Filter posts by...
In-game_Strategy
Tuesday, May 15, 2012
David Ortiz shows that he’s man enough to bunt. Surprisingly, this is an extremely rare occurrence, as Ortiz, in his career, has only five bunt hits on ten bunt attempts entering today, and now 6 for 11 for a 55% success rate.
The question is how often can a hitter bunt to make it more effective for him to produce runs, than to work the count and/or swing away. We know that Ortiz has a career wOBA of close to .400 when he doesn’t bunt, which is where you will find great hitters.
With the bases empty, the wOBA equation gives a weight of almost 0.9 for a single with 0 outs and under 0.8 with 2 outs. So, in order to get a .400 wOBA (and breakeven for a great hitter), a batter would need to successfully lay one down about 45% of the time with 0 outs, and 50% of the time with 2 outs.
Ortiz as I said, is a career 55% success rate. That is of course based on only a sample of 11 attempts, so we really don’t know how good a bunter he is. Any hitter who can lay one down over 50% of the time against the shift should simply keep bunting. As Jeff notes, it’s the batter’s equivalent of the IBB.
The Mariners, like most baseball teams or every baseball team, shift the infield for David Ortiz. In the fifth inning today, Ortiz dropped a perfect bunt down the third-base line for a single. Fans eat it up when players do this, even though it takes the bat out of their hands. When players get intentionally walked, they get the bat taken out of their hands, and fans can’t stand it. Fans are so weird.
Anyway, a player once told me that he could lay one down 100% of the time if the pitch were over the plate, and 50% of the time if the pitch was off the plate. That would mean that roughly 75% of the time, a great hitter should be able to lay one down. Even if this player is exaggerating, let’s say it’s 80% of the time he can lay one down if it’s over the plate and 40% if it’s not. That still sets the success rate at 60%, and that’s if the hitter bunts equally if the pitch is a strike or not.
What if we’re trying to be realistic and more complex? How about if it’s a strike, he can lay one down 70% of the time. If it’s off the plate, he can lay it down 35% of the time. And let’s say that he’ll attempt the bunt on 90% of the strikes and 30% of the balls. And let’s say pitchers throw an equal number of balls and strikes. That gives us a success rate of .9*.7*.5 + .3*.35*.5 all divided by .9*.5 + .3*.5 equals 61%.
So, we should be setting our expectation that a great hitter would lay one down and be successful 60% of the time, which would give them a wOBA of .500 to .550, and turn them into Barry Bonds.
That we don’t see this happening is a huge inefficiency among great hitters who are shifted. These batters, when shifted with no runners on, should bunt, bunt, and then bunt some more.
Among average to poor hitters, the breakeven point is that much lower. Whereas the breakeven point for a great hitter is 45% to 50% success rate on bunts, for an average hitter, it’s all the way down to close to 40%, and for a bad hitter, it’s around 35%. And, we’d expect average hitters to be able to bunt better than great hitters (because of experience), and similarly, the bad hitters may be the best bunters (because they need to learn whatever to survive as hitters).
So, to shift against an average or worse hitter is about the worst defensive alignment you can imagine, and the average or worse batter needs to bunt any chance he gets, when the bases are empty.
Wednesday, May 02, 2012
By , 06:25 PM
Top of the 9th, Rockies are up by 2 with a runner on first and 2 outs, Matt Kemp is up against a very good RHP, Betancourt. Tracy orders the IBB. I almost threw up.
Saturday, March 31, 2012
He says:
Finally, there is one statement that Bill makes that I want to point out that I disagree with. Bill wrote, “John wants to focus on groundballs and short line drives, which, again, is a legitimate and constructive step toward understanding the problem, even though I think it is being used to create an exaggerated estimate of the shift’s effects.”
I totally disagree with the part starting with “even though”. We are not trying to create an exaggerated estimate. We are presenting the facts that we have. Right now Baseball Info Solutions is undergoing an extensive video review effort to record every plate appearance and every batted ball where a Ted Williams Shift occurred in the last two years. It’s a massive effort.
Our data currently splits our Shift info between Ted Williams Shifts and Other Shifts for grounders and short liners only. We did these first because it would lead to the quickest initial significant results. Now we are going back to review all plate appearances, not just the grounders and short liners, to split our shift data between these two types of shifts. This has nothing to do with trying to exaggerate the data and everything to do with trying to develop useful research.
I think most people would agree that a Ted Williams Shift is more likely to affect grounders, short liners and bunts than it would affect a player’s flyballs to the outfield, how often he strikes out or walks, or even how often he hits a pop-up that gets out of reach of a fielder playing out of position.
