Visualizing Goaltender Statistics Through Beeswarm Plots

A picture is worth a thousand words. Yes, it’s a cliché, but when it comes to visualizing data, an individual can tell a story via the choices they make when presenting their data. One of the most common visualizations is a plot showcasing the frequency and distribution of an event. Data like this are often presented in a histogram or box-and-whisker-plot. However, a limitation of both of these types of plots is that neither shows the individual where each data point falls. On the other hand, a beeswarm plot allows the user to see where each individual point falls across a range. A random jitter effect is applied to maintain a minimum distance between each point to minimize overlap.

Inspired by the wonderful graphs from Namita Nandakumar and Emmanuel Perry, I thought I would attempt to visualize how goaltenders have fared in goals saved above average over the course of their careers.

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