Where and why bunting sometimes is a decent idea, mathematically

[PMDawg]

You really just don't get it. Your scenario that increases chances of scoring 2 runs also decrease the chances of scoring 1 run. Statistically, the reason the odds of scoring zero go up when bunting is because the odds of scoring 2 or more go way down. Not all of that goes to increasing the, "1-run" probability, a smaller portion of the redistribution goes to, "zero runs". You are getting hopelessly lost in the, "at least 1", or, "more than one" loop.

To grasp this, you only have to consider, "what is the greatest chance of scoring the one run I need this inning?" It's not about maximizing the total potential of, "expected runs". It't about maximizing the chances of getting 1 run. You are making a false argument that, "the better odds of scoring more than one" precludes the possibility that the odds of scoring just one are better in certain circumstances. That is an incorrect assumption, statistically.

I dont think you could be more wrong if you wanted to. But carry on making a fool of yourself.

[Smitty]

We lead the SEC in OBP and RUNS SCORED. And yet, we are "the worst team".

No. Mostly the best teams are not bunting. And we've played bs teams.

[smootness]

I do think it's something Cohen has to look at. It seems as though for the most part, bunting correlates with a lack of talent. Teams with less hitting talent are trying to play for single runs more. If this is the case, we need to evaluate the kind of talent we have.

Any manager who refuses to look at the actual statistics showing average results of certain decisions is hurting himself for no reason.

It would be like a basketball coach telling the center who shoots 8% from 3 to continue going out there and launching them. 'I don't care what these advanced stats show, I'm going on feel.' We would crucify that coach, for good reason.

[blacklistedbully]

Here's a link to a pretty good article that discusses ERT, run expectancy, and actual data from real games. It's a long and detailed read, and parts of it can be cherry-picked to support either side. http://baseballanalysts.com/archives...al_analy_1.php

One of the things I find interesting is that, "actual events" have out-performed the ERT tables that were based on simulations. Mostly this is attributed to managers taking into account the parameters of the specific situation, such as who is on base, how many outs, how is at bat, are we playing for, "1 run" versus, "maximizing run potential", etc.

There are also sections that deal with the legitimacy of choosing a, "one run strategy" over a, "max run potential strategy", both as judged by ERT tables and actual occurrences in MLB over 2 decades. Of course, it's an inexact science, as there are simply some potential factors we just can't possibly know, but it does give us some interesting data.

[blacklistedbully]

I dont think you could be more wrong if you wanted to. But carry on making a fool of yourself.

Look, the only one coming across as a fool right now is you for being a complete asshole by bringing unprovoked personal insults into the thread. Clearly, this is still a subject of hot debate, and one that has intelligent people arguing on both sides.

But carry on making an ass of yourself.

[smootness]

That article shows that your probability of scoring a run decreases from .432 to .414 by bunting the guy over to second.

But I was never talking about a 'max run potential' strategy. You seem to have confused my saying 'at least one run' with 'more than one run'.

But either way, your last post confused me as to what you are even claiming the stats show, and we're going nowhere, so I'm just going to bow out now.

[Smitty]

http://www.boydsworld.com/data/ert.html

Bunting a guy from 1st to 2nd decreases your chances of scoring. And that assumes 100% bunt success. When factoring in bunt fails it clearly shows the sac in most situations is bad.

[blacklistedbully]

That article shows that your probability of scoring a run decreases from .432 to .414 by bunting the guy over to second.

But I was never talking about a 'max run potential' strategy. You seem to have confused my saying 'at least one run' with 'more than one run'.

But either way, your last post confused me as to what you are even claiming the stats show, and we're going nowhere, so I'm just going to bow out now.

You have to read the whole article. It appears you read to a part that supported your POV, then stopped. I found some that supported mine, then kept going, and learned a great deal more than I knew when I started this thread, some that made me question my original line-of-thought as well.

In the end, the data seems to suggest that bunting is sometimes a viable strategy if the manager or coach is doing it in the right spots for the right reasons. It does seem to suggest that part of that strategy can include whether a manager feels his team needs a higher probability at 1-run than he needs to score multiple runs. It's not an all-or-nothing thing.

Both sides on this thread make some valid points. Very general ones we can probably all agree on is that sac bunting can be WAY overdone and hurt a team's chances of winning a game, and that there can absolutely be scenarios where it makes sense to play for a single run by incorporating the sac bunt, even though doing so statistically reduces the average, "expected runs" based on the simpler ERT tables that some here want to use.

[Todd4State]

No. Mostly the best teams are not bunting. And we've played bs teams.

Everybody else has also played mostly BS teams.

[LiterallyPolice]

http://www.boydsworld.com/data/ert.html

Bunting a guy from 1st to 2nd decreases your chances of scoring. And that assumes 100% bunt success. When factoring in bunt fails it clearly shows the sac in most situations is bad.

