Every month we take a deep dive into the latest research in sports science. In the October edition we start off looking at disordered eating in sport, including a look at prevalence, warning signs, and more. We then look at how training can be viewed in terms of creating synergies, monitoring training load in endurance athletes, integrated sports rehabilitation, game day priming, and more. Read more
Dave Reddin has helped assemble performance teams and structures at England Rugby, the Football Association, and British Olympic Association. Together, they achieved historic results. On this week’s GAINcast he joins us to discuss how coaches can best work together to support a team, as well as thoughts on how sports science and monitoring can best fit into the performance equation. Read more
Despite recent investments into monitoring at all levels of sports, the injury reductions and performance improvements promised have failed to materialize. Why is that? On this episode of the GAINcast Aaron Coutts and Franco Impellizzeri from the University of Technology Sydney dive into all aspects of the science of monitoring: why we monitor, technology, loading, metrics, fatigue, overtraining, subjective measures, planning, and more. Read more
Every month we take a deep dive into the latest research in sports science. In the June edition we take a deep dive into several articles on building mental toughness and resilience in training. Mental toughness is a term that is thrown around a lot, but without many coaches knowing exactly what it is or how to train it. We then look at the importance of individualized recovery, and how coaches commonly monitor athletes. Read more
In the previous article, I wrote about a variety of different models that better help us explain and understand why injuries occur. As a quick refresher, we typically have a predisposed athlete, who finds themselves in a local environment that increases their susceptibility, and they then have an inciting event which causes the injury itself. Central to many of these models is the concept of stress or load placed on the athlete. This installment of the Performance Health series looks to help coaches understand external and internal load, and what that means to coaches. Read more
Every month we take a deep dive into the latest research in sports science. Players are key partners in building a team culture, and their contributions depend a lot on their informal roles. The first article we look at in this month’s edition breaks down key traits of cultural architects, which can assist coaches in developing their own team culture. Then we look at ecological dynamics, acute:chronic workload ratio, training time, and more. Read more
On our last episode we looked at how some youth and amateur coaches are dealing with the current pandemic. This week we get some feedback from the pro level with Mike Potenza. He shares how the San Jose Sharks are managing their athletes through this situation and how that compares to a typical offseason approach. We also discuss training flexibility, his in-season training philosophy, player monitoring, and more. Read more
When Melbourne Storm director of performance Lachlan Penfold came on the show in 2018, we focused solely on his coaching journey that has led him through the NBA, NRL, AFL, Super Rugby, Rugby 7s, Olympic softball, javelin, baseball, and much more. On this week’s GAINcast we have him back on to dig deeper into his approach to training team sport athletes, including his thoughts on workload, speed, monitoring, testing, injuries, and more. Read more
Over the last decade, the use of GPS and similar technologies to track player movement in field sports has moved from a luxury to a necessity. Even small schools and small clubs are investing heavily in technology and staff to analyze the data. Is this the future of training? Will tracking every step help drive performance to new levels? The technology can bring some key benefits, but as with anything there are downsides too. These are rarely discussed. In order to get the most out of player tracking technologies, there are a few questions coaches need to ask first.
Are you capturing the whole picture?
To truly plan, you need the complete picture. By making crucial decisions based on data with big gaps, we potentially create larger issues down the road.
There are many areas where such gaps can occur. As Craig Pickering highlighted in January’s Sports Science Monthly, a recent article looked at the loads coming from warm ups, showing that this can account for 20-30% of total loads. If you only put on the GPS unit when the game or training starts, you’re missing a big piece of the puzzle.
Even more troubling is that GPS measures essentially running load. In sports like soccer, where the majority of load is running load, that might make sense. But in other sports, this is only part of the picture. Stopping on our own and stopping by being tackled involves the same number of meters covered, but a very different impact on the body. A scrum in rugby involves almost no meters covered, but an intense effort from the athlete. Even change of direction has a great mechanical load that is not captured just by measuring speed and distance. When Vern and I visited Rome in October we heard some great research being initiated by Accademia Preparatori Fisici to measure just how large the gap is between GPS and total load in rugby and other sports. It was jaw dropping. But it is was even more shocking to then think of the important training decisions we are making based on just this partial picture.
