How tennis joined the data revolution

How tennis joined the data revolution

‘The rise in analytics in tennis is long overdue,’ Head of Tennis Australia’s Game Insight Group (GIG), Dr Machar Reid, said in an article on the Australian Open website earlier this month.

In the same week, the New York Times reported ‘data analytics have become de rigueur in major sports’. Tennis, which had been slow to embrace this trend, has finally stepped up to join the data revolution at this year’s Australian Open, the article declared.

Pioneering Australian research

GIG formed in 2008 with the aim of becoming ‘the world’s leading authority on tennis science and helping the sport make up for lost time’.

Last year, GIG’s Dr Reid and our Associate Professor Stuart Morgan (working at the Australian Institute of Sport at the time), along with several other industry experts, published their internationally award-winning research.

The aim of the investigation was to deep dive into three years’ worth of Australian Open HawkEye data – that’s 37,727 shots – to identify the crucial shots and movement patterns of the world’s best players.

Once identified, the team could then use their findings to accurately predict the probability of a player winning at any moment, taking into account individual player style and match context.

‘Earlier work has often focused on the characteristics of ‘winners’, but we recognise the winning shot is often the least strategically-important shot in the rally. Rather it is the strategy over the preceding strokes to move an opponent out of contention in a rally that matters.

‘Understanding how points are won requires a deeper understanding of the way players manipulate their opponents to establish dominance,’ they wrote in their report.

The results ‘would give tennis fans, broadcasters and players an insight into what works and what doesn’t in each matchup,’ ESPN wrote of their research, which was awarded the Grand Prize at the world-leading 2016 MIT Sloan Sport Analytics Conference in Boston.

Dr Reid told Australian Open that the report and its recognition ‘showed we could compete with the world’s most popular sports in the analytics space’.

Beyond the numbers

Deep-diving into sophisticated analytics doesn’t just provide ‘more numbers’, it offers greater insight and context.

Dr Reid told The New York Times: ‘We intuitively all know Rafa Nadal’s forehand is one of the best in the sport, but why is that?’

‘A level one stat might be that Rafa hits that ball at 140 k per hour. But now if we’re able to layer in or interpret that speed alongside his precision or weight of shot or capacity to hit winners or — on the flip side — produce errors, if we were able to amalgamate that and identify a shot scorecard that allowed us to rate a player’s forehand or stroke performance, that for me is a level two stat, and far more interesting.’

When Nick Kyrgios unexpectedly lost in the second-round of this year’s Open, commentators and former champions Jim Courier and Llyeton Hewitt were left speechless, the Australian Financial Review reported.

Reid, however, could look at the data for answers. ‘In terms of quantifying it, with Nick in sets three and four, what you saw was a 30-40 per cent reduction in his work rate across those two sets. That is, the average intensity for each shot. In the fifth set the work rate elevated again [although it was good later],’ he told the AFR.

‘We saw Kyrgios’ intensity and movement dropped off on each shot, whereas Seppi sustained his intensity and movement. He did not lower his level, he maintained it throughout the course of the match.’

Today’s sports fans demand more

Sophisticated insights and analytics are obviously invaluable for players and coaches, but they also enhance the experience and engagement for avid fans.

IBM’s Stacy Newrocki says fans today, ‘especially millennials which represent the new fanbase’, no longer want to just watch the sport but rather ‘participate, analyse and critique’ the game and their favourite players in real-time. ‘They demand interactive entertainment,’ she continues.

‘That’s why more and more teams are developing second screen apps to keep fans engaged inside and outside the stadium….These apps provide fans with ways to speak out, share opinions, gain insights, engage with one another, buy tickets…’

The Australian Open in partnership with IBM is doing just that: providing predictive, real-time data analytics. ‘Fans can see how their favourite player is progressing against key indicators. Everyone can see how public sentiment changes over time. All of which brings the Australian Open to life in the most engaging ways possible,’ IBM explains.

‘‘What we’re trying to do is get the fans to engage at whatever level they want to with the statistics, but making the statistics the interesting thing and essentially turning the statistics into the story of the player,’ said IBM’s, Ian Wong.

Future jobs in the elite sports industry

For sport science graduates entering the elite sports industry, Associate Professor Morgan says those with data analytics skills will have a huge advantage.

He says data analysis is ‘very important and increasingly important’ in sport. ‘The whole domain of sports science has changed over the last 10-15 years and the number of technical devices for collecting data has increased.

‘The important thing about sports science now is the capacity to be able to handle and work with those kinds of data.

‘If you’re a graduate with data science and sport science qualifications, you’re going to be very, very competitive in the elite sport job market,’ he says.

Associate Professor Morgan is the Course Coordinator of our Master of Sports Analytics.

 

Image: Athletes via Pexels (CC0.1.0)

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