Carmen Colomer, head of performance for the Perth Glory Football Club and former director of sports science for the Philadelphia 76ers, is an Australian physiologist and sports scientist with years of practical field experience in athlete load management and recovery. A recent conversation with Colomer spanned the topics of movement-tracking systems, managing performance loads and meeting the needs of coaches:
Discussing wearables on the NSCA Coaching Podcast, you said, “You need to get the athlete buy-in. If you’re asking an athlete to wear something ... that’s a commitment on their behalf, too.” What are the primary pain points that still need to be solved in movement-tracking technology?
Inter-unit reliability has always been a pain point for many practitioners. Having two athletes run the exact same drill at the same velocities, yet yielding different results, is frustrating to say the least. Battery issues are forever present with any GPS or LPS sensor, whether this is due to human error or technological error. Also, the size and placement of the unit can sometimes be dangerous. Rugby players wearing units between their shoulder blades, for instance, can pose a risk if a tackle goes wrong.
From your recently published study in the International Journal of Sports Science & Coaching, entitled “A qualitative study exploring tactical performance determinants from the perspective of three Rugby World Cup coaches,” you mentioned on Twitter that a key takeaway was to “ensure coaches are receiving practical and useful information that meet their needs.” How can performance evaluators using movement-tracking systems achieve that goal?
The important piece here is the interpretation. There are thousands of insights that can be gained from movement-tracking systems, but knowing how to tell a story that resonates with the coach, or primary decision maker, is crucial to its value.
Knowing which questions to ask the coach (or coaches) is also valuable, as this can guide the story you tell with the data. This requires an understanding of the coach's wants and needs from a game plan and philosophy perspective, then understanding the demands of the sport. Finally, understanding basic periodization so this can be aligned with the coach’s technical and tactical micro-, meso- and macrocycles.
What are some of the most important insights to be gained from a movement-tracking system that can be applied to athlete load management?
For me, understanding the distances covered at different velocities is essential. Monitoring high-speed running (HSR) is of course important, but monitoring the velocity band just below the HSR threshold can also give you a lot of insight. A lot of overuse injuries happen within this velocity band, so ensuring players are accumulating sufficient load is important.
You’re currently working with an Australian football club, coming off your stint with the Philadelphia 76ers. Given what you know about the Sportlight system and its uses in soccer, how can you foresee the tech translating for NBA organizations?
This would solve a lot of the problems I encountered. I can't speak for other teams, but from my experience there are validity limitations, especially with using different systems across the week. For example, movement-tracking data is collected from one system at the training facility, a different system when traveling and, again, another during games – with limited data on the variation between the systems. Having one system used across all these venues and situations would solve this issue.
As a veteran of NBA sports science, what are a few examples of movement-tracking data collection you’d like to see brought to basketball?
I like to see a tracking system that doesn’t require athletes to wear sensors. Basketball training is very different from other team sports, where players can spend hours on the court working with a coach one on one, then come back late that night and work for another few hours with a specialist coach. Unless there were staff at the facility 24/7 giving the athletes their sensors as they walk onto the court, there’s no way to capture that data.
Most movement tracking systems do an excellent job of providing sports scientists with valuable absolute and relative information. However, there’s still a lack of information that characterizes athletes. For example, we can easily observe the total accumulated HSR as well as relative HSR based on an athlete’s velocity max. But this doesn’t tell us how the athlete accumulated this distance. In other words, if the athlete accumulated 300 meters of HSR, I would like to know if this was in 10 30-meter efforts as opposed to three 100-meter efforts. This is valuable for training and when returning to performance following an injury. Similarly, understanding each athlete’s change-of-direction characteristics, such as magnitude and angle of turning, would be valuable.