I disagree with Dewan, not only in his contention of what “most people” think, but also that it’s irrelevant what most people think. Since the defense has proposed a MASSIVE change in environment for the batter, the batter will change his approach in response. What’s the effect of BB and K and HR? I DON’T KNOW! And, that’s an important thing to know. And how about on flyballs? I DON’T KNOW! And that’s an important thing to know.
Dewan is taking a very myopic view that the focus should be almost entirely on grounders and short liners, while completely ignoring all the other plate appearances...as if they are immune to the change in environment.
John may very well be proven right in the end, but he is 100% wrong in his process to exclude them, or even try to reason why they should be excluded.
Now, it’s good that he says he will go back and look at ALL plate appearances, and not just the grounders and short liners. Once he does that, then we’ll take a big step forward.
Sunday, March 11, 2012
By , 03:15 AM
I was going to address this in the Kinsler thread, but I decided to start a separate one. I have always thought it ridiculous for a team to concern itself with finding someone for a particular lineup slot, as in, “We really need a leadoff hitter,” or, “We are so happy with this acquisition because we now have a proven leadoff hitter,” or some such nonsense like that.
You get the best player you can and then you construct the best lineup from what you have. It really doesn’t matter whether you have a “true leadoff hitter” or a “true cleanup hitter” or not. It doesn’t matter at all.
I am not even sure what that means anyway, so let’s try and be more specific in terms of what question(s) we want answered.
I’ll pose two specific questions which we can answer, more or less, quantitatively and which relates to this issue.
1) If we have someone who has lots of speed, or doesn’t have lots of speed, how much can we leverage that attribute (or lack thereof) by placing him strategically in the lineup?
For example if we want to acquire a speedy player that is worth exactly 2 WAR, how much more would he be worth if we plan on putting him at the top of the order versus the bottom of the order, and in doing so, we don’t affect anything else?
One way to answer that is to see how many runs per game we gain when we go from a slow runner to a fast runner at the top of the lineup versus how many runs we gain when we go from a slow runner to a fast runner at the bottom of the lineup. This is very similar to how we figure LI in a game. We compare the impact of a good player or good event to a bad event in terms of WE, at various points and situation in the game.
I took a typical Rangers lineup from last year and ran my sim with Elvis Andrus either batting second or batting 8th, as a great base runner (which he is, so I left his base running projection alone) and as a terrible base runner, like a Prince Fielder. I actually use a 1-5 scale in my sim, so I went from a 5 to a 1. This is not including SB/CS - only advancing on hits and outs by following hitters when on base. I cannot remember if it includes advances on potential WP and PB. My sim probably captures 90% of the value of base running.
I ran 500,000 games of the Rangers playing a team with a RHP. It doesn’t really matter who they played or who the opposing pitcher is. It might matter a little that it was the Rangers with a good middle of the order.
Anyway, with Andrus batting second, as a fast runner, they scored 4.167 rpg. As a slow runner, 4.101 rpg, for a difference of 9.9 runs per 150 games. That is around what we expect from the difference between a great and poor base runner in general (an average slot in the order), so I suspect that my sim is undervaluing base running a little, or maybe it will find around the same difference in any slot, in which case, it is probably capturing most of actual base running value in real life.
Nope.
As a #8, the difference between Andrus as a great (5) and terrible (1) runner is only 4.65 rpg. So yes, you can leverage base running with batting slot, but, this is the most extrme situation possible. My guess is that for an actual team making a decision about a player based on where they think he will bat in the order, or what other players that have slotted in the lineup, we are only talking about 1-3 runs per season.
For example, if a team is indeed looking for a lead-off or second place hitter, and player A has the same value/projection as player B, but player A is a speedster and player B is just average (and assuming that their hitting profiles are the same), how much more should they pay for player A. I think Player B is probably going to be worth only 1 to 1.5 runs more than Player B given that you are leveraging him the leadoff or second slot. I think that most teams is going to way overvalue that speedster. IOW, you should pretty much forget about the fact that you are looking for a player to fill a certain lineup slot. Like many things (clutch, batter/pitcher matchups, etc.) Use it as a tie breaker only.
2) Same question as #1, but what if we changed a player’s OBP by 20 points by adding walks only? How much can we leverage that by batting him lead off rather than 8th? We’ll use the same method.
I did the same thing with the sim. This time I used Kinsler in the leadoff slot or the 8th slot and I ran the sim (500,000 games each) for his normal projection at the end of last year and with his OBP jacked up by 20 points by adding around 10 walks per 500 PA.
Kinsler batting leadoff, normal OBP: 4.146
Kinsler leadoff and an OBP 20 points higher: 4.201.
