Allan Macdonald

Words: 1100

Time to Read: 8 minutes

Introduction

Performance directors, pathway managers, coaches and practitioners operating in performance sport must recognise and understand the nature of systems influencing the outcomes of their decisions. This article discusses the concepts of complicated and complex adaptive systems, providing a framework to identify and differentiate between them. This understanding is pivotal in developing decision-making strategies for the unique challenges and opportunities presented in high-performance sports environments.

Understanding Complicated Systems

A complicated system is characterised by its layers and intricacies, yet it operates under a set of predictable and controllable rules. In complicated systems, the components and their interactions are well-defined, and outcomes are largely predictable – often using mathematical equations. For instance, consider the operation of a car. It is a complicated system involving various components like the engine, brakes, electrical systems, and cooling systems. These components, when expertly combined and maintained, work together in a predictable manner to ensure the vehicle operates efficiently and safely. Viewing each of these components of the car in isolation, and understanding their function, allows us to understand their impact on the car as a whole. For example, if the power output of the engine is increased, the changes in acceleration, maximum velocity and momentum can be calculated and any required changes in the braking system can be precisely quantified. Consequently, changing a single component of the car gives a predictable and measurable outcome. 

Criteria for Identifying Complicated Systems:

• Predictability: The outcomes in a complicated system can be anticipated, and often mathematically quantified, based on the input and processes involved.
• Linear Interactions: The relationships between different components are usually linear and additive.
• Experiential Knowledge: These systems often require specialised knowledge for their design and management.
• Standardisation: Procedures and protocols can be standardised, replicated, and scaled with consistent results.

Understanding Complex Adaptive Systems

In contrast, a complex adaptive system is dynamic and less predictable. These systems are marked by their capacity to adapt and evolve in response to changing conditions. In performance sport, the athlete, the coach, and athlete-coach relationships are just three examples demonstrating complex adaptive systems. The interactions between athletes, coaches, and support staff, influenced by external factors like a single exercise stress, training session stress, competition stress, life stress create a system that is continually adapting and evolving. 

When dividing a complex adaptive system into individual components, these components may appear to have relatively simple to understand, highly predictable functions. However, in a complex adaptive system, changing one individual component, or condition of the system can have large and unpredictable effects on the entire system.

Criteria for Identifying Complex Adaptive Systems

• Adaptability: Complex adaptive systems can change and reorganise in response to internal or external stimuli.
• Non-linear Interactions: Relationships between components are non-linear, meaning small changes can have large impacts.
• Emergence: New properties or behaviors emerge that are not predictable from the individual components alone.
• Feedback Loops: These systems have feedback mechanisms that can amplify or dampen changes within the system.

The Predictable becomes Unpredictable

While complicated systems are predictable and controllable, complex systems are adaptive, thriving on change and evolution. We like to view the world deterministically, through constructing cause-and-effect relationships, and this helps us feel in control of outcomes. In performance sports the, potentially unnerving, reality is we encounter complex systems that challenge our linear, deterministic, cause-and-effect worldview – but what other options do we have?

As a thought experiment, consider a common scenario in rugby union: you are a head coach and you need to improve your team’s defence performance. After discussions with the other coaches and analysts, you reasonably conclude you need to increase defensive line speed. You tell the strength and conditioning staff you need to improve acceleration, and tell the rugby coaches to drill line speed “connection” on the field.

The strength and conditioning staff, using linear, deterministic, cause-and-effect reasoning, use Newtonian Laws of motion as the basis of their program design: acceleration [m/s^-2] = force [N] / mass [kg]. To increase acceleration, they must increase force capacity, decrease body mass, or a combination of both. The strength and conditioning staff have experience and data, and conclude the programme they design will “almost certainly” and “very likely” improve the athletes’ acceleration. The rugby coaches work with the analyst to design pitched-based drills to improve the players’ defensive line connection. Acceleration does improve, defensive line connection improves, defensive line speed improves, and defense match performance improves – success!

For a few matches.

A complex adaptive system adapts, and behaviours emerge. The opposition analysts have access to all match footage for every match and they flag to their coaches how great the defensive line speed is. The opposition adapts to the new line speed with small kicks in behind the defence line. Defence performance gets worse for the next match. Maybe it was predictable that opposition attacks would adapt with those tactics, and you decide to leave the scrum half to cover these short kicks for the next match. One of your coaches flags “that’s really predictable, teams will have watched our last match and know we’ll do that from now on – maybe we should try something else”. What decision will you make?

The predictable has become less predictable – and every decision from now layers unpredictability and uncertainty on top of increasing unpredictability and uncertainty.

You reflect, as all good coaches do: the strength and conditioning staff did a “good job”, and as predicted, they improved acceleration performance using their deterministic approach and improved each individual player’s line speed. The coaching staff did a “good job” as they predicted, they designed drills and through cause-and-effect this improved defensive line connection. It is undeniable many of the individual components of the defensive system, as predicted, improved. Yet, the aim was to improve defence performance and match performance. As more matches were played, the more opposition teams adapted with new attacking plays emerging. Performance has ultimately decreased. You reflect: “was prioritising increasing defensive line speed, instead of focusing on other options, a good decision?”.

Final Thoughts

In performance sport, recognising whether a system is complicated or complex is crucial for effective decision-making. Complicated systems, with their predictability and linearity, give us a sense of control over the eventual outcomes of our decision. On the other hand, complex adaptive systems, characterised by their adaptability and emergent behaviours, are central in all areas, from training stimuli interactions, to match tactics, to pathway strategy development. Understanding these differences between complicated and complex adaptive systems enables performance directors, pathway managers, coaches, and practitioners to apply the appropriate decision-making approaches and strategies to manage, and thrive under complexity and uncertainty.