Good Graph Design
March 16, 2005
It’s nice when a baseball publication manages to include graphics, but it’s also nice if they do it well. I received the latest issue of Baseball America yesterday, and I was pleased to see that they had a bar graph in the Major League Preview page on page 17. However, the bars in the bar graphs are a dark blue color, on top of a moderately blue background. You can barely see the data! I think the graph has something to do with average age at which contracts are signed, but I’m not completely sure.
Color contrast is a critical element of graph design. Lately, I’ve been lucky enough to assist David Pinto in the further development of his fielding graphs. Let me share with you one of the graphs I mocked up for David, focusing on Derek Jeter’s prowess at fielding ground balls (the gray areas represent the minimum and maximum number of outs achieved among all shortstops in each fielding vector):

This graph reinforces what many observers have said; that Jeter is fine going to his left, but among the worst when moving to his right.
But I really want to talk about two things I think are critical for a good graph: color contrast and positioning. There is a lot of information in this graph, but I like to think it’s relatively easy to read. Color contrast and positioning help make it so.
Regarding the color, the graph starts with a white background, and next adds gray bars to represent the range of potential performance in each vector. Next comes the yellow line to represent the predicted performance in each vector (based on the last three years and adjusted for ballpark). Yellow stands out on top of the gray boxes. We also made the yellow line relatively wide.
The final line is a black line that represents Jeter’s actual performance. Black stands out against the white, gray and yellow in the background, and also sits on top of all three. We also added symbols for the vector data points in the black line. By making the yellow line wider, you can see those instances when the black line is exactly on top of it. In other words, you can clearly see where Jeter’s performance was exactly equal to predicted performance.
Finally, we added a couple of gridlines that relate to a typical baseball field: the thirdbase line and centerfield. This way, you can relate the vectors and graph data to an actual baseball field.
I know I’m biased, but I think this is much better than a bargraph of blue bars on top of a blue background. The contrasts of color, size and positioning are critical for making good graphs. I know David is going to include some of these thoughts in the final graphs he produces—and I hope this example can serve future baseball graph producers too.
Studes,
You may be already familiar with the work of Edward Tufte, but if not, I think you’d really like it. He’s written 3 books on how to convey information visually. Makes me realize how worthless Excel (let alone Powerpoint) is for creating elegant graphs that shed light on issues. (And I’m not even particularly interested in design issues.)
Posted by
Stefan on 03/23 at 04:06 PM
Thanks, Stefan. Yes, I’ve read Tufte and find his work fascinating (though not as practical as I’d like, sometimes). He’s really the best-known teacher and spokesperson for good graphic design.
Posted by
studes on 03/29 at 09:36 PM
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