No coding, no PhD’s. New insights,
new answers, new superpowers.


No coding, no PhD’s.
New insights, new answers, new superpowers.

bigdata and predictive analytics in sports

Machine Learning is becoming part of the most varied fields, be they professional or private.


Sports are no exception, wether it is individual or team sports, amateur or professional, and there are already many case studies able to witness a reality far above the imagination. Below, we will talk about two, analyzing in particular how the targeted development of Machine Learning technologies can support the increase in sports performance, significantly contributing to the change in the entire professional sector. Like it or not.


Behind the great results, lies the great contribution provived by technology, in particular that of Machine Learning and Prediction Analytics.

Thanks to the synergies, the football clubs have in fact begun to gather an enormous amount of data on all the players belonging to the club, (from youth sectors to
satellite teams, up to the first team), including biometric and physiological parameters, training behavior and feeding style. The data can then be analyzed up to the composition of a series of predictive models designed to understand the progress of the players to maximize their performance with highly targeted training.
The results can be rewarding right away. The information collected leads to a decrease in injuries and an increase in the economic value of the players as well as, as already mentioned, to victory.


The second case study to be examined is linked not to a single episode but to a single sport, cycling, totally changed.
What should we attribute such an important change to? Obviously, to the introduction of new technologies that have allowed the collection of data and to Machine Learning models, that have allowed us to formulate accurate predictions on sports performance.
Power meters, heart rate monitors, impedance scales, lactate meters, fitness watch today allow us to collect a huge amount of data linked to individual performances. This means that athletes can predict, with a few days in advance and with reasonable certainty, what will be their sporting performance, thus being able to calibrate the best race tactic.


It seems quite clear, in short, that the work of any sports manager and professional trainer can no longer be separated from Machine Learning and from taking on skills
in data science and data analysis. Because the professional sports scene has already changed forever.

– Blog Author

Oct. 21, 2019
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