Joe P. Sheehan has a neat article out yesterday that takes the next step in comparing players. He calculates similarity scores on individual pitches using pitchf/x, allowing him to find pitchers that are similar in the actual pitches they actually hurl at batters. The similarity scores know nothing of effectiveness--they just use velocity and break (both x and y) from the pitchf/x data.
One of the pitchers that Sheehan investigated was Mariano Rivera and his cutter. Here is the list of pitchers who had a comparable cutter in MLB last season, according to Sheehan's system
Yep, that's Jared Burton, coming out well above everyone else in the similarity scores. This is consistent with some previous work that John Walsh did for us in September, which also showed qualitative similarities between Burton and Rivera. It's pretty neat to see just how similar they are, relative to other pitchers in baseball.Name Pitch Throws MPH pfx_x pfx_z Score
Mariano Rivera FB R 93.4 2.72" 7.72 100*
Jared Burton FB R 93.4 1.57" 7.58 98*
Brandon Medders SL R 91.2 2.27" 9.40 95
Juan Salas FB R 90.9 1.02" 8.05 95*
Jon Lester FB L 92.1 4.50" 9.56 95
Jason Isringhausen CT R 90.3 1.69" 7.92 95
Randy Flores FB L 90.0 1.79" 7.41 95
Jonathan Broxton CT R 96.3 1.03" 8.40 94
Brian Wolfe CT R 92.6 -0.39" 6.97 94
Kevin Cameron FB R 91.9 -0.11" 6.64 94
Now, as Sheehan makes clear, Rivera's pitch moves a good inch horizontally more than Burton's. And small sample sizes could be a factor here as well. But I think it's darn interesting that we keep seeing Rivera pop up as a comparable pitcher to Burton. As I've said before, it's very unlikely that Burton will come anywhere close to having something like Rivera's career. But having a pitch that is similar, at least in some ways, to Rivera's can't hurt either...
On a broader note, this line of work has tremendous potential in a variety of fields, perhaps most significantly in our ability to identify player similarities. As PECOTA has shown, comparisons to similar players is an extremely effective way to predict future player performance. Using quantitative "scouting" data like pitchf/x should eventually allow us to greatly improve our ability to identify similar pitchers, and thus predict their performance.