Does swinging at the pitch really protect a base-stealer?

Another one of those things I tend to over-hear on the radio: When a runner is trying to steal, the batter should swing, as this will disrupt the catcher and give the runner a better chance of stealing. Here’s to ye olde baseball conventional wisdom, the starting point of many a Sabermetric writing. Fair enough. Let’s see if this one stands up to the evidence. First, I isolated all instances of a stolen base or caught stealing, either of 2nd or 3rd in 2006, absent pickoffs. (As always, thanks to Retrosheet for the fact that I have a gig… and that I haven’t yet finished my dissertation.)

I looked at what the batter did on the pitch that came to the plate while the runner attempted to steal and classified it either as a swing (swinging strike or missed bunt), or a non-swing (either a ball or a called strike). I also classified pitches as either strikes or balls. Needless to say I also looked at whether the runner was safe at second (or third). The rest was just a matter of a few chi-square analyses.

Does swinging “protect” a base-stealer? Far from it. If the batter swung at the pitch while a runner attempted to steal 2nd, the runner was safe 65.7% of the time, while if he didn’t the success rate was 77.9%. Looking at a runner stealing third, the same finding emerged. When the batter was not swinging, the runner was safe 82.1% to 56.8% for the swingers. Both chi-squares were significant. Apparently, conventional wisdom has been wrong for a while, although players only swing about 19.8% of the time in this situation, so perhaps the “wisdom” is more present in the press box than on the field itself.

This is a strange finding though that needs some explanation. The fact that a relationship has been found does not mean a cause has been found. For example, it’s possible that batters are more likely to swing and miss (in this case, all swings missed. A foul ball would have returned the runner to the original base and a ball in play would not have resulted in a stolen base) at well-placed pitches and that those well-placed would be more easily used to gun down the would-be base stealer. Let’s take away the swing for a moment, and look at whether on non-swinging responses, whether the pitch was called a ball or strike made a difference on the runner’s fate when he tried to steal second. On balls, the runners’ success rate was 78.5%, while on called strikes, it was 76.3%. Chi-square was not significant, indicating that in this data set, it makes no difference statistically whether the pitch was called a ball or a strike. Now, this doesn’t disprove the original conjecture. Perhaps balls that are swung at and missed are a different breed altogether (more likely to miss a fastball?) or perhaps those that are swung and hit are the oddballs (pardon the pun). There could be a bias in which pitch types end up in the catcher’s glove and they might be biased in the direction of easier throws to second. There might also be pitches which are easier for the runner to read (and get a good jump on) and which are less likely to be swung at (or more likely to be hit when they are swung at).

Another factor floated in such discussions is the handedness of the batter. Most catchers are right-handed, and naturally spring out toward the left-handed batters’ box when making a throw to second. Perhaps if that box is occupied by a left-handed batter, the catcher will show some ill effects of this “obstacle.” The answer is no. Success with a lefty in the batter’s box was 76.1% and with a righty, it was 75.0%. No significance in that association. For a throw to third, there is an advantage to the runner for having a right-handed hitter in the batter’s box (80.6% to 67.7%). In that case, a right-handed batter is more directly between the catcher and third base.

To be honest, I’m confused. I don’t know what to make of this finding. Why would a batter’s swinging actually make it easier for the catcher to throw a runner out? Perhaps the batter is more of an obstacle standing there after not having swung than if he had swung. But, for what it’s worth, a reminder that one should never take accepted wisdom in baseball (or anything) without asking to see some proof.


21 Responses to Does swinging at the pitch really protect a base-stealer?

  1. John Beamer says:

    Hmmm. Interesting.
    One other reason could be failed hit and runs means that swinging strikes cause more outs … especially if they are aniticipated in a pitchout by the fielding team.
    Also a swing sometimes indicates that the runner is running on his own … he could be a less accomplished base stealer.

  2. Sean Smith says:

    I can understand if CV is wrong, that swinging and missing doesn’t help the basestealer at all, but I can’t believe it actually hurts the basestealer. Just doesn’t make sense.
    Something else may be going on with busted hit and runs. You might find that its slower baserunners being send on hit and run attempts. Or perhaps the baserunners are not getting as good jumps – they wait a little longer to make sure they aren’t being picked off, thinking that the batter will be trying to put the ball in play anyway.

