Data Science and Sports Rating!

Any sports fan understands the importance of sports rating and how it impacts different aspects like the selection process. However, have you ever imagined how the modern rating process works or the rating of a given player changes week on week? The entire rating system has been developed by data scientists after decades of data crunching, analyzing, and visualizing. Today Data Science has changed the way professional players of a given game are rated and the ratings are astonishingly accurate. Based on those ratings, team managements make hiring and firing decisions coaches draft up the playing eleven, and many more crucial decisions are taken.

If you are a sports fan and want to work for your favorite team or sports and create an impact then you must enroll in a data scientist course in Delhi, Noida, Bangalore, or any other major city in India. Once you acquire the skills required for a data scientist role, you can easily apply for open positions available at sports analytics companies like Sportsradar, Whoop, TraceUp, etc. Interestingly even major sports management teams and managing authorities directly hire data scientists and such opportunities are always open.

Let us now take a look at how Data Science is Changing the Game!

Data Ingestion
Data scientists employ a large number of techniques to acquire and accumulate data from multiple sources. For example, in football, a large number of data is collected through GPS devices that are fitted to the training vests of players. The small but useful devices keep track of player movements, distance covered, energy level, reaction time, and a lot of other data points. The data is uploaded to the data collection system on a real-time basis and automated ML algorithms start labeling and crunching them instantly.
When it comes to sports there is a lot of data to collect and the volume is both enormous and complex. For instance, in formula 1 real-time data of the racing car’s engine performance is generated and collected at high velocity and in hefty volumes. Data scientists ingest such data through skillfully crafted data pipelines and prepare it in such a way that Data analysis is easy and fast. Data is also accumulated through live streams of games, simulations, IoT devices, match reports, and manual surveys. We are living in an age where no data can be ignored and Data Scientists employ Big Data strategies to carefully collect all the data and manage them in Data lakes.

Data Analytics

The next step to data ingestion is data analytics. It is the task of data scientists to use a skill such as Machine Learning and Deep Learning to skillfully create automated systems capable of doing data analytics upon ingested data. Automation is an important aspect of data analytics as hefty and complex data volumes cannot be manually analyzed and it is only Data Scientists and Data Analysts who can do that. Data Science teams working for a popular team deploy multiple automated systems to extrapolate data which offers valuable insights and can be visualized for managers and coaches to take very important decisions. For instance, teams competing in the English Premier League have to play more than 50 games per season. Thus, understanding and predicting which players can play the entire season without fatigue and players who are needed to be replaced from time to time for preserving their energy level are important. With insights arrived after Data Analytics, managers can predict accurately a player’s energy level throughout the season and thus can manage team performance more efficiently. Interesting Data Analytics also helps managers to devise strategies that can fetch an important win for the team. For instance, in the Indian Premier League edition of 2019, Mumbai Indians successfully defeated Chennai Super Kings by defending a meager total of 149. We the audience know the contribution of the entire team and especially the excellent bowling performance of Jasprit Bumrah. However, in the background, the Mumbai Indians analytics team provided the captain and coach with accurate data insights about what kind of bowling works in the slog overs and which bowlers tend to be more effective in the starting overs. Thus, data analytics had a good hand in influencing decisions like whom to give the ball during the death overs!

Are you a sports enthusiast?

If you are a sports enthusiast and want to make a career in sports then Data Science can be a great choice. You can opt for the Data Science 360 course offered by the Analytix Labs and get trained in data science skills. Since there are a lot of job opportunities in the field, you can easily make a career in Sports Analytics!

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