A basketball fanatic and a math whiz want to do for basketball what Bill James and sabermetrics did for baseball, and their innovative way of parsing data could revolutionize game analysis, providing coaches with new insights while making the game more fun to watch.
Sabermetrics, for those who haven’t seen Moneyball, is the objective analysis of baseball using game stats. Billy Beane used it to revolutionize the Oakland A’s. Compared to baseball, though, basketball is much more dynamic, and ball movement becomes a key variable in success. Passing is one of the fundamentals of hoops, and in the upper ranks of the sport, turnovers — often the result of wayward passes — contribute to ticks in the win-loss column. Fast, agile passing can make or break a team.
That’s why sabermetrics might not tell the entire story about what happens on the court. Researchers at Arizona State University, led by life science professor and basketball fan Jennifer Fewell and math professor Dieter Armbruster found an ideal model to explain the results of the 2010 NBA playoffs by simply keeping their eye on the ball. Their work opens the door to an entirely new line of sports analysis, from game-tape breakdown to highlight reels and augmented-reality visualizations.