Kinematics of Player Motion

After a couple special topics posts in Sketching and Voronoi Tessellation, we take a step back and look at the basic mechanics of player motion: position, velocity, and acceleration. Understanding computation and estimation of such quantities allow us to perform more important calculations such as trajectories, coverage, and crashing. The easiest way to capture these…

Measuring the NBA MVP Race and Solomon Hill

In two days, we will find out who is the NBA MVP: James Harden, Kawhi Leonard, and Russell Westbrook. Each player has their pros and cons, and have been heavily debated over the past month since the finalists have been listed. Despite Leonard leading the Spurs into the second best record in the league (61-21)…

Markov Simulation: NBA Playoffs Round 2

In continuation of our Markov simulation of the NBA Playoffs, we take a look at the updated probabilities for each team remaining. In this article, we take a cursory look at each second round match up and see how the first round panned out compared to the probabilistic predictions. So Far So Good: All rounds…

Markov Simulation: NBA Playoffs

With the NBA Playoffs set to get underway, we take a quick look at the probabilities for each team becoming the NBA Champions. Common consensus would place any combination of the five strongest teams: Golden State – Houston – San Antonio versus Cleveland – Boston. But the question is how likely? To answer that, we…

NBA Probabilities: Warriors, Spurs, Playoffs

At the close of the Pelicans – Warriors game tonight, we witnessed the Warriors set the record for fastest team to 60 wins with a 125 – 107 rout in Oakland. With the Warriors moving to 60-6 for the season with 16 games to go, the 72-10 record seems very well within their grasp. However,…

NBA Power Rankings – November 15th Edition

Over the course of the past week, there have been another 58 NBA games that have been played, bringing the total number of games played to 151; over ten percent (12.28%) of the season complete. To date, we still have one undefeated team (Golden State, 11-0) and one winless team (Philadelphia, 0-10). Using the beta…

NBA Data Science: Breaking Down NBA Data

Recently, the Oklahoma City Thunder and the San Antonio Spurs played to a frenetic 112 – 106 OKC win on October 28th. It was one heck of a statement to open the year for the NBA as the Thunder returned to the court as a complete, healthy unit; the first time since February of last…

Spatio-Temporal Data In the NBA

In our last post we saw that we can use a simple nonparametric statistical method, called the kernel density estimator, to build nice looking scoring charts. As we saw, these charts give a better idea of the distribution of the scorer when compared to the basic shooting chart used for several decades past. In this post,…

NBA Shot Charts via Kernel Density Estimation

Shot charts have been used for decades, used to identify locations where players make field goals and to identify locations where players give up field goals. Decades ago, each player has their own chart with four quarters. Typically if a field goal is made, the player has a ‘o’ is placed on the relative location on…