Teams are collecting more sophisticated data through players wearables, sleep monitors, and even saliva. These new methods help decide when to rest a player to prevent injuries before they happen.

University of Michigan - Ann Arbor

There is clear evidence that the NBA is taking advantage of Data Science wide range of uses. Such as designing winning strategies, predicting and avoiding player injuries, and scouting

Data analytics in the NBA

The NBA has added a large amount of cameras on the court to help accurately collect granular data on player movements. This in turn helps train more sophisticated machine learning models than they were able to use in the past. Coaches can now make more specific game plans based on statistics such as defensive matchups or offensive plays. Using the player movement data and models they can point out vulnerabilities in opposing teams using math.

Designing winning strategies in NBA

Predicting and avoiding player injury

Drafting is extremely important in the NBA so teams leverage analytics to minimize the risk of their pick. They use advanced stats and videos to evaluate the up side versus risk of a potential player.

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