Welcome to the Visual-Baseball Project, where we merge historical baseball data with the latest in data visualization approaches. This page provides examples from our visualization portfolio. Take a look at some of the work below.

Batting Explorers (Exhibit)

These displays are controlled using a wide range of facets, all conveniently presented in a filter window.

Win Percent Bullet Charts (D3)

Track your favorite franchise with these historical bullet charts that compare a single franchise to the league champs for every season.

Pennant Race Charts (nvd3)

Interactive pennant race charts are available for seasons dating back to 1901 – over 350 charts in all. You decide which team to display and which parts of the season to focus on using simple click and drag options.

Word Clouds (Processing)

Word clouds provide a visual synopsis of a story, book, or other document by displaying multiple sizes of text dependent on the frequency of usage.

Heatmaps (Protovis)

Heatmaps provide visual evidence of categorical differences by using color variation, often in the form of shades of a single color.

Game Summaries (Exhibit)

View the details behind every game played covering 60 seasons of Major League Baseball. Use filters to display only the information you wish to view.

Box Plots (D3)

View box plots to see differences in distributions by teams across different variables. These charts help give viewers a quick sense for patterns within a large dataset.

Circle Plots (D3)

Circle plots can be used to depict both size and order, making them a nice option for displaying ranking data such as baseball standings. The size of the circle shows how frequently a given rank occurred, making it simple to visualize patterns in the data.

Mapping (multiple applications)

Maps can be used to illustrate geographic patterns within the data, and are superior to text or charts for this purpose. Interactive maps provide a gateway for users to explore by using the familiar map interface.

Network Graphs (Gephi)

Network graphs present the ideal means to view interaction between entities (nodes), which could represent teams, players, places, and so on. The strength of the relationship can also be shown through thicker connections (edges) between nodes.