Team Franchise Radial Axis Network Anatomy

A few years back, I created network graphs for many MLB franchises, using data from the Lahman Baseball Database. These graphs displayed the connections between teammates throughout the history of a given franchise from 1901-2013. Any players who were on a roster within the same season (or seasons) were connected to one another, with each node in the network representing a single player. These were then sized to reflect the number of seasons played with that franchise. Every graph was customized by using one or more of their official team colors, resulting in a visualization like this:

A full roster of the live versions can be found here.

Now that 2019 data is available, I thought it was about time to update the graphs, but this time with a new look that might make the graphs a bit more intuitive and perhaps even more visually attractive. Out of this was born the radial axis franchise graph, as shown for the 1901-2019 Detroit Tigers:

I’m pretty excited about the look the Radial Axis layout provides for this sort of data, and I think you’ll see why it is an effective method for visualizing all the players over the course of 119 seasons. Let’s have a look at the anatomy of this graph.

The graph runs in a counter-clockwise manner, starting with 1901 at the bottom of the graph, and working all the way around until we get to 2019, also at the bottom of the graph. Each set of nodes along the way represents the collection of players with their first Tigers season in that radian. We can see some years where there were many new players (1912 has an exceptional number), while other years had very few new players, 1915 being an example. Here’s a general diagram to help with this concept:

We can also identify a handful of players with especially large nodes, which indicate the number of seasons with the Tigers. These are sorted to make the graph clean and easy to interpret; players with the most seasons will all be closest to the center of the graph, with teammates from the same starting year sorted from longest to shortest tenure. The perimeter of the graph will be populated almost exclusively with one-season players.

For context, let’s examine a few of the large nodes, and identify who they are:

I hope this is starting to make sense. Each radian represents a season, and each node on a radian depicts a player, sized by their longevity with the team. The third critical aspect of the graph is the connectivity between players, represented by the thin gray lines running between them. These are called edges, and are at the heart of a network graph. Let’s have a closer look at the edges for Alan Trammell, as one example.

If we click on the Alan Trammell node, the graph is reduced to him and the players he played with over his career – or at least those who were on the roster in those seasons. This is the fun part of the graphs, as it facilitates exploration and pattern discovery. Here is a portion of the Trammell network, zoomed in so we can see the connections:

Now the edges are a bit more visible, and the graph detail begins to reveal itself. Notice the multiple large nodes in line behind Trammell; it turns out that this is the celebrated 1977 class, many of whom would ultimately be members of the great 1984 World Series champs. So while the 1977 Tigers were not a good team, they were beginning to see the fruits of a strong minor league pipeline. In order, here are the players in that group, and their connection to the 1984 team:

  • Alan Trammell (20 seasons, WS Champ)
  • Lou Whitaker (19 seasons, WS Champ)
  • Jack Morris (14 seasons, WS Champ)
  • Lance Parrish (10 seasons, WS Champ)
  • Milt Wilcox (9 seasons, WS Champ)
  • Dave Rozema (8 seasons, WS Champ)

Trammell is obviously connected to many other players who started in different seasons, given his 20 years with the team. In fact, he has a degree measure of 333, representing the number of players with a connection to Trammell. Thus, we can also see many connections to players who started their Tigers journey in other seasons. The three large nodes to the upper right of Trammell are interesting – who are they?

  • Closest to Trammell is John Hiller (1965-80)
  • Next is Mickey Stanley (1964-78)
  • Followed by Willie Horton (1963-77)

What we have here are the three remaining holdovers from the 1968 World Series champs, finishing up their careers just as Trammell was starting his long tenure with the Tigers. Discovering patterns like this make network graphs very interesting for me, and I hope you will also find them interesting. I’m currently in the process of refining the Tigers graph, which will be followed by graphs for each MLB franchise, once again using their team colors to provide some visual context. Hope you found this informative, and we’ll see you soon.

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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:


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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