These days, arguably, the most useful tool we have in sport is the data we collect, and with more technology working its way into sport, we only create more data. For this data to be useful though, we need both manage it correctly, and we need to know its limits.
Sport Science in particular that has seen the greatest growth of incoming data, and has resulted in the emergence of data science. Essentially the culmination of data analysis and predictive analytics, data science can be a useful tool in performance, with the aim of ultimately providing the elusive ‘edge’. The issue that we face however is that with an influx of information, we need to be able to collate it so that it can provide useful evidence to manipulate or maintain current practice.
Generally, when we collect information, the mistake we tend to make is that we limit the scope of what we look at. We need to remember that each set of data we collect is linked to each other, test from test, day from day, and week from week, its all related. This is why we must evaluate the data we collect as part of a system of information, and this is where a database comes into play.
Allowing us to store access and analyse the data we collect, databases are the most powerful tool in data science, because they consider all the data collect and not individual sources. Databases have grown along side the number of sources of data, and have seen the birth of many sport specific software systems.
Fusion Sport’s Smartabase is such a system that provides a database enabling easy collection, correlation and analysis of the data collected, from athlete loading information through to daily subjective monitoring. The Premier Leagues PMA goes one step further, with the ability to produce comparative reports and competition standards, as it is a system offered to all premier league clubs. Further again, the NSW Waratah’s partnership with IBM is an example of in depth analysitcs used for predicting injuries.
While these sophisticated systems are growing in popularity, seemingly by far the most popular system still, is microsoft excel. Only limited to your abilities, in sport science excel still tends to be the most used system for information analysis, because it’s fully customizable, can be as simple or complex as you’d like it to be, and because there are so many resources out there that can guide you to taking advantages of these benefits.
Ultimately, each example is simply a platform to bring together all of the data we collect, to simply the analysis to hopefully shine light on trends in performance, and furthermore, to provide the evidence to support and steer current practice.
The fact of the matter is you can’t escape the data in sport, but the issue we face is how much reliance do we put on it. Simply put, numbers can paint a picture of events that have unfolded or of certain performance characteristics. In order to further improve on these numbers, we must use them, scientific reasoning, and common sense to analyse how these values change over time and if they’re changing for the better or for worse.
It is important to remember though, that numbers only provide a piece to the puzzle, and not the whole thing. If we rely on numbers too heavily, or treat them as gospel, sometimes we can paint the wrong picture, or neglect necessary information. While an athlete’s loads might look good, it doesn’t mean they are immune to injury, or that their risk is low. More often than not, the information we collect won’t reveal this and rather the qualitative information we obtain, simply talking to them or watching them perform, can be just as vital to the puzzle as the quantitative data we collect.
“I’m a believer that coaches have been doing movement screens for over 100 years and it’s called watching practice.” pic.twitter.com/p9aV9PoMNz
— ALTIS (@ALTISworld)
What numbers cannot do is predict what is going to happen, performance or injury, or tell us why it is going to happen. We must instead, use the numbers to aid in evaluating performance. That means watching training and matches, observing players in the gym and in warm up, and using the data to reinforce our thoughts on how capable players are to deal with the loads we are giving them, mechanically and physiologically.
It is important to have a system that we can use to help us make sense of all the data we collect, in order to provide us with evidence to steer away from danger, and towards enhancing performance. At the end of the day, numbers can’t tell us everything, and while they are an essential tool for building on performance, where we get into trouble is immersing ourselves in calculations rather then the coaching.