Impact of Sleeping Patterns on Athletes in High Performance Sport

Impact of Sleeping Patterns on Athletes in High Performance Sport

In our conversation with Haresh Suppiah we discuss his PhD in sleep, training intensity & performance as well as his experience across Singapore & Australia. He also discusses the more technical aspects of his work and advice for the next generation of students transitioning from university to industry. Hope you enjoy the read and feel free to check out more of his work here!

Tell us about your background

I started my career in sport as a Physical Education teacher. Following this, I undertook a Bachelor of Exercise and Sport Sciences at the University of Queensland. That experience deepened my research interest in S&C as well as sports physiology. I then went back to Singapore, in 2012, to do my PhD in Exercise & Sport Physiology. As part of this experience, I was lucky enough to work within the high-performance sports sector in Singapore, which led me to join the National Youth Sports Institute (NYSI) upon the completion of my PhD, in 2016, as a Sports Physiologist. In this capacity, I supported several national bodies with optimising the performance of national athletes for various international campaigns and competitions and led the Research and Development arm of the institute to undertake and operationalise quality applied research and analytics on youth athletes and to develop scientific communication output and research knowledge for practitioners. During my time there, I was also fortunate to have done a one-year secondment at the high-performance sports policy division in the Ministry of Culture, Community and Youth which gave me a broader overview of the sports ecosystem.

Most recently, at the start of 2020, I made the exciting move to Melbourne to join La Trobe University (LTU) as a Postdoctoral Research Fellow in the discipline of Sport and Exercise Science. Personally, I used to enjoy playing several sports ranging from soccer, boxing, martial arts, triathlon. I’m a huge fan of mixed martial arts as well.

Tell us about your area of specialisation in your research

My doctoral research focused on the effects of various sleep-related interventions on elite youth athlete performance. This has included examining the impact of sleep extension, napping and other novel interventions such as bright light therapy on sport performance. However, my research interests have widened due to the applied nature of my roles resulting in me applying myself in other areas within sports physiology, strength and conditioning and talent identification and development. My data analytical skills help complement whichever area of research I’m working on.

What career paths would interest you going forward? What would your dream job be?

My dream job has always been one that has allowed me to unravel novel insights with data within sport. In that regard, I’ve been, and continue to be, very lucky in the roles I’ve held. I also enjoy teaching and scientific communication and have always tried to weave that into my various roles.

Which sports could your research apply to

Because sleep is a basic human need, research in this area potentially has applications on all sports. However, as a field, the effects of sleep loss on sport performance is still burgeoning and requires continued high-quality research for the practical applications to be tailored to each sport. Luckily, there are many great academics and researchers working in this area.

How would you compare your experience with your PhD at La Trobe and experiences with any external sporting bodies or athletes

The apparent difference is that my current role is very research-centric and also ensuring that LTU students have an outstanding experience with us. However, the partnerships that LTU has with sporting clubs and institutes means that a lot of my previous experience is still relevant when working with these partners.

I’d recommend starting by getting to know what people can do with sports data in terms of visualisation and insights. Twitter is a great way to do this and often provides the inspiration that many need to start learning the necessary technical skills

Which resources have been the biggest help in your journey so far

Online learning platforms such as Datacamp, Udemy and Udacity coupled with resources from Stack Overflow and GitHub have been crucial in the data analytics/science work. From an academic perspective, tools such as Mendeley and EndNote have helped tremendously in accelerating many work processes. I am also fortunate to be working with highly experienced colleagues and collaborators that have always been willing to share their expertise.

What tools and modelling or analysis methods do you use

I started off my career being entirely dependent on tools like Excel and SPSS, which are still really powerful tools. But I’ve since moved to leverage programming languages such as R and Python due to their accessibility and flexibility of usage. Most of my analysis is done using quantitative methods, which vary depending on the needs of the projects.

Any cool visualisations for us less technical folk

This is a visualisation done using R’s ggplot package that highlights some preliminary data we have on the fluid consumption rates of elite youth athletes under two different kinds of training scenarios. This was done with just a few lines of code in R Studio.

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

I’d recommend starting by getting to know what people can do with sports data in terms of visualisation and insights. Twitter is a great way to do this and often provides the inspiration that many need to start learning the necessary technical skills, such as coding, to perform similar data science techniques. Then, if you’re keen to take these skills to the next level or potentially work with sports data as a career, do look into La Trobe University’s Master of Sports Analytics.

If you had to pick one sporting code or team and solve a problem for them, who would it be and what would the problem be

I think that esports have a lot of potential to leverage data analytics and sport science theories and this is an area I’ve been very interested to apply myself in.

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