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Offensive and Defensive Ratings (Net Rating) - What Do They Tell Us?

In the world of advanced basketball analytics, offensive and defensive ratings are used as a way to track and compare how an individual player affects his or her team's performance. At a basic level, the offensive rating of a player represents how many points a team scores when that player is on the court and the defensive rating for how many points they allow. The two combined (offense-defense) are referred to as the net rating often times written as NETRTG.



Net rating is the offensive rating minus the defensive rating, but simply put it can be defined as how much better or worse the team is when a specific player is on the court. These ratings are usually on a per X possessions basis. Using possessions rather than minutes eliminates the effects of a team that plays very fast or very slow.

For example, we can see in this image from the NBA Stats page that Steph Curry led the NBA in net rating. In the NBA, these metrics are almost always on a per 100 possessions basis so we can see from the report on the right that, for every 100 possessions played by the Warriors when Curry is on the floor, they scored an average of 119 points and allowed 105 resulting in a net rating of ~14 for Curry.






Offensive, defensive and net ratings can also be calculated for the team as whole (to provide comparisons to other teams), at the 5 player lineup level (for comparison with other lineups), or at the player combination level. As seen on the left, Pivot's AI-powered analytics engine is able to process and display all two player combinations and their associated ratings. This shows how Duke performed when both RJ Barrett and Zion Williamson were on the floor. If you'd like to explore this on your own, along with our many other analysis tools, you can do so here.


Synergy

As seen here, we have also included a metric called Synergy. This number is based on the individual net ratings as well as the two player combination net ratings. For each two player combination, we measure the average between their respective individual ratings and their combined rating. In this example, RJ Barrett as an individual net rating of 19.3 and Zion has one of 23.2. When they play together, they have a joint net rating of 25.1

25.1 - 19.3 = 5.8 (Two Player Rating - RJ Barrett Rating)
25.1 - 23.2 = 1.9 (Two Player Rating - Zion Williamson Rating)
(5.8 + 1.9) / 2 = 3.8 (Average of the previous two results)

At Pivot, our focus has been on understanding the team impact of a player or players rather than his or her individual statistical prowess. Whether in our single player on/off data, the player combination matrix or the lineup explorer, Pivot Analysis provides players and coaches the ability to measure the effects of each individual and player combination on the whole team's performance. In the coming months, we will be adding functionality enabling the user to measure and analyze rebounds, turnovers, and shooting percentages (four factors and more) in the same fashion. The Pivot Analysis application will tell you when Player X is on the floor how many points a team scores, how often they turn the ball over, how well they shoot threes, how often they shoot free throws, and how well they crash the offensive boards.








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