New Graphics
December 12, 2006
Cool stuff.
I’m “reading” John Burnson’s newest book, The Graphical Player. I say reading, but I’m really reading graphs and charts--hundreds and hundreds of graphs representing game logs, age, skill level and lots of other things for major league players. It’s fascinating stuff, and John has included some unique and excellent graphs in his appendix, highlighting things like the depth of each team’s minor league system. I highly recommend it.
Speaking of great graphs, have you seen this display by USA Today? It’s a crazy good, superb representation of how coaches voted for college football teams. Roll your mouse over the teams on the left to see how they were ranked by different coaches. Sensational concept and execution.
Finally, David Pinto has released his 2006 fielding graphs. This is also a crazy good thing. Given the state of baseball fielding stats, I tend to think that these graphs are the best way to show fans just how good and/or bad specific fielders are. They’re intuitive and relevant. For instance, here’s a graph of Mike Cameron’s range last year on flyballs:
Lots of interesting things here. First off, notice how center fielders have less predicted out on balls that are directly over second base, and more balls to the right and, especially, to the left of second? I didn’t know that. Also, Cameron was better going to his left than his right last year, perhaps because he was shading that way. Great stuff. I could spend days just poring over these graphs, plus the Graphical Player graphs. Graphs aren’t quotable, so you don’t tend to hear about them in blogs. But they’re insightful and just plain fun.
By the way, I was a little disappointed in David’s execution of his graphics (though beggars can’t be choosers. David does this for free!). The two lines are only differentiated by color, which makes them hard to read for those who are even somewhat color-blind. What’s worse, he used red as one of his colors, when red-green color blindness is the most common type. Secondly, there is no perspective on these graphs. David’s 2004 graphs showed a typical variance in each vector, which helped tremendously. On this graph, for instance, you can see that Cameron is good, but you don’t know how good.
I like the fact that the y-axis scale is measured in outs rather than a rate. I also like the way his graphs expand or contract depending on the range of opportunities.
The ball in play distribution is essentially the superposition of two ball in play distributions; one by right handed batters and one by left handed batters, so I think we should expect opportunities to have two peaks in left center and right center, rather than a single peak in straightaway center. That superposition applies everywhere, but it’s probably easiest to detect in CF.
Posted by JoeArthur on 12/12 at 06:43 PM
Just to confirm I am reading this graph correctly, you said that “Also, Cameron was better going to his left than his right last year, perhaps because he was shading that way.” I assume this is the case because a greater percentage of predicted outs became actual outs on balls hit to RCF (Cameron moves left, meaning toward RF) as compared to LCF (Cameron moves right, meaning toward LF).
This is probably a silly question but I just want to be sure I am understanding what I am looking at!
Posted by Matt on 12/13 at 12:33 AM
Yes, Matt, you’re reading the graph correctly.
Posted by on 12/13 at 07:31 AM
Studes—are you colorblind????!!
Posted by Alex R on 12/16 at 08:53 AM
Yup, somewhat. 5% to 10% of all men are at least somewhat color blind. It’s an important factor to consider when designing sports graphics.
Posted by on 12/16 at 09:20 AM
It is an important factor in any evironment and, as you say, it is one of those things that no-one really realises. I was in a meeting with a client trying to present a graph with three bars, each with a different color and didn’t realise the guy was colorblind ... it is quite challenging to then describe the graphic without mentioning colors
Posted by Alex R on 12/17 at 05:26 AM
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