Is data analytics the future of sports coaching?
Data analytics is big business across both the business and sporting worlds.
The 2011 film Moneyball highlighted this trend, resulting in a great deal of speculation about the idea that technology may eventually replace sports managers. The film depicted the true story of Baseball manager Bill Beane. Faced with a tight budget, Beane reinvented his team by outsmarting the richer ball clubs. Joining forces with Ivy League graduate Peter Brand, Beane recruited bargain-bin players whom the scouts had labelled as flawed but had game-winning potential according to Brand’s computer generated algorithms.
The approach was based on two core concepts – firstly, computers are able to collate and analyse much more data than we could possibly analyse as humans, which allows them to better predict future performance.
And secondly, computers are not biased by emotions, subjectivity or the many other biases humans suffer from, so their decisions are bound to be more rational than ours.
In addition, at the core of high-performance coaching is a desire to identify, analyse and control variables that affect athlete performance.
Therefore, an approach adopted by many coaches today is that of reductionism, which is an attempt to understand the functioning of the whole through an analysis of its individual parts.
This approach provides a mechanistic guide, viewing behaviour as measurable, causally derived and thus controllable. This approach fits perfectly with the use of computers, data and analytics.
In theory, the reasoning and data work reliably, every time. In a casino, this is true. We know the odds, the payoff if we win, the rules about what is allowed and when bets are paid. So, the data works, we can make better decisions.
However, human performance is far from sequential and straight forward. And social encounters like coaching, consisting of non-linear relationships, are even more complex, defying such unproblematic representations. In sport we don’t know the odds (similar situations can end up very different), we don’t know what the payoff will be (it’s non-linear).
We know the “rules” and when the game “ends”, but there are multiple “actors” in the scenario, who do not act in completely rational ways, and whose actions affect the outcome in interlinked ways (it’s a complex system).
There are multiple cause-effect links too complex to calculate. Sports analytics, computer-generated algorithms, and big data can certainly improve human decision-making in the field of competitive sports, but so long as the athletes are human, technology alone will not improve their performance.
Data can help us make better predictions, but it will not make people more predictable than they already are.
So, what is the future of sports coaching?
Conventional organizational studies have tended to define sports as a set of highly heterogeneous physical, mental and cognitive activities within which it is difficult, if not impossible, to find universal pedagogies for controlling those activities.
However, adopting a whole system approach, and exploring the concepts of control, regulation and selforganization, it is possible for coaches, managers and psychologists to develop a better understanding of how a complex system works, and therefore, to more successfully manage and influence a team’s performance.
In the future, coaches will begin far more to challenge the simplistic cause-effect assumptions, the self- serving beliefs, the questionable rationales. Increasingly, they will question the relevance of their own experience, challenge their own biases and assumptions, and depart from automatic routines of thought.
To accommodate change, coaches will need to grow. They’ll still need all the current skills such as building rapport (the relationship seems to be the biggest variable in coaching).
They’ll still need to question and listen effectively, they’ll still need professional, interpersonal and intrapersonal knowledge, and to do plenty of other things. But they’ll also have to learn the reality that we can’t keep track of all the cause-effect links, the exact details of every last variable and that would still be true even if we knew what they were, which we don’t.
We can’t deal with that, it’s too complex, too scary. The result is that we simplify.
We actually have no idea why what we have done worked, or even, in many cases, whether it has worked.
But we like to look back and convince ourselves of the cause and effect relationships that we think are responsible for the outcome, regardless of whether they were simple problems to start with.
In essence, coaches will have to learn the reality of uncertainty, chaos and complexity, the dangers of simplified thinking, and ultimately, change their ways to work and lead in complexity.
Guiding Principles for working in Complex Systems Before you can work with complex systems to effect change, you need a basic familiarity with systems thinking. This means shifting from seeing things as parts in isolation to seeing things as part of an interconnected web.
Working with complex systems isn’t about coming up with a plan and implementing it upon the system. Imagine trying to plan each move of a hockey game or trying to plan what your child’s personality will be like when they grow up. It wouldn’t work!
As Dave Snowden (developer of the Cynefin framework) writes, trying to “impose order in a complex context will fail, but those who set the stage, step back a bit, allow patterns to emerge, and determine which ones are desirable will succeed.”
• Establish a general sense of direction (can be defined by an aspiration/purpose statement)
• To achieve change, we need to allow self-organisation. That won’t occur with tight constraints (many top-down rules). Try sharing the process in such a way as to empower athletes. But the converse is also true. Self-organisation won’t occur with zero constraints. You need to provide some minimum guidelines, or boundaries within which athletes have autonomy to act. This could be in a tactical sense, or even when considering their whole program.
• When in the complex zone, run a series of probes or experiments to see how the ‘system’ responds – amplify the stuff that works, and shut down elements that are not useful.
• Monitor the influence of those actions in changing the patterns/beliefs/behaviours – is the system evolving in the general direction established with your purpose statement? Are there unexpected patterns emerging (good or bad)?
• Adapt actions to amplify / dampen / stabilise patterns as required.
To learn and adapt effectively will largely revolve around the willingness/freedom to act, getting the monitoring methods right (feedback loops) and, at an organisational level, having the humility to:
• recognise you cannot predict with any precision when/how the system will shift
• accept you are not in control of the system, you are a part of it
• invite others to take the lead and be prepared to ‘follow’ at appropriate time
Sean Douglas is the National Coach Education Manager for Football Federation Australia
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