‘Van Meten naar Weten’ is one of the projects in the CoZone and is a partnership between Capgemini, the Dutch top level sports and science. In this collaboration we developed the Insights & Research in Sports application, better known as IRIS. A platform to store and easily analyze sports and exercise data with the use of smart solutions. Using this application, we hope to get a little bit closer to better achievements and gold medals in top level sports.
It is increasingly being said that data is the new gold. Because data provides, if properly analyzed, insights to determine what needs our attention. And what not. Good insights save us time and money. And it gives us direction in what we are doing. Nowadays we can measure almost everything. This also applies to sports. Think about a running app or smartwatch for example. In top level sports, we also use all kinds of sensors to measure sports performance and this amount of data increases every day. The big question is, how do we get the most out of this data?
We are working together with technology partner Dataiku to develop new features in IRIS. By using Dataiku’s integrated technology, we can take these insights to the next level by using the data for predictions in sports. With these capabilities, data science cannot be missing in the Dutch top level sports.
A tool in which sports and exercise data from education, science and top level sports is available in one single platform? That creates a playground for data analysts and scientists! By using smart big data solutions, IRIS makes it possible to provide historical mono- and multidisciplinary results to coaches and athletes. In addition, we are hopefully able to make accurate predictions based on these multidisciplinary data sources. By building smart algorithms, our goal is to provide coaches and athletes information about the optimal training intensity for a certain athlete. Completely customized to the physical condition of an athlete at a certain moment.
But that’s not all. By tracking eating patterns, rest and training intensity, we are trying to predict injuries in future training sessions. By combining these variables in IRIS, we are hopefully able to recommend athletes to not perform certain exercises to prevent an injury. By continuously collecting data, including data about injuries, we can feed the algorithms with new data. By doing this, the algorithm can learn and improve itself to make better predictions in the future. The power of machine learning.
Now that predictions are possible, it does not mean that we can predict which athletes are the gold medal winners at the 2020 Olympics. But the probability of success can grow by managing factors where we do have control over, with more certainty. Because IRIS helps us with the transition of only measuring to actual knowledge, we hope that IRIS can help athletes train more efficiently instead of more intensively. With this new technology, IRIS contributes to the development of talent, maintaining our spot at the top and to future sports results!
IRIS has been developed for every individual sports practitioner and is not only focused on the top level sports. In September 2018, students of the Sports Academy (ALO) at the University of Applied Sciences of Amsterdam (HvA) started with IRIS for example. In addition, IRIS is going to play a major role in the Sport Data Valley; an initiative of Sportsinnovator. Sport Data Valley is a platform that aims to bring together sports and exercise data of Dutch individuals and organizations so that they can share knowledge, (meta)data and technologies. By doing this, we contribute not only the growth of ourselves, but also to each other.
Do you want to know more about IRIS? Check dan de website!