# Boston vs. The Field: Defensive 3PT%

An annual discussion that takes place roughly around the start of every NBA season is whether teams are “good” at perimeter defenders. This discussion arises due to spurious, early returns on defensive three point percentages. This year is no different as the Twitter feed becomes log-jammed with discussion about whether there is a “leave the…

# 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…

# Story Underneath Usage: Incompleteness

In the era of possession-based statistics, we often look at items such as per-possession or per-100 possessions. This type of parsing makes sense as a possession is deemed to be the period of time a team “controls” the basketball. The technical definition of a possession defines the end of the “control” period as the point of…

# 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…

# Considering Consistency of an Analytic

Warning: This is a lecture from one of previous statistics courses taught over the years. It will be theoretically heavy, but offers insight on some of the research process required for developing analytics. (End Disclaimer)   Thought Exercise: Perimeter Defense Whenever we develop an analytic to help describe the game, we typically have to ask three things.…

# Transitioning Turnovers: Case Study of Golden State and Toronto

In Dean Oliver’s Four Factors, we are interested in effective field goal percentage, offensive rebounding percentage, free-throw rate, and turnover percentage. If a team cannot dominate a couple of these categories, then it will be unlikely for that team to win. For instance, let’s consider effective field goal percentage. The Golden State Warriors have posted a .558 eFG% while limiting their…