Every year in Melbourne, January sparks the start of a series of sporting events that keep us entertained right the way through to March. From the end of December and throughout January we have had the luxury of an action packed schedule of Big Bash (20/20) cricket, the Australian Open tennis and after a bit of a lull in February, there is the Australian Grand Prix to look forward to in March.
Whilst the sporting action continues to provide the spectator with excitement, enjoyment and entertainment, the role of analytics and data science in these events continues to grow with each edition of these great events.
The Big Bash has really stepped up its use of analytics this year. Both from a coaching perspective, with team captains and coaches repeatedly citing all the ‘homework’ they are doing on the opposition to produce more effective field placements and the like; and with the commentators, who have access to a plethora of statistics on things such as where batsmen’s favourite spots to hit the ball are (Hot Zones) and how certain batsmen perform against certain bowling types. This last point was actually a major point of controversy in one of the final group games when one of the commentators accidentally (well we hope it was an innocent mistake) informed the fielding team’s captain of a particular weakness that an incoming batsmen had to a certain bowler in the fielding team. As within the business world, this served as a reminder that analytics should only be used within the boundaries of a set of ethics, principles and standards to ensure that data is being used for the right reasons and within a set of governed standards and principles.
In the Australian Open, the data being provided for the tournament website and mobile app is all driven by IBM’s ‘Slamtracker’(1) technology (more info available here). They are drawing on more than 41 million data points across 8 years of grand slam matches to predict performance, match outcomes and fan sentiment. The lead developer behind the technology, Kenneth Agregaard Jansen, talks about the importance of analytics to growth, competitive advantage, improved business performance and to enable effective actions to be taken in the markets that you work in. For Tennis players, that means optimising their preparation and adapting for each opponent that they face, but the same logic applies in the business world too.
Finally, we have the F1 Grand Prix in March – a blockbuster weekend on the Melbourne events calendar and one of the most popular races on the F1 schedule. Back in my recruitment days in the UK, I was working with a candidate who was finishing up a contract as a Data Architect for one of the leading Formula 1 teams. The sheer volume of data that he was responsible for (both collecting and transmitting in a reliable fashion) was staggering. Updated quotes that I found online were in the region of 2GB per car, per lap and around 3TB per race (2). The client I ended up placing this candidate with had only one reservation with the candidate – my industry is nowhere near as ‘glamourous’ as the world of Formula 1 racing that he is coming from. However, the basic premise of using analytics for competitive advantage stood true and he ended up doing a great job working on their transformation programme. To further this point, other industries are now utilising the technologies that the car manufacturers have developed to benefit their own industries, for example, ConocoPhillips are working in partnership with McLaren to utilise the McLaren data systems expertise on their oil rigs(3).
So whether it is the use of Analytics in sport or in business (or a combination of both), Analytics will undoubtedly continue to play a vital role in the performance and success of individuals and organisations. The underlying principles are the same across both though – if you go about it in the right way, you can use Big Data Analytics to help drive competitive edge, reduce risk of failure and to provide actionable insights to heighten your chance of success.
Interested to learn more? Our Big Data Science course looks at both the technology and business concepts that are leading the way in the field of Analytics and Data Science.
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