The league-wide samples stay pretty consistent year to year, which is good for establishing baselines for these metrics. However, the samples that I used in last week's post (20 bunt attempts or 10 fair bunts) did not correlate very well year-to-year. Notable R^2 are as follows: hit% - .514, out% - .226, sac% - .528, Bunt Runs/100 - .178. The one that surprised me the most, however, was coefficient of determination for fair bunt%. That was only .065, which I found strange considering fair bunt% appears to be a distinct skill. Bear in mind that even though we're looking at three years' worth of data, it's still a small sample size. In order to get players that were qualified bunters in back-to-back years, I had to eliminate all but 82 of the individual seasons. I was particularly puzzled by the low correlation for fair bunts, which I figured would be a detectable skill even in the limited sample.
Since we appear to have some of the SSS blues, I think the best way for us to cheer ourselves up is to open up the leaderboards to include 2008 and 2009 data. Well, maybe that's just me. Anyway, this section is going to contain a lot of tables - I'll have leaders and trailers for all of the metrics I discussed last week, along with some commentary when I feel it is necessary. Also, the minimums are now at 50 bunt attempts and 25 fair bunts. I'll begin with attempt percentage, for which I won't show any trailers (there 55 qualified players who haven't attempted a bunt in the three years). Oh, also, the swing minimum for attempt% is 1,000.
My love for the fair bunt% statistic is slightly diminished after seeing how poorly it correlated in my data, but I still think that it's an important statistic to look at. Below are the 10 leaders and trailers for fair bunt%; Chris Young (of the Diamondbacks) is really in a league of his own.
The next set of leaderboards are for hit%, out%, and sac% out of fair bunts.
Unsurprisingly, all of the sacrifice leaders are pitchers. The first position players to appear on the list are Daric Barton (.760), Yuniesky Betancourt (.724), and Jamey Carroll (.720).
Like I did last week, I will end with a glance at the best overall bunters with linear weights - this includes a weighting of their hits, sacrifices, and outs, and also takes into account missed and foul bunts. Again, I will present in a counting form and in the form of bunting runs / 100 pitches. However, in order to (hopefully) make it more intuitive, the rate stat will be scaled to the league average bunt as opposed to the league average event. Over the past three seasons, the average bunt has been worth -3.53 runs per 100 pitches, so that will be what I consider "average," or 0. Onto the best and worst bunters of the past three years:
|Rank||Name||Bunt Runs / 100|
As usual, the trailers include a lot of pitchers, who don't tend to get a lot of bunt hits. The first position players that appear on the list are Chris Young (-2.54), Brendan Ryan (-2.42), Tony Gwynn (-2.29), Yuniesky Betancourt (-1.70), and Juan Pierre (-1.13). Pierre has appeared a lot in these two posts, typically as a trailer in some category. Based on the data for these three years, he doesn't have the ability to be a productive enough bunter to offset his great number of bunt attempts. In fact, of the ten players that topped the attempt% list I showed at the beginning of this post, Pierre was the only player to grade out as a below-average bunter. One other note - I'm skeptical of the bunt runs values for Pennington and Furcal since Pennington had a bunt double and Furcal had two. Bunt doubles are essentially flukes, and since doubles are worth a lot more than singles are, they skew the run value totals.
With that, I'll put an end to this venture into bunting. There are more questions that I'd like to investigate (team bunting statistics and the impact of leverage on bunting as two that come to mind), and most importantly, I think we just need more data. For the time being, I would like to recognize Ichiro Suzuki as the best bunter of the past three years.