the A-League is set up being able to maximise your scouting efficiency is so important especially when the club is signing foreign players, so I would love to help the club improve in that area.