I for the most part agree with you. But obviously these runs tables aggregate so much data that they "smooth out" any individual characteristics of a situation that may change things. For example, I would like to see what the run tables would look like if you had a .200 hitter coming to the plate that hits a lot of ground balls. I'd like to see if bunting in this situation would maximize your expected runs.

Is data like that out there anywhere?

[blacklistedbully]

http://www.boydsworld.com/data/ert.html

Bunting a guy from 1st to 2nd decreases your chances of scoring. And that assumes 100% bunt success. When factoring in bunt fails it clearly shows the sac in most situations is bad.

From the article:
"Table 4 provides a little more evidence of why managers bunt. The probability of scoring a run decreases only from .432 with a runner on first and no outs to .414 with a runner on second and one out. As these values represent an overall average of all games, one can imagine that it many cases it surely increases the probability. Once again we can generate these tables by batting order position as a surrogate for the multiple batter sequences that can produce a huge variation in expected outcome."

Do you get that what the author is saying is that, on overall average the chances of scoring one run decrease so little that a manager/coach must consider who his personnel are at the time to make the best call? In other words, depending on who is OB, who is Ab and who is coming after, the odds of scoring the one run can, in fact be a little better by bunting.

It simply does not make sense to base the decision to bunt or not bunt based on an overall ERT table. When you start to dig deeper into how the numbers change based on batting order and/or position it get's even murkier. Now consider again that the coach/manager may be privy to some info we are not, like how the specific players involved are doing today, or how they've been doing recently compared to year-to-date.

For example, maybe the coach/manager knows a certain player with a low average has actually been smoking the ball lately, just right at people, or that another has a great average, but has been getting a lot of lucky Texas-Leaguers, or benefiting from, "finding the hole" on steal attepts and/or hit-and-runs, etc. Maybe he knows his 3-hitter looked out-of-it in the cage pre-game.

There are any number of things we may not know that the coach/manager does, so we might should consider that when we evaluate whether or not he is making the right call. This is not to say that Coach Cohen isn't making mistakes. In fact, I tend to think that he does call for the sac bunt entirely too often, and in what appears to be, based on what I perceive the circumstances to be, the wrong time.

But I am not among those who think the sac bunt is almost always a bad idea. And I am not one who thinks these decisions should be based soley on ERT, particularly those very general ones I suspect most anti-bunt folks are referencing.

[Smitty]

Everybody else has also played mostly BS teams.

Has everyone lost to the SWAC?

You are the one trying to put words in my mouth. For the most part the best teams in our league are at the bottom of the sac list and the worst teams are at the top.

[blacklistedbully]

I for the most part agree with you. But obviously these runs tables aggregate so much data that they "smooth out" any individual characteristics of a situation that may change things. For example, I would like to see what the run tables would look like if you had a .200 hitter coming to the plate that hits a lot of ground balls. I'd like to see if bunting in this situation would maximize your expected runs.

Is data like that out there anywhere?

Closest thing I've seen so far are a couple of the tables on the link I reference earlier. It also goes into the, "bunt success rate" one would think necessary to justify the sac bunt attempt as a method to achieve at least 1 run as opposed to maximizing potential runs, something you brought up in your first post, I believe.

[Todd4State]

Has everyone lost to the SWAC?

You are the one trying to put words in my mouth. For the most part the best teams in our league are at the bottom of the sac list and the worst teams are at the top.

Has everyone else beat Arizona twice and is ranked 22nd in the country right now?

I didn't put words in your mouth at all. YOU said the WORST teams are sac bunting more and then put up the stat that shows that we lead the SEC in SAC bunts. I pointed out the FACT that we lead the SEC runs scored and OBP. And now you're trying to pretend like you didn't really say that the worst team are sac bunting and hope that everyone is too stupid to realize it. Either way you try to paint it, you're still wrong.

In fact, we are also currently 35th in the country in batting average, second in the country in OBP, and 22nd in the country in runs scored per game out of 300 teams. We're also 89th in the country in slugging percentage which is not stellar, but more than respectable considering we've been without Collins most of the season and Rea and now Humphreys have missed significant time.

The REAL issue right now is the bullpen.

[Smitty]

Todd gonna Todd

[Bucky Dog]

I believe I can end this discussion once and for all if:

1. Smitty agrees that there is at least 1-2 situations in a game where the bunt is absolutely the right call.
2. The Rest of us agree that Cohen over uses the bunt, and in situations where it is not the right call.
3. Everyone agree that there will always be a few "gray" areas where the decision to bunt or not to bunt can debated.

With that said, UCLA won the NC with this philosophy, but they had a team BA of like .250 and a team ERA of just above 2 if I remember correctly. They HAD to manufacture runs and the HAD the pitching to play that way. We have at least 3-4 guys in the lineup at any given time that can hit the ball out of the park. Players who can hit for average, and guys with speed. We do NOT have the superb pitching right now either.
So, IMO, let the players swing the bat and be aggressive at the plate. Steal bases and hit and run to put pressure on the other team but quit giving away so many outs during the game via bunt/bunt fail attempts.