In a recent post, we took a look at identifying how a team distributes the ball on offense with a deep dive look at the Brooklyn Nets. In that article we identified how to construct a community; the sets of likely passes for scores between players. This also included two-pass assists (hockey assists) where it…
In a recent podcast by Sixers Science, an analytic called the Kidd Score was unveiled. The goal of the analytic is to identify players who are great at two ancillary tasks: assists and rebounds. These two components are part of the big three statistical categories that make up the traditional triple double: points, rebounds, assists.…
In possession models and analytics such as RAPM, the ability to count free throws is crucial. Any miscalculation in computing free throws can result in an unintended dire consequence. In the case of a possession, a team’s possession may be calculated with bias and therefore comparing two teams using per possession stats becomes a flawed…
A common question about identifying player tendencies on offense is to ask “how likely is this player to receive the ball during a possession?” This methodology can be aided by the quantity touches. However, a player can touch the ball with what I like to term as an empty touch. These are touches that have…
The calculation for Offensive Rating, another fruitful Dean Oliver metric, is simple: compute the number of points produced when a player is in the game per 100 possessions that the player is in the game. The computation is performed at a “per possession” rate and scaled out to 100. The challenge lies at being restricted…
As a point guard growing up, I found that driving with my dominant shooting hand would typically put my shooting hand away from the basket. And being undersized at the position (5’4″, 95 pound Sophomore) made life more difficult to shoot off the dribble. Instead, I developed my non-dominant hand, which gave me two options…
On September 28th, the NBA Board of Governors approved changes to the NBA draft lottery system. These changes were construed in an attempt to help avoid tanking in the league in an effort to maximize a respective team’s probability of obtaining a high draft pick. In part, this is not a bad effort as we…
In a recent blog post on defending the Hammer Offense, I showed that the quantification of distance to passing lane helps identify the coverage a defender has on an opposing player.In that very post, I showed only a graphic and did not give insight into how to compute this quantity. Today, we will walk through…
While I’m on a flight between Albuquerque to Oakland, let’s take a quick glance at another advanced analytic: Game Score. Game score is a metric that was developed by John Hollinger (one of the Godfathers of basketball analytics) to quickly give a rough estimate of a player’s contribution to a game. If a player scores…
In our previous post, we introduced the theory associated with Regularized Adjusted Plus Minus (RAPM) through an illustrative example. In this post, we walk through a vanilla-flavored methodology for building a RAPM model for NBA data. In this article, we focus on the data necessary, the required data manipulation process, and methodology for determining required…
Squared Statistics: Understanding Basketball Analytics 