Global positioning systems (GPS) were first used in sports about 20 years ago, and have become more and more prevalent across not only elite sporting teams, but also sub-elite and amateur organisations. It is not uncommon for professional teams to employ a full-time “GPS analyst”, alongside other members of the sports science/performance structure. While the technology and software have been streamlined, staff commonly spend hours upon hours poring over the data these systems provide, in an attempt to prevent injuries, or to “maximise” performance. But what does that actually mean? Can injuries actually be prevented? What are we doing that can even influence performance, let alone maximise it?
Unfortunately I am of the belief that, for the most part, we are missing the point. Don’t get me wrong, I think that these devices (along with the in-built inertial sensors) have been a great advancement in the industry. They allow us to objectively quantify what previously we would have had no choice but to guess. However, knowing what is happening during a session is a very separate issue from knowing the implications of that load. Right from the very beginning of my career, fresh out of an undergraduate internship, I was being asked questions like “have we done enough” or “have we done too much”, because I was the guy sitting behind the computer with the numbers on it. I definitely gave it my best shot, but in all honesty, what did I know? I didn’t have the knowledge to understand the complexities of these questions, the context of where the athletes were in a microcycle, or how we were expecting them to recover. I didn’t have the skills to foresee how this load was going to affect the afternoon’s weights session, or to consider the impact of the hour-and-a-half video review session the players had just completed. I could have had the most finely tuned training load optimization program that I had downloaded from the internet, and I don’t think it would have helped me one bit.
This skill set is a rare one, and is achieved only one way – experience. I am extremely critical of the way GPS are used in a team-sport environment, where decisions are based upon what this load will do to the team’s acute:chronic workload ratio for example. Yes, there may be reasonable research to suggest that certain levels of training load are associated with elevated injury risk, I accept that. However, these associations are just that – associations. Despite what many studies might try and suggest, no one can “predict” injuries. In the words of the famous American baseball catcher, Yogi Berra, “it’s tough to make predictions, especially about the future”. I’m not suggesting we disregard measuring cumulative loads and studies quantifying injury risk and their relationships with injury. I just think that we need to slow down a little bit in that regard and really consider what GPS does (and more to the point, doesn’t, but that’s a topic for another day) measure. Put trust in people’s experience with what works and what doesn’t work, and simply use these data to guide and compliment performance decisions.
On the other hand, there are plenty of ways we can integrate GPS technology within a team-sport setting to compliment other members of the performance staff. For example, although the limitations of the metabolic power method for quantifying true energy cost of team-sport activity have been discussed in depth (Buchheit, Manouvrier, Cassirame, & Morin, 2015; Osgnach, Paolini, Roberti, Vettor, & di Prampero, 2016), the fact is this method is our best guess at actual energy expenditure, and can still assist nutrition staff in periodising energy intake or post-session recovery protocols. Alternatively, we can work with conditioning staff to ensure that players are being exposed to the desired stimulus during a session, whether that be a high-speed running volume, or time above 90% of the players’ individual max heart rate (MHR) (Buchheit and Laursen, 2013). This information is also useful for strength coaches when planning a training block, or making modifications for the afternoon’s session. Lastly, and in my opinion most importantly, is the integration of sports science with coaching staff. I genuinely believe that when done correctly, we as sports scientists can use tools such as GPS to actually influence the scoreboard in a positive way. Obviously all performance structures are not the same, and some coaching staffs are going to be less receptive to intervention that others. However, if the message is delivered appropriately, sports science can be used to not only replicate the physical component of competition, but to also integrate this aspect with the technical, tactical and cognitive elements required of match play. We can assist coaches design sessions and training drills to be time efficient, specific to the requirements of the game, and develop players across the board.
Throughout my following blog posts, I will discuss each of these topics in a bit more depth. This initial post was intended as a bit of an outline on the type of content I will be discussing in coming months, and I hope you have enjoyed it.
Multidisciplinary approach: I work closely with Jace to analyse game-play and training data, looking for trends in energy expenditure over time. Taking the average energy expenditure of a player over a full competitive season I could then calculate the energy expenditure relative to body mass and time (kcal/kg/min) in order to develop a more strategic approach to fuelling, periodising intake to reflect competition and training demands, and support pre-determined outcomes (Anderson et al., 2017). The GPS data also helps to quantify specific actions such as decelerations. It is widely recognised that muscle damage from eccentric exercise can impair muscle glycogen resynthesis. This then feeds into my recovery protocols, where I would consider utilising a more aggressive carbohydrate-rich approach if the circumstance dictates. Despite the known limitations in the validity and reliability of this data, these numbers are a useful starting point for nutritional interventions.
Anderson, L., Orme, P., Naughton, R. J., Close, G. L., Milsom, J., Rydings, D., . . . Morton, J. P. (2017). Energy Intake and Expenditure of Professional Soccer Players of the English Premier League: Evidence of Carbohydrate Periodization. Int J Sport Nutr Exerc Metab, 27(3), pp. 228-238. doi:10.1123/ijsnem.2016-0259 Retrieved from http://journals.humankinetics.com/doi/abs/10.1123/ijsnem.2016-0259
Buchheit, M., & Laursen, P. B. (2013). High-intensity interval training, solutions to the programming puzzle: Part I: cardiopulmonary emphasis. Sports Med, 43(5), pp. 313-338. doi:10.1007/s40279-013-0029-x Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/23539308
Buchheit, M., Manouvrier, C., Cassirame, J., & Morin, J. B. (2015). Monitoring Locomotor Load in Soccer: Is Metabolic Power, Powerful? Int J Sports Med, 36(14), pp. 1149-1155. doi:10.1055/s-0035-1555927 Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/26393813
Osgnach, C., Paolini, E., Roberti, V., Vettor, M., & di Prampero, P. E. (2016). Metabolic power and oxygen consumption in team sports: a brief response to Buchheit et al. Int J Sports Med, 37(1), pp. 77-81. doi:10.1055/s-0035-1569321 Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/26742014