The New South Wales Waratahs rugby union team will be using a predictive analytics system to help anticipate player injuries and prevent them happening in 2014.
The side has selected IBM’s SPSS Modeler to collate data which coaching staff collect from a variety of sources. This includes collision and fatigue data from GPS trackers that are fitted to the players during training, medical screening information and wellness reports that the 35 players fill out on their smartphones every week.
According to IBM, SPSS Modeler predicts the likelihood of a particular player being injured, which will allow coaching staff to adapt each player’s personalised training program to maximise their training load and minimise the risk of injury.
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NSW Waratahs athletic development manager Haydn Masters told media at a briefing in Sydney that he is collecting more than 100 data variables per player every week.
“The system will allow us to collate and analyse all these variables. Over time we can build an accurate picture of what to look for in individual players and positions, in terms of predicting injury risk.
“The most important factor [with data analysis] is how much time I can get these athletes to spend on the field and maximise their outputs,” he said.
According to IBM business analytics leader Brock Douglas, the results from the predictive analytics model it built for the Waratahs were “compelling”.
“Our model analysed retrospective data from the players, and identified three players who went on to sustain an injury in the following weeks.”
He added that a rugby union player will take up to 40 tackles during a game.
“The average player will miss 2.15 games in a season through injury while one in four players gets injured in a season. The impact that can have on a team’s performance and the overall result of the game is huge,” Douglas said.
IBM has been a technology partner of the NSW Waratahs since 2007.
Follow Hamish Barwick on Twitter: @HamishBarwick