Data Science in Sports: Are you doing it right?


Collecting data is good but putting it into action is even better.

Modern organizations have an overwhelming amount of information at their fingertips yet only a fraction of that information is used to inform strategic decisions. 

  • Which players do you want on your team?
  • How do you develop your players?
  • What tactics will win the next game?
  • Which stars need a rest and when?

It’s a data accessibility, data visualization and predictive analytics thing.

Good data science is shared, actionable, and consistent

  • Is all of your data sitting in one “single source of truth”? 
  • Is it at least partially accessible by all decision-makers? 
  • What happens when you try to ask questions of the data? 
  • Is it user-friendly or are you relying on another human to facilitate? 

Remember, it’s human AND machine, not human VS machine.

Modern tech stacks don’t “break” 

  • How much time do you have left for “the fun stuff” each day? 
  • How much gets burned connecting infrastructural forms just to get basic functionality?
  • How fast are you able to action the data? 

When daily processes become automated and the barriers of entry to data queries get reduced, space opens up to connect the dots–and that’s where the fun begins.



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