Gain: 8.25 rpg (Tango, how does that compare to what you would expect for an average player on an average team in an average slot?)
Kinsler batting 8th, normal OBP: 4.163 (why you don’t bat him 8th, BTW - you lose 6 runs a year!)
Kinsler leadoff and an OBP 20 points higher: 8.55 rpg.
Wow, interesting. You cannot leverage his OBP by batting him at the top of the order. I am not sure why. When my computer frees up, I’ll run some more game. Maybe I’m getting too much random fluctuation in 500,000 games. My guess is that 1 standard error even in 500,000 games is still like 5 runs per 150 games, so really, a comparison of 8.55 to 8.25 doesn’t really tell us anything.
I’ll try and run some more games with the speed thing too. Even though the results seem reasonable, there is too much sampling error there too for the difference to be reliable to any degree…
Saturday, February 18, 2012
Jeff looks at IBB rates, and how they affect the non-IBB walks.
Wednesday, February 15, 2012
Matt:
I made up a simple card game. There are two cards, A & B. I put one of them face down and you try to guess which card it is.
If it is A and you guess A you win $1 If it is A and you guess B you lose $3
If it is B and you guess B you win $3 If it is B and you guess A you lose $1
Obviously, me playing A is a much better move than playing B. I only have to give you $1 if you win and I can gain $3 if you guess incorrectly. Of course, you know that so if I always played A you would always guess A and clean me out.
I know game theory centers around finding the approach that makes your opponents decisions irrelevant. I did the math and came up with this:
My best strategy is to play A 50% of the time and B 50% of the time. Your best strategy is to guess A 75% of the time and B 25% of the time.
I think I did this correctly, but the result is so counter-intuitive that I’m wondering if I didn’t make a mistake.
MGL:
Yes, your answer is correct. I don’t know why you think it is counterintuitive. I must guess A enough to keep you from taking advantage of the fact that A is the best choice for you (if I played randomly or incorrectly too much toward B). You must not play A more than B because otherwise I would simply guess A all the time. Like the poker player who bluffs even slightly too much, his perfect opponent should always call a potential bluff.
In this case, it just so happens that because the A and B payoffs are “balanced” you must play A and B 50/50 and I must play the ratio of the payoffs (3/1).
Friday, December 23, 2011
This was from Tippett, and a followup.
In a blog entry the next day, we offered the opinion that this was a poor decision with the league leader in strikeouts on the mound. We didn’t get into the details then, but we will now.
In last year’s essay, we pointed out that 11.4% of all plate appearances in double-play situations result in a ground ball double play. Not all of these plate appearances see the batter put the ball in play, though, and when we subtract the walks, hit batsmen, and strikeouts, it turns out that 15.4% of balls in play produce GDPs.
If you DON’T send the runner on a 3-2 pitch, the chance of getting a ball in play that produces a GDP is a little over 5%. That’s because 15% of balls in play result in a GDP and batters put 3-2 pitches in play about a third of the time.
So what are the chances of a double play if you DO send the runner on a 3-2 pitch? Last year, we estimated that probability at about 5.5% based on the frequency of strikeouts, a typical caught stealing percentage, and the small chance that a ground ball up the middle will produce a GDP even with the runner going.
In other words, the overall averages showed a rough balance between sending and not sending the runner, leaving the decision to an evaluation of the skills of the specific players involved.
But that was for the case where the only runner was on first base. What about the first-and-second situation?
Wednesday, December 21, 2011
Mike does a great job at identifying situations that are disproportionately hit and run situations:
Finally, we arrive at the definition used for a hit-and-run situation in this study: (1) runner on first, bases not loaded, (2) none or one out, (3) a ball-strike count of 0-0, 1-0, 2-0, 1-1, or 2-1, and (4) the team leading or trailing by four runs or less. If the runner went on the pitch and the batter swung in such a situation, I will consider it a likely hit-and-run play.
And gives us these results, among many others:
Teams that attempted the hit-and-run play scored 0.11 runs on the play and 0.69 runs in the remainder of the inning on average, compared to 0.17 runs scored on the play and 0.70 runs in the remainder of the inning by teams that did not attempt the hit-and-run play in hit-and-run situations.
There are a few biases here that need to be controlled, before we can compare the .69 to the .70 (i.e., a wash). Later in the article, Mike does an excellent job of reviewing most of them, and adjusting for them. What he does there is exactly the kind of thing a saberist should be doing: identifying reasons for bias, and adjusting for it, as best you can.
He ends up with this huge finding:
Thus, the advantage for attempting a hit-and-run play during 2003-2011 appears to be about .061 runs on average.
