Leicester Tigers find software 'predicts' players' injury The programme, thought to be the first of its kind in the Aviva Premiership, is being run as a controlled experiment to test its accuracy. It could go "live" by the end of the season. "We are running the whole team as a control group," Shelton added. From the last two weeks we have had 13 injuries or varying severity. The model has picked up nine of those. Either the data is not quite ­accurate enough yet to predict the injuries it missed or the injuries would have occurred regardless of whether they was fatigue on the ­tissue in the first place. Shelton said that a wide range of data - from quality of sleep to immune system activity - has been analysed in each player alongside information about their previous injuries. He expects the margin of error to fall over the course of the season. "We measure subjective data from the players, things that affect their well-being such as hours of sleep," Shelton said. Then there is objective data as well. The players wear GPS units in training and in games, which gives us an idea about the movement of the player and the sort of forces that might be going through their body. We can also collect some collision data as well, so we can get a really good idea about everything that the players are doing on the training ground and during games. Similarly we also collect data on previous injuries that they had and what they are doing in the gym, ­basically everything they do from when they walk in the door of the club in the morning and leave in the evening is collected. The IBM package stores our ­historic data and then we run our new data set through that existing model. It allows us to analyse whether this new data looks like something we have seen in the past that has led to an injury. It gives us a prediction, a measure of confidence in the prediction and risk percentage. Shelton says that while some injuries - particularly collisions that led to knee ligament damage - cannot be prevented, he hopes the ­programme will enable the club to tailor individual training programmes to try to minimise the risk of injury. "Non-contact soft-tissue injuries and some collision injuries are avoidable because you can affect both the strength of the tissue and the amount of fatigue that is on that tissue," ­Shelton added. The aim is to be able to affect a player's lifestyle through the week. For example, if they recorded a very good night's sleep, then their risk of injury could go down from "predicted injured" to "not-predicted injured." It may be that certain players are predicted as injured because they haven't done enough training. It could involve doing extra recovery work or ensure their nutrition is very good when they are in a high risk of injury. It may be the model also flags up that, if a player increases his strength, his prediction of injury may go down through the season by, say, 10 per cent. The aim is to never get to the stage that a player is predicted as getting injured on game day. We want to affect the prediction before that.