  3. Guy says:

    Yes, what you are mainly measuring is the difference between true SBAs — when the batter is expected to take the pitch — and failed hit-and-run attempts. The H&Rs often come with a slower runner who wouldn’t attempt a straight SBA, and that results in the slower success rate on swinging strikes. Actually, it’s a little more complicated than that, since some of the swinging strike plays were probably not a true H&R (batter must swing) but an option for the batter. The “optional swing” play likely features faster runners, and a higher success rate. But the busted H&Rs almost certainly account for all or most of the lower success rate.
    If you really want to know if the swinging strike helps or hurts the runner, you will have to control for quality of runner by comparing the success rate of a given set of runners when batter swings vs. when batter takes.
    However, these results are themselves interesting. It is often asserted that teams make more SBAs than they should, since the aggregate success rate appears to be at about the break-even level. That is misleading, however, because CS totals include a lot of busted H&Rs. Your data would suggest that the success rate on true SBAs (of 2B) is 78%, far higher than the raw SB/SBA ratio. That means teams are using the SB weapon much more rationally than we thought, and that it does have a postive offensive value.
    BTW, I’m not sure it’s “CW” that a batter should swing. I’ve always thought the batter was expected to take (and that should really count as a cost of the SBA). Surely, no manager asks his batter to swing and deliberately misss. At most, you would want your batter to swing if he got a good pitch to hit (but of course, you always want that).

  4. Pizza Cutter says:

    Maybe it’s just the Cleveland announcers that I listen to that believe that swinging is convention wisdom. The busted hit and run theory works logically, although I wonder if it would produce that big an effect. Most H&R are specifically attempted with high contact rate hitters. The more likely event would seem to be a foul ball or a ball in play. But then again, those have, by definition, been removed from the equation. Maybe I should dig a little deeper and see what I can find…

  5. Pizza Cutter says:

    Guy, I specifically removed pickoffs from the database, so those aren’t influencing the findings.
    The problem with estimating contact rates league wide is that hitters make contact with 80% of the pitches that they choose to swing at and batters (other than Russell Branyan) don’t swing at pitches 2 feet outside. Suppose that a hitter was ordered under threat of death to swing at the next pitch coming from the pitcher, even if it was 2 feet outside. What would his contact rate be then?
    I’m thinking that I could take a look at how often runners go on a pitch and contact is made (excluding 3-2 counts with two outs), whether it’s a foul ball or a ball in play, which we have in the Retrosheet data. That could give us a baseline on H&R. I could also try a binary-logit model with speed scores entered in as a control variable. Hmmm….

  6. Guy says:

    I can believe that broken H&Rs explain this. If 20% of SBAs involve a swinging strike, that would mean about 425 busted H&Rs in NL last year. If hitters make contact 80% of the time (just a guess), that would suggest about 133 attempted H&Rs per team, less than one per game. Seems plausible.
    * *
    In my post above I forgot about pickoffs. So the overall success rates will be lower. Still, if we remove the busted H&Rs, it will increase the overall success rate by about 2%.

  7. John Beamer says:

    PC — why can’t you compare every hitter’s SB% on swing strike (bodged H&R) vs called strike? Or does this run into small sample size issues?

  8. Pizza Cutter says:

    Sample size would probably be an issue here for some folks. But I could have a minimal cutoff point. I could then correlate that to contact percentage. See if there’s a relationship. Ah, but it’s the last week of class where I live, and finals week is just around the corner. It was bad when I was a student. It’s worse now that I’m a professor.

  9. John Beamer says:

    You’ll also need to watch age as we know that speed declines — which could affect success rate.
    Perhaps the best method is to select 2% cohorts … look at all player seasons with 76-78% SB success for CS and see what SS is etc … probably should do vice versa as well to be fair

  10. Guy says:

    PC: You only have a sample size issue if you care about individual hitters/runners. We just care about the aggregate. So take every hitter with >10 SBAs (or whatever), weight your swinging-strike sample to match the no-swing sample (because the fast guys will be overrepresented in the no-swing sample), and see how the success rates compare. Or more simply, just take a straight average of the success% differential (which was 78%-66%=12% overall). You may also want to separate for LH vs. RH pitcher, if the two samples differ on that dimension. Ideally you’d control for quality of catcher arm as well, but may not be worth the trouble.
    If you want a shortcut that will tell you if busted H&Rs is the issue here, just look at the overall SB% and # of SBAs for the hitters in the swinging sample vs. the take sample. I’m confident that the swinging sample includes a lot more low% and low-SBA hitters.
    * *
    I know you didn’t include POs, which is fine. I was just acknowledging that my earlier claim — that true SBAs are successful 78% of the time — is not correct if you take PO into account.
    * *
    If you can tell from Retrosheet whether a runner was going on the pitch, then you should be able to do an analysis of the effectiveness of H&Rs more broadly. That would be terrific — don’t think I’ve ever seen that done. But it would be complicated, as you’d need to account for impact on hitter performance, runner advancement, DP rate, etc. Would probably need to use a RE or WE framework.

