Become A Data Analyst For A Professional Football Team | Key Skills

  Dec 17, 2022

By India Today Web Desk: The key factors that determine whether a data analyst is good enough to do the job are often trivial, at least on the surface. Rational, logical thought process and unbiased drawing of conclusions are the two most important qualities a data analyst must possess.

Of course, decent coding skills and, perhaps more importantly, a good understanding of statistics are required but it becomes relevant only when accentuated by the aforementioned qualities.

Domain plays an important role and understanding it sufficiently is part of a data analyst/scientist’s job. Unless the domain understanding is adequate, even the right results can lead to erroneous business conclusions.

When it comes to football, it is no different. A data analyst working for a professional football team must know two things: how to analyse data, and football!

Yes, it is that simple really. Now let’s try to break this down further.


Football is a high-octane sport and the physiology of the players is of high importance. It is important to understand how the bodily parameters are correlated (or not) with performance and results.

The next challenge comes in understanding how to measure performance in football and for that, a decent understanding of the game and how it works is an absolute must.

There are finer indicators like one-to-one matchups and positional significances which also require a more than average understanding of the game. So, understanding the game and regularly following it is crucial. Otherwise, inferences will either be wrong or outdated.


In terms of data analysis skills, there is nothing out of the ordinary required for the job. Good logical reasoning, the knowledge to make the most meaningful charts and diagrams, and statistical know-how are all that are required.

Decent knowledge of the standard machine learning algorithms might also be handy more often than not.

Data is now captured in all possible ways, from all possible sources, and in every possible domain. Football is no exception.

There are individual player data, how they perform with/against each other data, and how they perform for/against every team data.

Moreover, there are one-to-one match-ups, strength and weakness data, in both absolute and relative sense.

There is more! But, in a nutshell, enough ingredients for an analyst to cook well!

So, the work of the data analyst and/or data scientist is now deemed very important. Decision-making is no longer done on the basis of the sixth sense and whims of certain individuals. It is almost always driven by data. And hence, the armoury of the data analyst must be filled with all relevant ‘weapons’.

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