Steve Barrett, Director of Sport Science and Research Innovation at Playermaker, earned his PhD, MSc, and BSc in Sport Science and Performance from the University of Hull. Steve has worked in the elite sport environment for more than 14 years as a practitioner with Hull City and The FA (England Women’s), and as a coach gaining his UEFA B. He is a BASES-accredited supervisor/reviewer and a chartered sport scientist, and he has expertise in wearable IMUs in sport.
Freelap USA: Mental fatigue is real in sports, yet most research focuses on neuromuscular fatigue and metabolic fatigue. Could you explain to the readers what mental fatigue is and how it can play a role in team sports like basketball or soccer?
Steve Barrett: Mental fatigue is a psychobiological state experienced following exposure to cognitively demanding tasks (Boksem et al., 2005; Lorist et al., 2005) and has been theorized to be detrimental to performance in sport (Coutts, 2016). Within soccer, led by Chris Thompson, we have been able to see the thoughts and perspectives of players at different age groups and standards across the sport, showing that mental fatigue has multiple factors that can influence it.
For example, within professional soccer players in the U.K., travel during congested fixture periods was deemed as one of the biggest onsets for mental fatigue in professional players. Given that the travel expectations required by professional athletes in the U.S. is so much greater than those at the domestic level in the U.K., the influence this might have on performance requires further exploration. Slower reaction times, slower times to complete cognitive-based tasks (including decision-making skills)—these are influenced by an individual’s state of mental fatigue.
Freelap USA: You did an internal and external load study years ago; a classic study that can really teach a lot of coaches the value of contrasting objective workloads and internal responses. With heart rate seen as just coming along for the ride now with wearables, how can coaches get more out of TRIMP?
Steve Barrett: As practitioners, one of the biggest things to consider within the performance continuum is whether or not what we do influences or helps the coaches/ athletes to achieve their goals. The dose of that given exercise or task will then have a specific response from the athlete.
We conducted the study you refer to, with Iby Akubat as the lead author, in my first coaching role at Scunthorpe United. We were constantly trying to better our support for our athletes and make sure that the methods we used to assess their response to a given task was reflective within the numbers we provided to the coaching staff and players. With traditional TRIMP, the scores tend to be arbitrary, and each individual has a similar calculation. Using the iTRIMP proposed in this paper (and throughout Iby’s PhD thesis), we identified that by using an individual’s blood lactate scores at 2 and 4 mmol, we were able to see stronger correlations between the exercise dose to the player and their response.
Freelap USA: Bio-banding is a popular method in youth sports. Outside of peak height velocity measures and general talent identifications, can you share any new ideas on how to keep youth sports improving the science without turning them into miniature professional teams? It seems that LTAD needs more physical education and less formal training. A really hard topic for sure!
Steve Barrett: It’s an interesting one, to be honest with you! There is a lot of good work being led by Dr. Chris Towlson over here in the U.K. that is examining different methods we can use to help us identify talent within soccer, with potential implications across other sports. There has been a big bias toward the physical implications of youth development programs when comparing early and late developers; however, when we look at the potential implications on the technical/ tactical elements of the game, there are two ways of looking at it. One, if you play against bigger and stronger kids (early developers), you may not get as much of the ball. However, on the flip side, you might end up having to make decisions more quickly and move the ball more quickly to avoid the contact with those bigger kids, something that within our recent study we have seen early signs of.
Invisible talent identification may be a potential route to promote good science within LTAD models without letting the kids fall out of love with the game, says @SteveBarrett5. Share on XOne of the things we have advocated is to remember that these are kids playing a sport that they enjoy with their friends. The methods we look at adopting are those that go on in the background and bring us more insights, while allowing the players to take part in the sport they love. For example, the use of video analysis, footwear technology (PlayerMaker), and heart rate data can provide us some powerfully insightful data, while allowing the kids to forget they are even being monitored. Invisible monitoring has been a term previously adopted, but invisible talent identification may be a potential route to promote good science within LTAD models without letting the kids fall out of love with the game.
