How Can Movement Analytics Predict NBA Player Performance?

NBA teams and analysts have used Player Efficiency Rating (PER) for many years to create a more nuanced picture of player performance, mostly for two reasons: 1) because PER accounts for positive and negative contributions, and 2) the metric can be applied to specific scenarios, such as results against certain opponents, first-half and second-half performance splits, and so on.

But no matter how much deeper PER delves than the traditional NBA counting stats, it can’t pinpoint the most granular performance factors – those that help explain why a player is a better defender in the second half, for instance, or why that player had a very poor second half last night.

Sportlight’s LiDAR technology already has demonstrated that capability in soccer’s English Premier League, because it produces hyper-accurate data that details the player’s actual physical performance. And the technology has the potential to deliver similar results in the NBA and other basketball leagues. For example, imagine a system that precisely measures jump height on a player’s 3-point attempts to find correlations among fatigue, time of game and accuracy – an analysis that’s much harder if jump height is being “eyeballed” by a coach in real time or using game film. This sort of granular performance evaluation is within LiDAR’s scope.

For franchises, the genius of player performance analysis is in determining what to analyze – how to arrive at insights, rather than just raw data collection. The inability to gather certain data points has, until recently, hampered the growth of new insights. An assistant coach might have a hunch that a jump-shooter gets off his shot quickest when he receives a pass at chin-height, or toward his shooting-hand side, for instance. But without the space-and-time measuring precision of LiDAR technology, the coach previously had been able only to suspect, not prove.

Even in the heat of a game, LiDAR can provide hard data – like reaction times to certain situations – that could tip off a coach to player inattention, fatigue or susceptibility to injury. These are insights that have value to an organization all the way from up in the front office to down on the floor at crunch time.

Think of it: A coach can use these insights to stagger the player’s minutes accordingly, resting him in a way to optimize performance. A trainer could work with the player to strengthen specific weaknesses based on those insights. A front office executive could more accurately measure individual value and more intelligently build a roster based on a deeper understanding of that player’s profile.

No game on earth combines so many large and swift athletes in such a small playing space as the NBA does, or so strenuously challenges the eyes of coaches and trainers to discern what’s going on in real time. Technology that allows for the measurement and analysis of all the tiny (but significant) movements and interactions on the floor can be a literal game-changer. Now franchises and their personnel have the tools to make it a reality.

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