Last updated on March 22nd, 2024 at 07:08 am
Sports have seen their fair share of analysts and pundits ever since the first game was played. Traditionally, the analysis made by these pundits and analysts is based on hunches rather than concrete mathematical and statistical foundations. Even if they tried to factor in the statistics, there is no way that a human brain would calculate the entire complex, behind the scene calculation, which goes into a typical mathematical or statistical model.
So, it was thought that data analytics in the sector of sports had reached saturation. It all changed with Machine Learning and Artificial Intelligence.
In case you are not aware, machine learning and artificial intelligence are the fields that employ complex statistical models with a colossal amount of data to analyze the data, derive insights, and make predictions from it. So, when these advanced modeling techniques are fed the data generated from sports, we derive more accurate results, wisdom, and forecasts than all the pundits and legacy sports analysts.
Let us now see precisely what makes data analysis so lucrative in this sector.
How is sports analytics changing the paradigm?
There are only two ways in which sports analysis is being used in today’s paradigm. One is when the sports teams ask for data analytics, and the second is when it is used for sports betting.
The first step of the Data Analytics course in sports involves mining various data like stats of any individual player, match conditions, and the teams’ recent performances. Then, all the information is passed down to Data Analysts.
It is their job to run machine learning models on this data to generate new insights. Now, these insights could be as simple as whether the team would win the next match or not.
To something more specific like, will Ronaldo be able to score his third goal with his left foot in the 69th minute?
Analytics is not limited to in-game events. By analysis of the data generated by the fans, the team would be able to cater to their needs better and thus improve their following. The sports team can also use data analysis to enhance merch sales.
How are big teams using data analytics?
While there are many examples available out there, we choose the ones from football.
Manchester United: We all have seen the Red Devils wear the AON branded shirts for a long time now. ManU has been using AON’s data analysis to stay ahead of the curve.
Real Madrid: This might come as a surprise to many, but Real Madrid has partnered with Microsoft (the Azure platform owner) to provide the Madridistas with all the analytics they need. They use Microsoft services to plan out the training, performance, and even fitness regimes of their players.
Conclusion:
There are a lot of apparent benefits when it comes to using data analytics training in the paradigm of sports. We have barely touched the surface here. However, we hope that we were able to provide you with some new information about data analysis in sports today.
