John Young is living the dream of many a data analyst. Following a 16-year career at an elite sports coaching level, he transitioned into a role as Chief Analyst and Data Scientist at the Central Coast Mariners Football Club. For two years he assisted in player performance evaluation and analysis across all the teams as well as set player goals and planned their seasons. Young is now a sports data scientist working on a consulting basis with several different sporting teams in Australia and the US, including an NFL team, while he completes his PhD in the use of deep learning in sport.
Central to his role is the ability to quickly process gigabytes of data from each game, creatively collect data on the other teams and mine that data for insights for the coaching staff, all based on data and sports science best practice. The data Young examines is critical as it can help reduce injuries, improve performance, and extend athletes’ careers.
While his office environment may differ to that of a typical data scientist, his role has similarities. The data load is significant: there is about 180 billion bytes of data per game to analyse including heart rate, skin temperature, perspiration and information about the player's gait. Along with the tools for collecting biometric, spatial, location, speed, game statistics and other data, Young carries high capacity drives wherever he goes.
Seagate Technology’s Regional Vice-President, Robert Yang, says, “We certainly need to consider a variety of data users as we design and continue to develop solutions for data storage and access. As data scientists proliferate into a wider range of roles than ever before, technology solutions must keep up with data storage, accessibility, security, capacity and scalability requirements to help them tackle the challenge of making vast amounts of data usable and beneficial."
Critical to the contribution
Young makes is his ability to see things in the data the coach, athlete or
other observers would not notice. He spends considerable time
understanding what questions to ask of the data and then identifying the data
points that will be important, thus removing guesswork, assumptions or
hypothesis. His goal is to deliver data driven insights to the coaching
staff that are beyond watching game or performance videos and assessing player
stats. This helps inform player, training, team and match strategies, and shape
recruitment planning for the club.
“Professional sport is, ultimately, a business, and like any enterprise, decision makers look to their data scientists to ensure that the actions they take on behalf of their business are based on data-driven insights, assessments and conclusions” Yang says. “For their part, the data scientist must deal with very high expectations in terms of the sheer amounts of data they must process, and very quickly, to yield relevant, action-oriented insights.”
According to Young, it’s not enough to be a great number cruncher if you want to be a Sports Data Scientist. Communication skills and the ability to help educate others in how to interpret and understand the data findings are also vital. Interestingly though, coaching experience is not essential and indeed a lack of experience with a specific sport can be a benefit as it ensures little bias towards the data.
It’s still early days in the world of Sports Data Science, with just two of the 32 NFL teams in the US employing data analytics staff and four of the teams in the local football league. But those who are involved, including John Young, are finding themselves in high demand as they pursue alternative approaches to capturing, collecting and analysing data that allows them to deliver what is being described as ‘deep learning’ in sport.
Learn more about the Data Age 2025 and how data can be critical to the success of your business at https://www.seagate.com/au/en/our-story/data-age-2025/
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