AI Case Study
Brooklyn Dynamics researching an athlete scouting application based on machine learning of historic data
Brooklyn Dynamics has been building data sets of individual performance - their "data CV" - to support player measurement. This builds on the approach to discovering undervalued players popularised in 'Moneyball'.
Consumer Goods And Services
Entertainment And Sports
"The proprietary algorithms are based on a decade of elite athlete data and successes. Clients include 5 MLB World Series champions, NFL teams and world class events, such as The Tour de France and F1 racing. Brooklyn Dynamics masters predictive analytics and maintains a 97% accuracy rating in MLB and NFL drafts, forecasting player vs player comparisons, salary cap modeling, and live in-game scenarios. "
Using data to discover undervalued players was popularised by the book and film 'Moneyball'.
"The issue is, under the current environment you can not monitor all players, across all leagues as it's not physically or financially possible. Platforms that collect data, standardize and create uniformity in the collection allow players to be evaluated 24/7. 'The premise [Boston Dynamics] work under is that we are creating the data CV of the athletes for the entire life cycle. Take away any human bias…you evaluate a player and their data, you don't see race, nationality or other factors that often cloud judgement.'"
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