There’s that moment The Matrix, where Keanu Reeves’ character Neo realises his destiny, and can “see” The Matrix. Neo becomes The One. Instead of seeing green symbols cascading down a screen, Neo can see the shapes they form. Suddenly everything happens in slow motion, he can fight with ease and become more powerful from the challenges he faces.

In professional sport, as in other industries, there has been a proliferation of data collection that we are promised will help solve many problems for us. There is a problem though, numbers are seductive. They provide the illusion of certainty in an uncertain world and a measure against which we can seemingly track progress. The danger comes when we begin to rely solely on these numbers and ignore the context from which they came.

Charles Goodhart is a British Economist who in 1975 wrote an article on British monetary policy in which he expressed the following…

“Any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes.

This has become known as Goodhart’s law and is more plainly expressed as…

When a measure becomes a target, it ceases to be a good measure

When the number we use as a measure becomes the target instead of an incidental outcome, we begin to change our behaviour to achieve the target. In professional sports, around 15 years ago, GPS technology entered the mainstream and gave us a measure of how much distance athletes were covering at different speeds in their sports. Fast forward to today and many of these external load measures that we couldn’t previously capture have become the targets by which we measure performance, instead of seeing them as an incidental output of performance as a whole.

If we continue to use them as a proxy for performance, we will narrow our focus on them to the detriment of other performance factors. If players then realise that it is on these numbers they are being judged, they will try to game the system, and they cease to become a good measure. We are now affecting performance as we have created an observer effect.

Many of the sports scientists now in team sports have only ever worked in an environment where the utilisation of GPS technology is the norm and treat the numbers as the gospel truth, sometimes at the detriment of what they might be able to see with their eyes.

This reminds of a time when a player posted high game physical outputs for two games over consecutive weekends, leading into a week with 3 games in 6 days. The player had a history of injury and plenty of discussion was had around whether the player should be rotated for one of the three games. When we spoke to the coaches one of them asked why the player was suddenly less robust than 6 weeks previously when they had completed a similar pattern of games, shortly after returning from their last period out. I was struck at that moment that the coach was not only seeing the numbers but was seeing the pattern and shape of the weeks and using their learned experience to see how the player fitted within that.

This kind of reasoning takes expertise from experience built up in the environment, often through many years of trial and error, and learning. If all the coach, or sport scientist (or any other practitioner) ever looked at was GPS outputs, without understanding the context that created those numbers, the internal effect they created within the body (through heart rate or blood lactate monitoring), or without applying some existing tacit knowledge, they are failing to see as much of the picture as they could.

We must constantly be taking the data we collect, turning it into digestible information and reflecting on what it shows us, in relation to our existing knowledge base. This will create further questions which to answer, we will have to collect more data. The quicker we can cycle through the data-Information-knowledge loop, the faster we will learn.

The famous CEO of Jack Welch made General Electric the world’s most valuable company whilst at the helm. He understood the importance of this process and was quoted as saying…

“An organization’s ability to learn, and translate that learning into action rapidly, is the ultimate competitive advantage.”

Once we have passed through this loop enough times, we no longer look back at what has happened, we begin to recognise shapes and patterns and see forwards, we attain wisdom.

Good players have these skills. The ability to recall the positions of chess pieces on a board displayed for only a few seconds discriminates between the level of chess player, with Grandmasters doing significantly better than masters.

I am no football player, and when I watch the game, I track the players on the pitch as individuals, I do not see the shapes that they are making with their teammates and the opposition. I also, more importantly perhaps, don’t see the space that these fluctuating shapes create. Good players and coaches can recognise these shapes, allowing them to act and reposition before they need to, increasing their efficiency.

Our ability to see shapes instead of numbers then is related with efficiency and expertise.

Focussing just on numbers makes us reductive, creates opportunities for us to be gamed and makes us more fragile. Focussing on shapes however provides context around the numbers and is more indicative of performance as a whole, however this takes practice, expertise and experience.

Think about it this way. When you are driving, you adjust you speed and position based on all of the sensory information you are taking in through your eyes, ears, hands and the rest of your body. What you don’t do is drive just watching the numbers on the dashboard, this would be both foolish and dangerous. Instead, those numbers are there as a reference for you to look at inform what you are seeing and feeling. Use data in this way and you will have better success, just stare at the dashboard and you are sure to crash.

As Neo learns and appreciates The Matrix, he is better able to bend it to his will, and use the environment to his advantage when he sees the context of the matrix within that environment.

Further thinking

  1. How are you applying context to numbers?
  2. How are you ensuring your organisation is data informed as opposed to data driven?
  3. Do you ever get fixated or caught up on a KPI? Why?
  4. If you have a regular target that you don’t hit, how do you feel?
  5. How can you ensure that you and your team are moving as quickly as possible through the Data-information-knowledge loop?