Using data to make predictions is certainly nothing new but where an information revolution is really taking place is in the accuracy of predictions modern technology is allowing us to make.
Thinking of areas and industries where accuracy is paramount, health care is likely to be at the top of that list. It’s a field where the right information can mean the difference between life and death and where, sometimes, you’ve only got one chance to get things right.
Predictive analytics is helping to improve accuracy. Hospitals worldwide are now implementing systems that can quickly scan through patients’ information and predict their outcomes. This ultimately aids staff in providing better and more streamlined care.
Although not quite as life threatening, the sporting realm relies just as heavily on accuracy. If you believe the words of coach Tony D’Amato (Al Pacino) in the film Any Given Sunday, “there are only inches between winning and losing.”
With that kind of philosophy it’s easy to understand why professional sports teams have welcomed data analytics with open arms as they search for an opportunity to gain that crucial edge over the opposition, and use analytics to make on-field decisions.
At Mindfull we work with the Auckland Blues Super Rugby team to integrate predictive analytics, with the aim of forecasting when players might be struck down with injury and finding the next superstar of the sport.
Using RFID tracking modules attached to players, we are able to track metrics such as acceleration, distance travelled, intensity and other performance indicators to run these against medical data. On top of this, we also take into account injury history, wellbeing and demographic data to determine the likelihood of future injuries.
By formulating patterns from the data for each individual, trends can be extracted outlining certain workloads that make them susceptible to injury and from there management know when to reduce a player’s activity or give them rest days. What this method of analytics also reveals is each individual’s performance peaks. By having players follow the right programme, management can ensure that, come game day, their team is at their optimum performance levels.
By analysing the characteristics and data of current stars, we are able to pinpoint certain traits and patterns that would make younger players more likely to be a high-performing team member.
The data includes more than just on-field performance with aspects like personality, family, culture and education also entered into the equation. Using this data, we enable the Blues to discover youngsters carrying similar characteristics, and evaluate whether they could be potential stars using the patterns developed from the existing athletes.
To find out more about the possibilities with predictive analytics click here.