Thomas Dos’Santos is a senior lecturer in strength and conditioning & sports biomechanics at Manchester Metropolitan University, as well as a physical performance coach of para-football for the Football Association, which oversees all aspects of the amateur and professional game in England, from grassroots football to the Emirates FA Cup.
Dos’Santos has published more than 90 peer-review articles, many of them focusing on areas of interest and expertise such as change-of-direction biomechanics, anterior cruciate ligament injury screening and intervention, inter-limb asymmetry, and assessment and development of strength and power characteristics.
One of your areas of expertise is mitigating non-contact anterior cruciate ligament injury risk. Are most teams screening and conducting interventions appropriately, and how can modern performance-tracking systems aid in that task?
I personally don’t think teams are adopting the best screening practices for their athletes, which therefore doesn’t result in individualized biomechanical or neuromuscular (NMS) targeted interventions that can mitigate ACL injuries. Teams are often restricted on time, and may not have the financial resources to adopt gold-standard laboratory techniques, which then restricts high-quality biomechanical/NMS testing. That said, there are recent advancements in technology, such as markerless technology, which could be used to screen athletes’ movement mechanics during tasks such as jump-landing, deceleration and change of direction (COD), which are the key mechanisms tied to ACL functionality (and injury) in numerous sports. However, to my knowledge, no markerless system yet produces valid data for frontal and transverse kinematics.
From my understanding, teams are very rarely evaluating their athletes’ movement quality during these three tasks. Athletes’ movement quality and injury risk profiles are task-dependent, and I would argue that failing to evaluate our athletes’ movement quality during these three tasks is negligent. I am a big proponent of using simple, 2D video evaluations of athletes’ movement quality during jump-landing, decel and CODs, and to identify sub-optimal movement quality linked to potentially high mechanical loads (such as knee valgus and lateral trunk flexion). This can be easily done in the gym or field, or even by watching training and game-play footage. Identifying those athletes with sub-optimal movement quality can then allow the multidisciplinary team to develop individualized, informed and targeted interventions rather than applying generic training interventions to mitigate ACL injury risk. Modern performance-tracking systems, if valid, can help improve the feasibility of testing without testing (i.e., invisible monitoring) to allow more ecologically valid screening of athletes’ movement mechanics in the field.
Female athletes have been another area of study for you. We know that women are more at risk for injuries such as ACL tears and concussions. As a strength and conditioning coach, how does your approach to female athletes differ, if at all?
To be honest, my S&C approach doesn’t really change between males and females. The only thing different that I would consider is a female’s reproductive status/profile and symptomatology when designing and delivering training programs. Although there is no direct evidence, as far as I am aware, for MC phase-based training if the female is eumenorrheic, we need to ensure that our approach conforms to the key principle of training: progressive overload! Whether assessing a male or female, I would be more concerned regarding the athlete’s training history and age, movement competency, physical testing results and previous injury history over their gender.
My philosophy for ACL injury prevention, irrespective of sex, is characterized by four pillars: 1) developing perceptual-cognitive ability (due to the neurocognitive element of ACL injuries); 2) periodization and monitoring of mechanical loading (to regulate tissue homeostasis and avoid the fatigue failure mechanism of injury); 3) development of technique and movement quality (e.g., jump-landing, decel, acc and COD optimal techniques to reduce mechanical loading); and 4) development of multi-segmental (knee and non-knee spanning musculature) physical capacity (e.g., muscle activation, rapid force production and neuromuscular control).
Although there is evidence that females tend to be more susceptible to ACL injuries due to a range of different factors, addressing socio-economic inequities for females begs more consideration and research. By providing them better-quality sports science, medicine and strength-and-conditioning provision, women athletes are more likely to develop their technique (pillar 3) and strength (pillar 4) – two key, modifiable ACL risk factors.
Additionally, improved monitoring of training load (pillar 2) would have a positive effect. For example, in ballet, the ACL incidence rates between sexes are minimal, in part because of the high-quality training provided for young girls to accumulate deliberate practice of key motor skills and physical qualities. This model needs to be applied to other sports and organizations.
What sort of insights can Sportlight provide about change-in-direction movements that legacy performance-tracking systems had trouble delivering?
The unique thing about Sportlight technology is that not only is it able to provide information pertaining to the frequency of different turns and CODs (in addition to other locomotor activities), but it is able to provide detailed, holistic information regarding the mechanical properties of COD such as turn angle, entry and exit speeds, entry and exit distances, turn time, and peak and average acceleration and deceleration – during both training and match play.
Importantly, the technology is non-invasive (not involving a device that an athlete must wear), which should improve athlete and coach compliance. Additionally, its portability and usability in indoor settings are further advantages. The wealth of information regarding the COD profiles and activity of players then allows practitioners to make informed decisions about the potential mechanical loading, while also allowing them to establish typical normative data regarding the physical demands of match play and training.
This information can also help develop position-specific and contextualized sport-specific agility drills and testing assessments. Importantly, an understanding of the physical demands can assist rehabilitation and reconditioning practitioners when working with previously injured players, ensuring that the athletes can tolerate and meet the expected COD mechanical demands of match play. This allows for a more objective and conservative approach when progressing COD intensity during rehabilitation, which is too often neglected in most return-to-play protocols.
You recently retweeted from your Twitter account a paper about drop-jump analysis. The researchers discussed drop-jump assessments providing a controlled environment for analysis, but could performance-tracking systems also be used to track in-competition samples? It seems there might be some efficacy in that – especially in, say, basketball or track-and-field settings.
Definitely. As stated previously, “testing without testing” during training and match play and “invisible monitoring” could be a massive part of future athlete profiling. For example, athletes perform numerous sprints, decels, CODs, jump-landings during training and match play. So with the correct, valid technology, there is no reason why data pertaining to kinematics and spatio-temporal characteristics can’t be obtained for insights into their physical capacities. In-situ force-velocity profiling has recently garnered attention using the GPS data collected from training and match play (over a period of time). There is no reason other bits of technology such as LiDAR, RADAR, LPS, GPS, opto-electric – potentially in combination with other technology, such as AI and computer vision techniques – can’t give direct information pertaining the velocity, angular kinematic and spatio-temporal characteristics of different tasks, such as decel, COD and jump-landing, in addition to sprints and curvilinear sprints.
What do you consider to currently be the most important difference-making characteristic among performance-tracking systems?
The ability to provide more holistic information about the movement strategies and locomotor profiles (kinematics and spatio-temporal characteristics) of not only traditional linear sprinting tasks but also deceleration, curvilinear sprints and COD tasks, which is externally validated and reliable.