It’s no surprise that a study shows 1 in 4 rugby players will be injured during a season since the objective of the game is to take a hit for your teammates and keep the ball moving down the field.
In order to find new ways to keep top players healthy, the Leicester Tigers, nine-time champion of the English rugby union’s Premiership and two-time European champion, are using IBM predictive analytics to help the team better understand and reduce players' injury rates and minimize risk.
After all, losing a key player for an extended period of time can not only hurt the team on the field, it can also result in reduced ticket sales and spectator attendance if the team does not perform up to expectations.
Leicester is looking at important indicators such as fatigue, and threshold and game intensity levels in order to detect hidden patterns or anomalies. Better understanding this information will allow coaches and trainers to prevent injuries for each player by investing in adequate training programs, tailored to players’ physical and psychological states.
For example, if a player has a statistically significant change in one or more of his fatigue parameters and the current intensity of training is likely to be high, the data may show that the likelihood of this player becoming injured is 80 percent greater. This type of real-time information will make it possible for the team to alter the player’s training to reduce the injury risks.
Predictive analytics also allows Leicester to analyze psychological player data to reveal other key factors which may affect performance, such as stress around away games and social or environmental elements that could significantly change the way players perform during a match.
It’s basically a human form of predictive maintenance.
In the manufacturing industry, plant managers, maintenance engineers and quality control champions all want to know how to sustain quality standards while avoiding expensive unscheduled downtime or equipment failure, and how to control the costs of labor and inventory for maintenance, repair and overhaul operations.
Through the use of IBM predictive analytics, they can now gather information in real time from a variety of sources, including maintenance logs, performance logs, monitoring data, inspection reports, environmental data and even financial data to determine the areas of greatest risk.
For example, an IBM customer who manufactures helicopters is able to identify and predict equipment maintenance, ultimately increasing customer satisfaction by keeping the helicopters in the air instead of grounded for repairs.
It’s the same way that Leicester is investing in business analytics to uncover the key predictors in the data “scrum” to deliver personalized training programs for players at risk and improve performance.
Now that’s a good “try.”
For more information:
· Read the press release on the Leicester Tigers' use of IBM predictive analytics
· Read a previous blog post describing how other sports are leveraging IBM business analytics
· Download a whitepaper on predictive maintenance