We're barely a week into the season, and already announcers are mentioning the bunt. I was watching a game earlier this week (I honestly can't tell you which. I'm thinking it was Braves-Brewers or Nationals-Mets), and the pitcher came up to bat with a runner on base and less than two outs. The announcer promptly said, ``And up comes [The Pitcher], and he should be bunting here."
As I stated in the summary, bunting gets a lot of criticism within the sabermetric community. Manny Acta stated at SABR Analytics that he first started looking at sabermetrics after being informed that the inefficiency of the bunt by a Mets clubhouse kid in 2005. So the knowledge about the bunt has been working its way down the line over the years.
That being said, pitchers are awful hitters. I mean really, really awful. With pitchers being that bad of hitters, it has to be more beneficial to a team's run expectancy to have the pitcher bunt.
That's what you'd think, but before we assume that, let's dig into the data a little. To start, let's look at the RE24 of a plate appearance where the pitcher executes a perfect sacrifice bunt; that is, each runner advances one base and the pitcher is thrown out at first.
|Base State||No Outs||One Out||Two Outs|
|0 0 0||-0.2183||-0.1571||-0.0918|
|0 0 1||-0.0344||0.1979||-0.3527|
|0 1 0||-0.1560||-0.2843||-0.3054|
|0 1 1||0.0279||0.0707||-0.5663|
|1 0 0||-0.1892||-0.1880||-0.2064|
|1 0 1||-0.0053||0.1670||-0.4673|
|1 1 0||-0.1269||-0.3152||-0.4200|
|1 1 1||0.0590||0.0398||-0.6809|
So, there are 6 out of a possible 24 Base-Out states where a perfectly executed sacrifice bunt results in a positive RE24. However, it's not enough to look at the RE24 for the plate appearance, we also need to look at the proportion of times a Base-Out state occurs given that the player bunted, or P( Base-Out | Bunt Occured ). Since we're focusing on pitchers, we're just looking at pitcher bunts.
|Base State||No Outs||One Out||Two Outs|
|0 0 0||0.01530612||0.005102041||0.005102041|
|0 0 1||0.00000000||0.006377551||0.000000000|
|0 1 0||0.06887755||0.006377551||0.001275510|
|0 1 1||0.00127551||0.000000000||0.001275510|
|1 0 0||0.27933673||0.327806122||0.003826531|
|1 0 1||0.02551020||0.048469388||0.000000000|
|1 1 0||0.07142857||0.128826531||0.003826531|
|1 1 1||0.00000000||0.000000000||0.000000000|
So, from all this, we can get an expected value of RE24 given that a bunt occurred but taking ΣBase State ΣOuts RE24|Base-Out × P( Base-Out | Bunt Occured ). After all that, the RE24 for a bunt would be expected to be -0.1755696.
So, if a pitcher can have a better RE24/PA than -0.1755696, his team's run expectancy would be better served on average by him hitting, as counter-intuitive as that might seem. So what percentage of pitchers would you expect to be better off bunting? Of the 75 pitchers who got at least 20 non-bunt PAs over the 2013 season, there were 12 pitchers who fell below the break-even point. That still means a majority of pitches (84%) would still be better off swinging away. For those wondering, there were no position players with at least 400 PAs to fall below the threshold (The lowest value was -0.0624).
So who were the pitchers? Who were the disastrous dozen? Well, here they are, along with some of their other batting stats.
|Pitcher||Non-Bunt PA||RE24||RE24/PA||Slash Line||wOBA||wRC+|
|Jorge de la Rosa||50||-11.3249||-0.226498||.038/.074/.038||0.058||-95|
Blech. I mean really, blech. Those are some rough statistics. Only 3 of those 12 had an ISO better than .000 and there were 4 OBPs over .100. By comparison, Miguel Cabrera had the highest RE24/PA in the majors last year with 0.1153. And for those interested, of the 75 pitchers with 20+ non-bunt PAs, there were only 4 pitchers with a RE24/PA greater than 0. They were Tyler Chatwood (0.0739 in 39 non-bunt PAs), Zach Grienke (0.0308 in 70), Henderson Alvarez (0.0274 in 30), and Scott Feldman (0.0237 in 32).
Of course, there's the obvious cavaet in this: sample size. There's an incredibly small sample size in this dataset, making any conclusions difficult to draw. However, with the well-documented ineptitude of pitcher hitting, these conclusions might not be too big of a stretch, even with the small sample size.