This monthly blog feature will focus on the concept of Load Management, looking into the definition and history of the terminology, how the concept is applied in a practical setting and evaluating how PlayerData aims to simplify this process through our new ‘Workload’ metric (coming soon).
What is Load Management?
Load is defined as the cumulative pressure that a player endures during training or competition over a period of time (Jiang et al., 2022).
Load is often measured through physical GPS metrics such as distance, sprint distance, accelerations and decelerations (Jiang et al., 2022).
Hence, load management refers to how coaches and practitioners aim to control the exposure levels to certain levels of load, in order to ensure their athletes can consistently perform well in competition with a reduced risk of injury.
Examples of Load Management techniques
Training Load can be altered and controlled through various measures, such as;
- Changing the duration of the session
- Adapting the frequency of training
- Increasing the number of high intensity drills
A real world example of when these load management techniques are utilised would be in periods of high fixture congestion. For example, if you typically compete on the weekend but a midweek fixture gets introduced - then as a coach you’re naturally forced to change your training plan. This is done due to the understanding that athletes can’t perform at their best with limited recovery time. In fact, research shows that short-term fixture congestion may increase risk of injury sustainment (Jiang et al., 2022).
Overall, load management is simple when written down but is incredibly hard to manage in absence of Sport Science professionals to aid operations. However, the new ‘Workload’ metric being developed by us here at Playerdata, aims to break down those barriers - simplifying the load management process without the loss of quality.
The New ‘Workload’ Metric
This Workload metric that is soon to be released has been derived from the concept of Load Management, aiming to give coaches insights into how much and how hard athletes are working in training or competition. Hence, ‘Workload’ presents itself as a single value derived from a combination of volume and intensity metrics, compared to a performance baseline established from the previous 28 days.
The metric itself is displayed as a rating for the session on a scale of 1 - 10, with 5 being a baseline for the individual.
This scale is calculated through a combination of intensity and volume metrics such as distance, metres per minute, sprint distance, high intensity running, accelerations and decelerations. We take how the athlete has performed under each intensity and volume for a session and put it against the baseline. Their baseline is defined as their average performance under each variable across the last 28 days. Moreover, their performance for that session is compared to the baseline, this score is then scaled from 1 - 10 and this presents itself as the athletes Workload value for that session.
Join our Insiders Group for early access and help provide feedback on the latest product developments from PlayerData.
References
- Jiang, Z., Hao, Y., Jin, N., & Li, Y. (2022). A Systematic Review of the Relationship between Workload and Injury Risk of Professional Male Soccer Players. International journal of environmental research and public health, 19(20), 13237. https://doi.org/10.3390/ijerph192013237
