It’s not uncommon to hear talk of “injury prevention strategies” within the sports science and medicine communities, and of course the minimisation of injury occurrence is something all practitioners seek to achieve. In reality, it is impossible to quantify the number of injuries which have been prevented, and what we actually do is address those factors which have been reliably shown to be associated with increased risk of injury. Thus, what we are actually attempting to implement are interventions which mitigate (reduce) injury risk.
The key to effective injury risk management is in monitoring closely factors associated with increased injury risk, and to put into place appropriate interventions when increased risk is identified. This approach forms the basis of a robust and effective injury risk model. The pillars of this process generally include:
- Establishing daily and weekly benchmarks based on the profile of each athlete
- Identifying outliers within a specific session or training week
- Capturing the volume and intensity of each session to quantify the capacity of an athlete
- Using data from athlete monitoring devices to develop an injury risk management model
Benchmarking & Monitoring
The establishment of daily and weekly loading benchmarks is the foundation on which effective injury risk models can be built. By creating these benchmarks, it is possible to gain a deeper insight into an athlete’s ‘normal’ work profile, around which thresholds or ‘boundaries of risk’ which trigger preventative interventions can be established.
Over time, the development of individual and squad databases within athlete monitoring programmes can help coaches to identify ‘red flags’ which are associated with increased risk of injury. Once those red flags have been established, coaches become better equipped to make appropriate interventions that can significantly reduce the chances of a player suffering a soft tissue injury.
As the sophistication and scope of your athlete database builds, you can move from squad focussed interventions to positionally focussed ones to finally those which are based on the individual athlete and their unique requirements.
Programmes structured around known dose-response relationships will be more efficient and effective, can reduce injury and illness risk, and will also support enhanced training and competition performance.
Fitness & Fatigue
Quantifying the demands being placed on an individual athlete, and the way they respond to those demands, it becomes possible to better understand the relationship between fitness and fatigue. When used correctly, this information can allow for the development of a model that optimises athlete performance while simultaneously mitigating injury risk.
Measuring the relationship between fitness and fatigue will help you to identify periods when injury risk is low or high. Athlete monitoring data can help you avoid those two extremes and ensure that your training programme keeps players in the ‘sweet spot’ of positive adaptation but low injury risk.
Interested in finding out how Catapult can help your team find its competitive edge? Click here to learn more about our range of athlete monitoring technologies.