That is a much larger number than I expected when I embarked on this research. I have attempted to remove as much of the selection bias as I could reasonably identify. It is possible that I have overlooked some bias or used a mistaken assumption, but every direction from which I came at the analysis pointed to the hit-and-run being a positive offensive play in most circumstances in which it was attempted.
I agree that that number seems simply too high. Adding .06 runs on one PA is the equivalent of one of the best hitters in baseball. Basically, it’s too big to be taken as the final number.
One bias that he noted early on, but that it doesn’t look like he adjusted for, is that a hit and run is in neutral or moderate hitter’s counts. So, we expect more runs on that basis. This will probably account for .03 or .04 runs of bias. But, Mike says:
The ball-strike count also plays a role. The more favorable the count is to the hitter, the less likely that the batter will be forced to swing at a pitch he does not like. On the other hand, the same is true if the batter is not protecting the runner, and in that case, he may be more selective and take more powerful swings.
But his chart ends up with actually a net benefit for the hit and run. Which is confusing me.
In any case, it’s a great piece of research, and hopefully will inspire more people to take up the cause. You really couldn’t ask for any more for an initial piece of work. It was a real pleasure to read.
Tuesday, December 20, 2011
If you are going to compare to a baseline, you CANNOT compare to zero. You have to compare to the actual hitter’s true talent level. It’s not the average hitter that bunts, but a below average hitter. So, we EXPECT to see a negative win value relative to the average hitter, not only on bunts, but on non-bunts too.
Glove-slap: Mike.
Friday, December 16, 2011
Dewan has some data for us.
Batting Average by Zone, 2011
Non-Sacrifice Situations
Zone 1 .246
Zone 2 .412
Zone 3 .164
Zone 4 .139
Zone 5 .520
Zone 6 .720
Overall .438
So, a .438 batting average if bunting for a hit, with no one on base, or runners on base and two outs. What’s the breakeven point?
Well, a single with no one on adds around +.25 runs, while an out costs .16 runs. That gives us a break-even point of .390. That is, if you bunt for a hit with no one on base, and you have a .390 batting average, you are a league-average hitter.
Players are bunting for a .438 average, which means they are picking their spots pretty well, bunting when they think they have a .375 to .500 batting average.
***
Note that with a runner on base and 2 outs, the batting average breakeven point shoots way up. Here are some numbers (all with 2 outs):
runner on 1B: .500
runner on 2B: .670
runner 1B/2B: .580
As you can see, only the absolute very best bunters should EVER bunt with runners on base and two outs. Either that, or the fielders have to be playing very deep.
So, I’d like to see those numbers, of bunt batting average with no runners on base, and with runners on base and 2 outs. We should see that .438 be pretty different, something like .420 with bases empty and at least .500 with runners on base.
Thursday, December 01, 2011
By , 11:55 PM
http://www.nesn.com/2011/12/bobby-valentine-plans-blending-sabermetrics-with-baseball-experience-to-make-decisions-with-red-sox.html
I could end up being wrong, but I have a feeling that Bobby V may be the first manager we will see that actually uses correct sabermetric principles. I think that the only reason Boston would hire such a controversial manager is for that reason - they finally found a manager who is astute and progressive enough not to think that he knows everything about baseball and is willing to throw away half of what he thinks he knows. I have a feeling that he is going to work very closely with James, Tippett, and the rest of the Sox’ sabermetric department, and that we will see (or not see) things that we have never seen on a baseball field, other than fake noses and glasses…
Friday, November 18, 2011
MGL’s terrific guest piece at BPro:
In any case, it is easy enough to see how these starters pitched after they were allowed to bat. Remember that, on average, the starter pitched another 1.42 innings after his stint at the plate. What was the average TAv against over these 1.42 innings, again, after removing all pitcher batting? Remember, these were .258 pitchers for the season who had pitched to the tune of .221 so far in the game. They were also facing the lineup for the third time on the average; if there was no carryover effect, we would actually expect them to have pitched worse than their normal .258, all other things— like the park, weather, and opposing batters—being equal.
So how did they pitch? (We’re going to exclude the ninth inning for the reasons stated above.) They pitched to the tune of a .251 TAv against (after adjusting for opponent batter pool)—better than we expected, but quite a bit worse than their .221 prior to being allowed to hit. Coincidentally, .251 is almost exactly the same as the average reliever, who is a .250 pitcher. So leaving your “hot” starter in the game yields no advantage over replacing him with an average reliever, unless he is a considerably above-average pitcher.
What about when the starter was taken out of the game for a pinch hitter? How did the relievers pitch in the very next inning? They allowed a TAv of .243, which is around what you would expect from a late-inning reliever.
