The Waratahs will be using predictive analytics technologies to reduce player injuries as part of their quest to win 2014's Super Rugby competition.
An Australian-first, the long-term predictive analysis project comes as IBM signs a new two-year agreement to be the club's Technology Partner, extending the relationship between the two parties to nine years.
The technology is being used by the Waratahs to inform decisions regarding player training load, enabling the training and coaching staff to "predict and act rather than sense and react" so that they can field the best possible team throughout the season.
The analysis predicts the likelihood of a particular player being injured, which then enables the coaching team to adapt and modify each player's personalised training program to maximise their training load and minimise their risk of being injured.
Statistics currently show that rugby players miss an average 2.15 games per season and Waratahs Athletic Development Manager Haydn Masters wants to lower that number.
"The aim of our strength and conditioning program is to improve athletic performance and increase injury resilience to ensure players spend the most amount of time possible on the field," he told the Waratahs' official website.
"IBM's predictive analytics technology gives us a very objective, sensitive and reliable measure of predicting each player's limit and their injury risk and allowing us to modify training accordingly."
The Waratahs collect player data from a range of sources to build a clear picture of each individual player's welfare and performance. This includes a GPS tracker fitted to each player to measure and monitor intensity levels, collisions, and fatigue during training and matches.
The GPS data is then is combined with medical data, wellness data and player data, and over a period of time, clear patterns and early warning signs start to emerge.
The long-term project for predictive insights will provide the Waratahs with a critical opportunity to anticipate an injury and change the variables, such as modifying the training regime or resting a player, to reduce the chance of injury.
Masters added, "At the moment we collect between 100 and 250 variables per player per week from GPS data, medical screenings and wellness reports. IBM's system allows us to collate and analyse all these variables, which in turn helps us to best manage each player and, over time, build an accurate picture of what to look for individual players (and future players) and positions, in terms of predicting injury risk."