Is bunting smart? Want to know why bunting is bad? Let’s start with a definition:
Run expectancy: how many runs we can expect to score, on average, given a specific base/out state.
Base/out state is also simple: it’s a situation, such as runners on first and third with one out. Every hitter comes to the plate in a base/out state; it could be 2 outs and bases empty, or no one out and the bases loaded. There are 24 possible base/out states.
And, for every base/out state, there is a mountain of MLB data that shows the probability of a run scoring in that situation, and how many runs score on average in any given situation (run expectancy). We’ll touch on run expectancy and bunting today, and cover probability another day.
How Has Run Expectancy Data Changed Baseball?
Well, to be precise, it only changes baseball when players and coaches are receptive to it. Understanding run expectancy charts helps a coach and player make good decisions based on the probability that runs will score, and how many we can typically expect.
The biggest takeaway from run expectancy is how incredibly important outs are. Every out causes a drastic reduction in expected runs, so we have to treat them like they’re precious. This is where sacrifice bunting comes in to play.
Why Bunting Is Bad — It Reduces Expected Runs.
In short, because outs are the biggest detractor from a team’s chances of scoring, sacrifice bunting hurts — a LOT. I’m not talking about bunting for hits.
Below are three charts that illustrate how expected runs decrease in the three most common bunting situations:
- Bunting a single runner from 1st to 2nd (most often used late, when the winning or tying run is aboard)
- Bunting a single runner from 2nd to third (most often used in the same situation as above)
- Bunting two runners over from 1st & 2nd, to 2nd & 3rd (this is common when weaker hitters come to bat)
I jumped onto Tom Tango’s website, Tangotiger.net, and used his run expectancy data, which I inserted into the charts below, to make the data easier for you to read. The data is from 5 MLB seasons, 2010–2015.
I recommend Mr. Tango’s book, The Book: Playing the Percentages in Baseball, which can be found Here. I really enjoyed it. The information he posts on his website is free, so please support his research.
Sac Bunt, 1st to 2nd
In the situation below, I’ve highlighted the two base/out states we’re dealing with: runner on 1st with no outs, which then becomes a runner on 2nd with 1 out after the bunt.
Runner on 1st, No Outs: We expect 0.86 runs on average
Runner on 2nd, One Out: We now expect only 0.66 runs on average
RESULT: The bunt reduces the success of the average inning by 0.2 runs, which means that if you bunt 10 times in this situation, your team would score 2 fewer runs than if you didn’t. This might mean two fewer games tied up or won…
Sac Bunt, 2nd to 3rd
This is a common situation, trying to move the potential tying or go-ahead run to third with one out, so that a team can “manufacture” the run. A runner on third with one out will score with a deep fly ball or ground ball to the middle infield if the infield isn’t playing in.
Runner on 2nd, No Outs: We expect 1.10 runs on average
Runner on 3rd, One Out: We now expect only 0.95 runs on average
RESULT: The bunt reduces the success of the average inning by 0.15 runs, which means that if you bunt 10 times in this situation, your team would score 1.5 fewer runs than if you didn’t. This seems counterintuitive, since a sac fly or middle-infield grounder can score a player from third with one out. But, nonetheless, this sac bunt hurts the inning. This reduction is smaller than in the previous, but still relevant.
Sac Bunt, 1st & 2nd to 2nd & 3rd
This one is probably the biggest mistake of the three in youth baseball, because it reduces the team’s chances of having a BIG inning, and big innings often single-handedly win games. The reduction in run expectancy (RE) is only 0.06 runs, and so it basically wastes an out without improving the odds of scoring.
BUT — remember, that this is MLB data below, and the effect of the double play, which will wipe out a inning faster than anything, is very real. 1st and 2nd has the double play in order, whereas 2nd and 3rd does not.
In youth baseball, especially at 16U and below, this difference is especially important, as double plays are vastly less frequent. In the Major Leagues, when the double play is in order, a double play occurs about 15% of the time.
At youth levels, this might be 5% or lower, which means that 1st and 2nd will produce even more runs than we expect in the chart to our left, since a grounder to shortstop will most likely move the situation to 1st and 3rd with one out (RE = 1.13), rather than 3rd only with 2 outs (RE = 0.35 runs).
Getting the first two runners on is the exact thing we want in producing a big inning, and giving the opposition an out hurts that goal, even more so in youth baseball than MLB baseball.
Run Expectancy Is Important!
It tells us why bunting may not be the right choice in most situations. There may be situations where a sacrifice bunt still makes sense, and bunting for hits is NOT included in this analysis of why bunting is bad. Bunting for a hit is completely different, as the goal is not to give the opposing team an out in exchange for a base.
Outs are the currency in baseball — making an out is the worst thing a hitter can do, and NOT making an out, of any kind, provides tremendous run-scoring value for a team, even just a walk, hit by pitch, or single.
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Originally published at www.danblewett.com.