Statistical network of basketball

Posted to Statistics  |  Tags: ,  |  Nathan Yau

By now, everyone’s heard of Moneyball. Applying statistics to baseball to build the best team for the buck. Naturally, there’s a lot of interest these days in applying the same data-based philosophy to other sports. Jennifer Fewell and Dieter Armbruster used network analysis to model gameplay in basketball.

To analyze basketball plays, Fewell and Armbruster used a technique called network analysis, which turns teammates into nodes and exchanges — passes — into paths. From there, they created a flowchart of sorts that showed ball movement, mapping game progression pass by pass: Every time one player sent the ball to another, the flowchart lines accumulated, creating larger and larger and arrows.

Using data from the 2010 playoffs, Fewell and Armbruster’s team mapped the ball movement of every play. Using the most frequent transactions — the inbound pass to shot-on-basket — they analyzed the typical paths the ball took around the court.

The challenge with basketball is that play is continuous, whereas baseball events are discrete, so you can’t apply the same methods. But if you can model the game properly, you know where to optimize and areas that need work.

Favorites

Divorce Rates for Different Groups

We know when people usually get married. We know who never marries. Finally, it’s time to look at the other side: divorce and remarriage.

Famous Movie Quotes as Charts

In celebration of their 100-year anniversary, the American Film Institute selected the 100 most memorable quotes from American cinema, and …

Best Data Visualization Projects of 2016

Here are my favorites for the year.

Top Brewery Road Trip, Routed Algorithmically

There are a lot of great craft breweries in the United States, but there is only so much time. This is the computed best way to get to the top rated breweries and how to maximize the beer tasting experience. Every journey begins with a single sip.