Freelap USA: Repeated sprints are often used for conditioning, but the trade-off on fitness and maximal velocity is usually determined by the rest periods and volume. When trying to prepare athletes for a season, how do you identify which athletes are fit and which athletes are fast but lack conditioning?
Steve Barrett: Within team sports such as soccer, which place different demands on the body throughout the activity, I’ve tended to discuss a continuum/scatter graph of marathon runners in comparison to sprinters. We all want players to be able to run as much as possible, but also be as quick as possible. The ability to repeatedly perform high-intensity efforts is desirable within most team invasion sports.
In order to identify our sprinters, marathon runners, or the nice blend in the middle, we have specific tests or field-based drills that we can do. For example, when performing repeated sprints, we can look at the quickest time versus the average sprint time versus the slowest sprint time within a period of repeated efforts. This allows us to see some form of a fatigue index during the sprints, while also assessing who is actually the quickest player.
Whatever sport you work with, running a review of the demands of that sport can help us identify what exactly a repeated sprint/effort is within that sport. Then we can take and perform that in a manner that allows us to make assessments that help support the athlete’s ability to improve their speed, or their ability to perform repeated efforts/maintain their speed for longer.
Freelap USA: Foot sensors are growing in popularity in the mainstream, such as Stryd and RunScribe products in endurance running. Strangely, speed and team sports don’t have the same support with IMUs on the foot. Can you share how this is a paradigm shift toward the future? It’s almost a no-brainer to have micronized wearable sensors for locomotion.
Steve Barrett: One of the biggest takeaways I had from my research into using IMUs is that the location of the device can bias your results depending on what you are assessing. Within team sports that involve running, we generate a lot of our speed and power from the interaction we have with the ground…. So surely, looking at what happens close to the ground can help us inform our practice better? Furthermore, when we start to place these units at our central line, we can sometimes miss the ability to assess our individual leg contributions to that exercise.
One of the biggest takeaways I had from my research into using IMUs is that the location of the device can bias your results depending on what you are assessing, says @SteveBarrett5. Share on XGoing back to one of my previous answers, we look to assess the dose-response relationship of our athletes to ultimately help them improve or reduce their risk of injury. By having these IMUs closer to the ground (and on each foot), we can get insights into the response of our limbs during different types of exercises. For example, being able to assess if “fatigue” has influenced our kinematics might have implications for us as practitioners to help build a conditioning program for that athlete.
If I’m able to see during repeated high-intensity efforts that their contact time is increasing on their right leg, causing a large asymmetry between their left and right, can I then build up that athlete’s robustness by performing some unilateral strength work under fatigued and non-fatigued states? It provides us with insights that we have had before in a lab environment but have just never been able to get within the field domain.
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References
Boksem, M., Meijeman, T., and Lorist, M. “Effects of mental fatigue on attention: ERP study.” Cognitive Brain Research. 2005;25(1):107-116.
Lorist, M., Boksem, M., and Ridderinkhof, K. “Impaired cognitive control and reduced cingulate activity during mental fatigue.” Cognitive Brain Research. 2005;24(2):199-205.
Coutts, A.J. “Fatigue in Football: It’s not a brainless task!” Journal of Sport Sciences. 2016;34(14):1296.
Thompson, C.J., Noon, M., Towlson, C., et al. “Understanding the presence of mental fatigue in English academy soccer players.” Journal of Sport Sciences. 2020:1-8.
Akubat, I., Barrett, S., and Abt, G. “Integrating the internal and external training loads in soccer.” International Journal of Sports Physiology and Performance. 2014;9:457-462.
Towlson, C., McMaster, C., Goncalves, B., et al. “The effect of maturity-status bio-banding on the physical and psychological responses of academy soccer players during small-sided games.” Science and Medicine in Football. 2020:1-8.
