# Approximating Curves II: Assimilation of the Jump Shot Process

If you were to ask one-hundred shooting coaches “What’s the most important aspect to making a jump shot?” you will probably get at least fifty different responses. Answers may range from detailed such as the finger mechanics of the release or “shooting axis,” to broad, holistic responses such as “Find your repeatable comfort zone at…

# Approximating Curves I: Mechanical Process

Now that the 2019-2020 season has ended, let’s take a quick look at something almost every data scientist knows: polynomial projection. Now, if you’re a data scientist and find yourself mumbling, “I’ve never heard of that,” don’t worry: You have. Over the next few posts, we are going to discuss a larger problem of approximating…

# Analytic Breakdown: 1963 Finals Game 6

On April 24th, 1963, the Boston Celtics took the floor at the Los Angeles Sports Arena holding onto a 3-2 advantage in the NBA Finals against the Los Angeles Lakers. For the only time in the history of the league, a Finals team trotted out only  (later to be named) Hall of Fame players: Bob…

# Extending Possessions: Geometric Distribution

In a recent post, we took a brief glimpse at offensive rebounding and discussed some pro’s and con’s about crashing for rebounds and provided an illustration about where rebounds go after missed attempts. In one such instance, you would have seen this plot: For the sake of argument, let’s suppose that every single red circle…

# Offensive Crashing

Back in high school, it behooved our team to “keep one man back” on offense. The thought process was simple, if the defense were able to get out into transition, our team would at least impede their progress towards the basket with the hopes of them settling into the half-court offense. Sometimes it worked. In…

# Manifold Nonparametrics: Which Way Do Passers Pass?

As a player traverses across the court, they break down and process every event that they see: the assertion of defensive players, the alignment of their teammates, and current state of the game. The ability to perceive all three components simultaneously is what I call court vision. It is one of the primary instigators that…

# Exercising Error: Quantifying Statistical Tests Under RAPM (Part IV)

In the Regularized Adjusted Plus-Minus (RAPM) model, one of the perceived challenges is understanding the error associated with the resulting posterior RAPM value a player receives. In a previous post, we noted that RAPM is a Bayesian model in which we assume that “player contribution” can be estimated through weighted offensive ratings conditioned on the…

# Warping Play Registration

Synergy: Breaking Down Field Goal Types With the creation of Synergy, the basketball world gained valuable access to previously hard-to-obtain data on all field goal events in the league. One of the biggest introductions was the “primary defender” tag on field goal events. With play-by-play data, when a player drives to the basket or attempts…

# The Randomness of Ratings

Fresh off a Boston Celtics sweep of the Indiana Pacers, across Twitter phrases of “Remember that the Boston starters were -3.5 Net Rating for the series” piped up. The implication was that the Boston starters should have lost the series, and the most common rumblings came about the depth of Indiana’s bench costing them the…

# The “80 Point Club”

Whenever we talk about scoring in the NBA, typically the the conversation points towards heroic scoring feats such as Wilt Chamberlain’s 100 point game or Kobe Bryant’s 81 point game. Or Wilt Chamberlain’s 78 point game… Or Wilt Chamberlain’s pair of 73 point games… or Wilt Chamberlain’s 72 point game. Of those other spurious 70+…