Facilitating Sports success with Data Science & Analytics.

If you watched the 2020 NBA games that were played in the Orlando Bubble then you are probably rolling your eyes. And I would agree with you except there is a way both traditional basketball & sports science can marry without compromising any one of the two.

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Image source: Google search

The  who as I speak were booted out in the second round of the western conference finals long after trading their starting big Clint Capela were one of the teams that fully embraced sports science, other teams like the  behind enthusiastic data scientist & former basketball player  (A Doctor of Philosophy Mathematical Sciences btw).

Videos like  as well as ’s  can help give a quick dive into the world of sports science.

Now its as I mentioned earlier most  fans will dismiss sports science because not only were the  bested by the  (Who by the way beat them using their own small-ball system), the team also lost their GM  a big fan of sports science after he stepped down recently.

But hear me out.

The team had its success until things started going south. My guess is they relied more on the data insights and totally ignored the intuition of the traditional feel for the game which can be attributed to experience.

Both Sports science and traditional sports style can flourish alongside each other if not better each other. The various challenges faced by most organisations or individual entities come about if sports science is relied on completely. The trick as far back as the old days is to drink just about enough alcohol to enjoy one’s self without taking too much to make a fool of one’s self.

Now players like  (who has one of the best IQs in the game on top of his athletic abilities and skill), retired  &  are some of the few players who found success in sports sciences as basketball players. In the (MBL)where the whole concept of using analytics to find success in sports probably started, is  who called his decision to sign with the Mets instead of going to Stanford as the “only decision he would ever make in his life about money.” eventually got a job with the  as an advance scout then Assistant GM, later GM and then Executive Vice President.

The Book;  by  depicts Billy Beane as general manager of MLB’s Oakland A’s trying to win games against difficult odds whereas the movie ; in a slight spin tells a story of how a general manager challenged the system and defied conventional wisdom when he is forced to rebuild his small-market team on a limited budget.

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Micheal Lewis Book; Moneyball. Image source: Google Search.

Beane did this with the help of a young, number-crunching, Yale-educated economist (Jonah Hill) by developing a roster of misfits who went on to win 20 consecutive games between August 13 and September 4, 2002, and along the way, forever changes the way the game is played.

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Brad Pitt playing GM Billy Beane (left) and Jonah Hill playing Ast.GM Peter Brand(Right) in Movie Moneyball. Image source: Google Search.

To say data science is not important in sports is to say traditional winning of sports games in this day and age can succeed without Data science. Today you would be handicapped in sports without analytical insights just as a business without technology would be outcompeted by one that utilizes the full benefits of technology.

One needs the other, the mistake on the other hand is relying on one over the other or replacing one for the other. Basketball shouldn’t replace how traditional basketball is played but rather boost how it can be played better and more efficiently.

Combining analytics with traditional opened minded basketball intuitive coaches, GMs, scouts, & agents to mention but a few who have a good feel of the game can be the recipe for long success.

Sports science, for example, can help eliminate unnecessary spending, movements and decisions for a professional sports organisation or even a sports business. I realised how inefficient my favourite athletes are while filling up the stat sheet when I started taking a keen interest in sports science, which also showed me all my failings as an athlete when I thought I was excelling.

Recently started learning data science on the side as part of my post-basketball playing days to transition to basketball management roles with the help of sports science, player development coaching & training among other avenues.

My love for the game and expertise in Informational technology along with a few leadership responsibilities should be a big help in this endeavour. I do hope to establish a thriving business in the data science space with sports science as one piece of the big pie.

I would love to get your feedback and insights so feel free to reach out for a coffee or so while at it.


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