  11. John Beamer says:

    That works!
    I initially dismissed that approach because I thought that you wouldn’t capture poor base stealers swiping on a CS much …. but obviously you are looking at how the good stealers perform on SS. In summary, I was dog stupid.
    PC — keen to see these results!

  12. John Beamer says:

    H&R definitely appears to be the issue. I’ve taken the Retrosheet data for five years 2000-2005 and looked at SB for a C&B vs S … I replicated PC’s results:
    On a S: 65% success
    On a C or B: 76% success
    Controlling for “faster” base stealers and not limiting SB that success on an S increases to 74%.
    That doesn’t control for aging, handedness or catcher’s arms so is quite rough

  13. JR Ewing says:

    I think the Guy is on to it here… the difference is a runner being thrown out on a SB attempt (where the batter gets the “take” sign), a failed HR attempt, and a runner getting the green light (where he can run when he wants but no sign is given to the hitter). If there were a way to get data on what “play” was called – SB, H&R or green light – then you could compare success % on for failed H&R individually from that of a green light. That would better compare apples to apples.

  14. John Beamer says:

    Post 12 should say
    “Controlling for “faster” base stealers and not limiting SB ATTEMPTS THEN success on an S increases to 74%.

  15. Guy says:

    John: how did you control for basestealing ability of the runners?
    The .02 difference that remains — assuming it’s real — is probably a function of the pitchers and/or catchers in the Swing sample. That is, even with a good runner on, if the manager is putting the H&R on — instead of the steal sign — it probably reflects less confidence the runner can make it on his own. If we could control for CS% of the pitcher and the catcher, as well as the runner, the difference in success rates probably drops to zero.

  16. John Beamer says:

    Guy — I weighted the samples as per your suggestion.

  17. tangotiger says:

    Great job all-round guys. I agree that it’s H&R, and quality of baserunners.

  18. MGL says:

    It is hit and run, quality of baserunners and the fact that balls not swing at include balls that the catcher cannot handle like balls in the dirt. Balls than batters swing at do NOT include balls that are hard to handle (way out of the strike zone) unless there is a hit and run, and even then, the batter is NOT supposed to swing at a ball in the dirt on a hit and run although they often do.
    When you looked at CS% of balls versus caught strikes, while your chi-square test suggested that the results were not significantly different, sometimes common sense trumps statistical significance. OF COURSE runners will be more successsful on balls than strikes as some balls are hard to handle for the catcher and more strikes are fastballs. It is more likely that the true CS difference between balls and called strikes is LARGER than what you got in your sample.

  19. Pizza Cutter says:

    MGL – Some of that might be taken care of by the fact that a pitch that’s hard to handle that allows a runner to go to second would be scored as a wild pitch, rather than a stolen base, although that’s not going to happen 100% of the time. If I have time this weekend, I will play around with looking at speed/quality of the baserunners… it’ll distract me from grading this stack of papers…

  20. Pizza Cutter says:

    So I went back in and fooled around with the data set. On pitches where the batter swung and a stolen base was attempted, it generally was a poorer runner (using Bill James’s speed score formula). The t-test was significant, and the difference was about half a point on average (6.0 vs. 5.5). I put together a binary logit regression and looked at both whether there was a swing and the speed score of the runner on first attempting to steal second (I restricted it to just these situations.) Speed score was a very big predictor, but swinging still didn’t disappear as a significant predictor. Seems that it’s not all just bad runners being thrown out on busted hit and run plays.

  21. Guy says:

    Beamer’s analysis above has already shown that it IS almost entirely a function of the quality of the runner. The remaining small difference is presumably some combination of MGL’s point (some of the non-swing pitches were hard to handle), and/or the quality of the pitcher and catcher at preventing SBs. Unless you control for those 3 factors, your regression isn’t showing anything. (Plus, speed score is only a crude way of controlling for runner ability, compared to what John did.)

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