This blog was written to fulfill a promise made to Ravi (@Scribblr_42) in a tweet back in February to explain why I strongly disagreed with a statement by Dean Oliver (@DeanO_Lytics) at the Opta Forum (http://bit.ly/1Uw5DCO) last February, and that Ravi ‘liked’.
During his presentation Dean Oliver displayed the following slide where the first point (as one can see from the pic below): “Know the sport first, analytics second“
What Dean meant by this statement – as he later explained – was that a deep knowledge of a sport (one that is normally acquired by working within a club as a Performance Analyst) is more important that a knowledge of analytics. I strongly objected to this statement and later posted a tweet of my disapproval.
Of course, anyone involved professionally in Performance Analysis of any sport, has to ‘know’ the sport. But this deep knowledge is no longer of primary importance, not if one has an analytics role in a club. Analytics is about analysing data – these days, lots of data (big data?). Therefore the primary knowledge required for this task is knowledge and experience of advanced analytic techniques and tools. Without this knowledge and experience is not possible for anyone to analyse data efficiently and effectively. Any data! Of course, such person must also ‘know’ the sport where the data comes from. But, thanks to years of media coverage, TV in particular, any intelligent person that follows a particular sport has gained such knowledge. Not, of course, to the level that Dan implies, but enough to do his job.
It should be clear that I am not advocating that data analyst/scientist should replace Performance Analysts (PAs.) Only that the latter should stop pretending that in today data-rich sports environment are capable to fully exploit the large amount of data available to them. They are not! They are not qualified for this task, nor, I dare say, have the aptitude. Video analysis has been for years their main tool and focus, not statistics. Sadly, this is the main reason why analytics has failed to gain a foothold in many team sports, football in particular.
However, I am not suggesting, , that clubs should get rid of their PAs, but only that they should take a back seat when data analysis is concerned. At a recent ISPAS conference in Carlow – http://www.itcarlow.ie/research/conferences-workshops/ispas-2016-workshop.htm- I put forward the suggestion that clubs should employ a Performance Data Analyst (PDA), whose sole concern be of leading the data analysis of the sport, as well as helping PAs improve their data analysis skills. Unlike PAs, the PDA does not need a deep knowledge of the sport to do his job well. He also does not spend time on the pitch with players, but interacts only with PAs and other coaching staff including the head coach. This is another reason why PDA does not need the communication skills of a PA – in contrast to another important point that Dean makes in the same slide.
Sadly, I don’t think that my suggestion (which, I should mention, was greeted with contempt by prof. Hughes at this conference) will be taken up by sport clubs any time soon. Aside from the hostility of PAs to any challenge to their role of ‘analysts’, there aren’t many data analysts/scientist to go round. And even the few that are passionate for a sport are unlikely to accept the miserly salary they are likely to be offered by clubs when many business companies are prepared to pay them lots more. This point is eloquently made by Ben Alamar last year in an article of which I reprinted a pragraph in one of my tweets.
— Johan (@soccerlogic) July 25, 2015
(Note: with the acronym PAs I am also referring in general to any member of the coaching staff who is involved in data analysis)