I was inspired to write a short piece after reading the following BBC article recently: ‘Data experts are becoming football’s best signings.’ The sentence that stands out to me is this one:
“Having access to people who can understand that data is critical.”
When we speak to clubs and organisations the issue facing analysis teams is not the amount of data they’re able to get access to or generate themselves, it’s how to apply and communicate the data to the coaches, athletes, and all other departments within their organisation that is of utmost importance.
Athletes and coaches across all sports are bombarded with information. If anything, they’re data-fatigued. They might be presented with tracking data, event data, video, instrumentation data, health data, sleep data, nutritional data, biometric data…the list goes on.
You can have 10 Laurie Shaw’s in your organisation but unless you’ve also got a Pep Guardiola and a Txiki Begiristain who give you the time and trust required to build your data infrastructure and make decisions that are data-informed, there would be no point. The organisation’s leadership needs to create an environment whereby a data-informed strategy becomes commonplace.
It’s how to get the right data in front of the right people at the right time.
There will always be “the next stat” or “the new tech” that supposedly gives you more information than you’ve had before and which unlocks the key to your organisation’s success – but will it be understood by the athletes and applied in the coaching effectively?
Another element that’s currently a hot topic amongst football analysts is just how accurate is the event and tracking data being provided by the big data companies.
We recently conducted an analysis of discrepancies between event data providers across one tournament. We also carried out our own match tagging to see if we could provide a more accurate version of events. The results were interesting.
Amongst the more objective events such as corners, fouls, throw-ins, and goal kicks, there was a difference of approximately 3% – the biggest difference was freekicks with 14.8%. Amongst the more subjective measures such as passes, crosses, interceptions, and tackles, the difference in one case (tackles) was as large as 82%…which was a full 1074 difference in actual number of events tagged. Even passes had 20% variation.
If you’re basing your feedback and strategy on these numbers, you need to know they are accurate, reliable, and reflect your operational definitions.