Do you need different viewpoints?
Even if the data set is complete, one set of data only gives you one viewpoint. This makes is harder to put the data in context. Managing a training plan based on loads is like managing a lifting plan entirely based on volumes. It would be crazy to set up a lifting program where next week’s volume is entirely dependent on this week’s, but as I pointed out on this week’s member hangout that’s what more and more on-field training is looking like. There are many other factors to consider beyond quantity, such as quality, internal load, and more.
The one viewpoint often missing is whether the team is actually getting better. The data that dictates my own training plan is whether we are throwing farther. This is easy for me to quantify. If lower training loads lead to that, then I’ll use lower load. If higher loads help, I’ll do higher loads. But I don’t led the loads determine the loads. In fact I haven’t calculated our weight room volumes in years. Instead I let the performance determine the loads.
Are you using data proactively or reactively?
As mentioned above, much of how GPS is utilized is reactive in nature: if data shows an athlete worked too hard, you give them rest. Good training programs need to be responsive, but you need to have some idea of where you are heading in the first place. An entirely reactive program is unlikely to get you where you need to go. In speaking with Mike Bahn this week, he explained the point better than I can:
“Technology is driving the problem, whereas the problem should drive the technology. The problem has to be identified before solutions can be constructed.”
It doesn’t have to be this way and there are plenty of coaches that use GPS proactively. But it is the minority. Dean Benton is one that take the opposite approach. As he puts it, he use GPS for prescription, not restriction. GPS can help us better analyze the game and sport demands, which in turn can help us plan better and create targets. Rather than simply monitoring loads, the data can be used to see if we did what we planned to do. That’s a simple change in practice, but a big change in mindset that has proven successful in his work with previous teams.
Are you planning for the short term or the long term?
Focusing on daily and weekly data loads creates a tunnel vision effect that focuses training on the short-term rather than the long-term. A short-term mindset a leads to short-term thinking and long-term problems.
Here’s an example: a prevention mindset focuses on avoiding everything in the short-term that might cause an injury. This might prevent the next injury, but could cause even greater issues in the long-term, either a lack of development or greater injuries down the road. Even if nothing major comes up in the future, we often pull them out of more training than they would have missed if they were injured. As Sam Robertson pointed out on Twitter: “If a player misses x training sessions to prevent an injury that never eventuates, they may end up actually missing more training.” Naturally, if you don’t train, you won’t get better. The prevention mindset never asks how they can get better.
Are you still willing to experiment?
The problem with relying on data is that you become locked in to what you have done until now. New becomes the unknown and it is much easier to play with tools you’ve used (and measured) before. Clubs that having been using GPS for many years have created detailed databases of the drills they use, so they know what training loads to expect from them. What happens if they might need another drill to get better? They might not consider it. They box themselves into what they have done in the past, forgetting that they may have missed something big entirely. Future training can become biased towards tweaking past training rather than trying new things.
Finding the way forward
You might read the above and think I am against player tracking technologies. It is quite the opposite, the idea intrigues me and I have seen GPS used in ways that brings great value to teams. But doing it right takes time and thought. You can’t simply plug in technology and expect it to be a game changer the next day. You have to hire the right staff, take your time, and use it as one element of training, not the only element. Most importantly, you have to ask the right questions.
The whole concept of load management as it is being interpreted and implemented is beyond me. Frankly, it makes no sense. Call me old school, but isn’t good planning and training design that prepares the athlete for the rigors of competition what we are supposed to be doing? We have reduced the quality and intensity of training to meet magic numbers developed by flawed measurement devises based on artificial algorithms. Read more