Understanding Player Load: A Comprehensive Guide to Athlete Workload Analysis
WHAT IS PLAYER LOAD?
Player Load is a metric that measures an athlete’s physical effort during movement. It calculates this by adding up the acceleration in all directions, as captured by a three-axis accelerometer. To make the number more manageable for analysis, the total acceleration is divided by a scaling factor of 100. This simplifies the overall Player Load value. Originally, the Australian Institute of Sport (AIS) developed this formula for rugby union to quantify players’ effort levels.
About Player Load
Coaches, analysts and sports scientists are always striving to quantify the performance of their athletes, but vast quantities of information can make it easy to get lost in an avalanche of data without unearthing the most powerful insights:
- Measuring athlete workload with player load
- Player load Context & validity
- Player Load: Sport-specific context
Measuring Athlete Workload with Player load
One parameter that empowers time-poor coaches, scientists and analysts alike is Catapult’s PlayerLoad metric. In scientific terms, PlayerLoad is an instantaneous rate of change of acceleration divided by a scaling factor. In coaching terms, it is a measure of your athlete’s workload.
Developed in conjunction with the Australian Institute of Sport (AIS), PlayerLoad measures workload performed independent of distance, however well correlated they may be. This leaves you with a single number – obtainable indoors and outdoors – that provides an objective view of an athlete’s workload at any given time.
PlayerLoad is measured instantaneously (an athlete’s workload at that second) and cumulatively (total workload over a session). Because heel strike force generates vertical accelerations which feed into the formula, PlayerLoad is influenced by distance for athletes whose sport involves a significant amount of movement.
Additionally, by using PlayerLoad 2D, it is possible to omit the vertical accelerometer from the calculation to enable accurate quantification of athletes covering short distances, or whose sport demands they play in tight areas (e.g. badminton). It is also a great measure of workload performed in small sided games within team sports.
Player Load Context & Validity
Distance and speed metrics are interesting with the appropriate context, but without that context they can be limiting as they don’t capture movement and impact. Giving a more complete picture of the workload an athlete gets through, PlayerLoad enables you to personalise and periodise individual athlete loads.
If a coach is seeking a quick summary of an athlete’s workload, then PlayerLoad is able to provide that. The metric can also be used to inform far more detailed analysis, with analysts being able to take the number, integrate it with other metrics, and devise their own custom parameters for deeper investigation.
For example, PlayerLoad (PL) represented per unit distance covered or time worked is an excellent indicator of movement efficiency. More efficient athletes expose themselves to less PL/min than less efficient ones. Monitoring players over time, variations in this metric are reflective of alterations in movement efficiency, or within a session of intensity of different drills.
Validated in many independent research papers, PlayerLoad is an easy-to-use solution for scientifically taking the guesswork out of athlete management, and can form a key reference point in your athlete monitoring process.
PlayerLoad’s Sport-specific Context
- American football: Chronic to acute indicators
- Australian rules football: Minimising injury
- Ballet: Quantifying workload
- Basketball: Balancing workload
- Futsal: Assessing injury risk
- Rugby: Managing individuals and teams
- Soccer: Objectifying performance
- Tennis: Live tracking in-game
- More metrics in our premier wearables solution: Catapult Vector
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.
/// More Catapult Fundamentals
1. Why use GPS tracking technology?
GPS-based technologies are used throughout sport to support performance monitoring, but how do they work, what do they measure, and how do they benefit athletes and coaches?
2. Why is athlete monitoring important?
Recent innovations have enabled teams to closely monitor athlete performance across all sessions and matches, facilitating a much deeper understanding of training methods that benefits athletes and coaches alike…
3. Using internal and external load to answer performance questions
A well-designed training programme will expose athletes to a range of stresses, all of which will induce fatigue and adaptations to that stress to differing degrees. Without an objective measure of the stress being imposed on the athlete, or their response to that stress, coaches and sports scientists are unable to quantify the true effectiveness of their interventions…
4. The key principles of an effective training programme
When designing a training programme, the primary aim is generally to optimise the performance of athletes by delivering loads that will encourage positive adaptations without placing them at an unnecessarily high risk of injury…
5. Structuring training programmes using periodisation
Although sports differ widely in terms of their physical, technical and tactical demands, the process by which training plans are constructed is underpinned by a set of common principles…
6. Mitigate injury risk using athlete monitoring technology
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…
7. Evaluating the quality of performance data
By its very nature, data in sport is inherently noisy. As technology evolves, and more data is generated, it is important that we quantify the boundaries of this noise (variability). Once the boundaries of noise are defined, we can then have increased confidence on judgement calls made when observations lie outside of these boundaries….