Final Network Graph MLB Template

After what seemed an eternity (in reality, just 10 days), I’ve settled on a template and formula for depicting the player networks for MLB teams dating back to 1901. Throughout this process, the hometown Tigers have been my trial balloon to see if and how this idea would work. I’m happy to report that the idea not only works, but it makes for a beautiful (and highly addictive) interactive graph.

After several days of testing a variety of graph algorithms, I’ve landed back at the ARF method used for the Octavio Dotel graphs created earlier this year. There’s something about a circular layout that is visually appealing and informationally dense at the same time. Players are clustered by color, reflecting the primary peer group they belong to, although many will connect across two or more groups. The size of each player node reflects the number of seasons played with the team. Alan Trammell and Ty Cobb have large nodes, while Eddie Miller has a very small node, reflecting his single season in a Tigers uniform. Check it out for yourself: UPDATE: Node Sizes not behaving as planned – still tweaking

Tigers Network Graph

To play with the live version, click here.

It took awhile to get a satisfying result, but after setting a few parameters in Gephi and tweaking some options I’m thrilled with the graph. Now I’m poised to do the same for all MLB franchises, using the same settings to allow each franchise’s patterns come to the fore. I’m eager to create the entire series of graphs, and to start assessing the differences and how they relate to team success patterns.

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Another Tigers Network Graph

I’m having a lot of fun creating network graphs using Gephi, and excited about the possibilities for displaying a wide range of baseball information. My initial pass at showing team connections uses the Tigers, with this version incorporating all players from 1901 through 2013. Try it out here.

Update – new version with Tigers colors: Updated version

This is done using a radial axis layout with Chinese Whispers Clustering, based on a paper by Chris Biemann. The colors along each of the axes is based on the clusters created by this algorithm. Once again, I’ve used Sigma.js to create the interactive version, so you can dive into the graphic and gain an understanding for how the data is displayed. Here’s a static view of the graph:

Tigers-1901-2013-graph

Kind of colorful, isn’t it? For those of you who are long-time Tiger fans, you’ll soon detect that each cluster (color) represents a specific era in Tiger history, an by clicking on individual nodes, you’ll be able to see which players connect across multiple clusters. Typically, this will be players like Alan Trammell, Ty Cobb, and others who played many years with the club, and thus transcend their own cluster position.

Not sure if this will be the style for all the franchise graphs I plan to do this year, but it feels close, given the ability to display more than 1500 players and nearly 48,000 connections without having things too cluttered.

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Octavio Dotel Network Draft 2

A few days ago I shared a post about creating a network graph detailing the many travels of former Tigers pitcher Octavio Dotel in his Major League Baseball career – 13 franchises over a 15 season span. I now have a live graph on my website, complete with a search box, hover capabilities, and easy clicking on links to narrow the graph to a manageable number of nodes.

Gephi provides the base functionality for the network creation and the excellent Sigma-js plugin converts the original network to a highly interactive web-based one. All I have to do is get the data into Gephi, choose a suitable algorithm, and maybe tinker a bit with the style settings in Sigma, and presto! a slick graph is created. Here’s a static look, but to really appreciate the beauty of the interaction, navigate to the Dotel visualization. The live version lets you mouse scroll to resize the image so you can zoom in for greater detail, in addition to the other navigation functions already mentioned. I’m not done yet, as some more data elements are coming, but the basic look and feel should remain unchanged. Enjoy!

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