Artificial Intelligence in Sport

Artificial Intelligence in Sport

Artificial intelligence (AI) is a buzzword gaining popularity at an immense rate. Nader Chmait discusses his journey including a PhD in AI and application of his research within his role in the Australian sporting industry. The article is designed to help you discover the possibilities of modern technology in sport. Enjoy!

Tell us about your background

After completing my Masters’ degree in Computer Science at Notre-Dame University in my home country (Lebanon), I moved to Australia in 2013 to start a PhD in Artificial Intelligence at Monash University. I graduated from Monash University in 2017. 

During my PhD I worked as a sessional teaching associate at Monash University where I tutored/lectured (postgraduate level) subjects including Artificial Intelligence, BI Modelling, Computer Models for Business Decision Making, Introduction to Software Engineering & Data Management. Since 2017, I have been working as a postdoctoral researcher at Victoria University (VU) and a Data scientist at Tennis Australia (TA). 

You’ve got a Masters in Computer Science and a PhD in AI. What were the key areas you focused on in your education and research

My Masters research was mainly focused on the applications of bio-inspired algorithms and heuristics to solve complex problems (such as the scheduling problem). My PhD research was about quantifying the performance of cooperative heuristics and machine learning algorithms using notions from algorithmic-information theory. In other words, I did experiments and simulations to measure how well groups of (machine learning) algorithms perform under different cooperative settings. 

How have you been able to apply your research and theoretical knowledge to your work in the Sporting industry

I will discuss my published work for now. Two of my published journal papers in the “Sports Management Review” and in “Telematics and Informatics” journal are listed below. 

Tennis superstars: The relationship between star status and demand for tickets. This work consisted of doing statistical modelling to measure the impact that professional tennis players have on demand for stadium attendance at the Australian Open. I demonstrated how much individual players have influenced stadium attendance at the Grand Slam, and discussed the non-player related factors that impact ticket purchase for the Open. 

Tennis influencers: The player effect on social media engagement and demand for tournament attendance. In this work I show that the effect of professional tennis players on social media user engagement extends beyond their talent (professional rankings). I modelled the impact of some tennis stars on prompting social media activity, after accounting for factors related to their performance, the tournament rounds in which they were featured and the opponents against whom they played.

The other work that I’ve done with TA was mainly in the area of Business Intelligence and understanding consumer behaviour. Overall, some of the Machine Learning skills that I developed during my PhD were useful to do the research I currently do with VU and TA. 

I modelled the impact of some tennis stars on prompting social media activity, after accounting for factors related to their performance, the tournament rounds in which they were featured and the opponents against whom they played.

How has data science and AI/ML evolved in the time you’ve been involved within the sport tech space

On the business end, there has been quite a big drive in using AI and ML to design and implement sports business strategies that are user-centred. More sophisticated tools or methodologies are increasingly being used to understand fan behaviour and their preferences and consequently customise sports events according to these preferences.

On the athlete performance end, many sports organisation are implementing deep learning and other ML models to analyse match events: from creating classifiers that predict ball trajectories, to building player tracking technologies that help in (a) coaching and (b) enhancing viewer screen-experience when consuming sports on TV or over the internet.  

What are the key tools and methodologies you’ve used

Mostly statistical packages to build predictive models (regression models, Decision trees and so on) and visualisations. On a day-to-day basis I use R and SQL among other tools including social listening tools and cloud data platforms. 

While the tools used are important to get the job done, the real value/advantage lies in the understanding of the underlying modelling techniques and methodologies and how they operate, when are they needed and how to assess the output. 

What are some exciting applications of AI/ML that you’ve seen recently that you’re excited to see come to fruition

Apps with augmented or virtual reality solutions that incorporate advanced sensors are quite exciting. But these are mostly engineering solution harnessing the power of Artificial intelligence and ML. 

I am personally passionate about custom business intelligence solutions for sports organisations. For instance, I’d like to see the Australian sports industry move towards a more intelligent sports offering which enhances user experience and aligns the offers with their expectations, particularly in commercial terms. I see a future in the use of AI and ML to identify and propose packages and subscriptions models in real time! From intelligent dynamic pricing-models, to discounts and gifts based personalised user experiences, all the way towards an Internet of Things (IoT) solution where fan profiles are built based on a combination of factors including their favourite players, favourite food, genre of music, preferred time and channels of watching sport. 

If you could use your experience and skills to help one player; who would it be and what would you assist them with

If by player you are referring to an athlete, I would choose an Australian tennis player (maybe one of the upcoming players). 

Player success is not only performance dependent. Fandom and charisma play a major role. Successful players earn much more from endorsements than from prize money. So, I would add value to the players’ careers by informing them of how they compare to other professional players in terms of their impact on demand for attendance and social media influence, with the aim of enhancing their economic value and their revenue. One example is by advising players on how much to demand in appearance fees when attending non-grand slam tournaments. 

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