lead to teams scoring five to 15 more points per game.Researchers analyzed player metrics and material that were accrued from an undisclosed NBA team through a stop-motion camera during many of its games this season.
The science squad was then able to project precise positioning that guaranteed better scoring outcomes for individual players — sometimes by moving mere inches.“Every 40 milliseconds, we know with … a very high degree of accuracy, where every player is and where the ball is located,” Boris Barron, a doctoral physics student on the project, told The Post. “[Our work] has the potential to be a game changer for basketball … This is taking ‘Moneyball’ to the extreme.”Although the Big Red missed the big dance, Barron — along with physics professor Tomás Arias and peer Nathan Sitaraman — have been on their toes these past few weeks by applying density-functional fluctuation theory (DFFT) to introduce “more kind of advanced quantitative analysis” to the game.In quite plain terms, DFFT looks at fluctuations caused by certain events that either separated or brought together entities within a group.
Previous research using the theory observed how fruit fly clusters adapted to heat being introduced to their environment and separately, was used to predict crowd behavior among people.Barron and company are using DFFT to break down the spatial interactions of where players like to be and how players interact with one another on the court. “Looking back at a game, I can see how this can help players improve,” Barron said. “The improvements can be in the [team total] range of five points in 100.
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