So let’s recap the last few paragraphs. When a manager allows his starter, who is an overall .258 pitcher but has thus far pitched at a .221 level, to bat in a high-leverage situation (LI > 1.5) after he has pitched at least five full innings, he pitches at a .251 level (TAv) for the next 1.42 innings, on the average. When the starter is removed in the same situation, relievers pitch at a .243 clip for at least the next inning. Clearly, there are some starters who are good enough to post a sub-.243 TAv later in the game, but remember we are asking the question, “What if we were to remove all starters when they have completed at least five innings on the mound and they are due to bat in a situation where the LI is greater than 1.5?” Whatever our answer is, we can perhaps leverage that one-size-fits-all strategy by letting some pitchers (aces) bat for themselves and continue to pitch. Of course, you are still giving up the value of using a pinch hitter, which is almost the whole point of the strategy. In other words, a pitcher would have to pitch a heck of a lot better than .243 or .250 in order to justify allowing him to bat. This brings us to our next, vitally important question:
...
Also remember that each team averages around 28 of these decisions per season, and the starter ends up batting around 12 of the 28 times. Multiplying 12 times .032 wins yields a gain of .384 wins per season per team by virtue of this simple strategy.
If one were to argue that such a strategy might tax a bullpen or hurt the confidence or ego of a team’s starting pitchers, remember that the average subsequent IP whenever a starter is not removed for a pinch hitter is only 1.42. That means that we would be transferring a total of 12 * 1.42, or 17 IP, from the starters to the bullpen, an average of around three fewer innings per starter and perhaps one or two more innings per reliever. This hardly seems like a crisis.
A gain of 0.384 wins on 17 innings? That’s a gain of +.200 wins per 9 IP, which is like replacing an average pitcher with Roy Halladay.
Saturday, November 12, 2011
So speaks Bob McClure, with another HR from Laurilia:
Banny had a heck of a year [in 2007], but it got in his head that the way he was pitching wasn’t good enough. You’re talking about a guy who was third or fourth in Rookie of the Year voting and who won 12 games. He said, “I’m giving up too many fly balls.” I said, “Yeah, but they’re mis-hitting them, because you have deception and because of the way your pitches come in.”
He tried to get guys to do this and do that. He got into the rotation of the baseball. He got into where hitters hit their extra-base hits and what the best pitches are to throw to them. He started subscribing to all of that and getting into the terminology. I mean, he’s a very bright kid; he went to Stanford. He got into things like how the ball was turning, and to me, it’s not that complicated.
As a pitcher, what I’m trying to do is keep you off balance just enough, and locate my pitches. I’m trying to get ahead in the count, keep you off balance, and make pitches. That’s all I’m trying to do. I don’t think it’s any more complicated than that. The first three pitches are the most important ones you throw. If you can get to 1-2 on three quarters of the batters you face, you’re probably going to have a good game.
Banny got a little overboard and tried to do more than he was capable of doing. The next thing you know, his walks go up and his hits go up. He’s trying to sink the ball instead of what he was doing in the first place, which was commanding his fastball and his cutter. It kind of turned into a mess.
Banny was convicted in what he was doing and I don’t think anyone was going to change his mind. Now, that being said, I think that if he was 100-percent healthy… he had some very good points in wanting to sink the ball a little bit and get the ball on the ground a little more. He could maybe not take as many pitches to put a hitter away by getting them to hit it on the ground. He had some very good points, it’s just that we’re dealing with someone whose shoulder, here and there… as far as health, at times it was difficult to do enough work in order for him to get where he wanted to be.
Friday, October 28, 2011
Here’s the situation. It’s the bottom of the 10th, the defense is up by 2 runs, there’s runners on 2B, 3B, and there’s 1 out.
There’s a GB to third base, and a decent chance for a play at the plate, or a sure out to first base. What do you do?
You need to know the chance of winning in those situations. Let’s start off with the win probability before the ball is put in play (and average batters following, which is NOT the case anyway, with Pujols and Berkman due up): Markov says .301 chance for the home team. You don’t really need to know this, but it just sets it up for you.
You get the sure out, let the runner on third score, and now you have a runner on 3B, up by 1, and 2 outs. Home team has a .172 chance of winning.
If instead you go home, you have these two outcomes:
everyone is safe: up by 1, ONE out, runners on the corners, chance of home team winning is .478
runner out at the plate: up by 2, two outs, runners on the corners, home team is .107
So, that’s the choice facing Beltre: go for the sure out for a .172 chance of losing the game, against try for home, and get into either a .478 chance of losing if he doesn’t make the play (.306 change in win probability) or get into a .107 chance of losing if he does (.065 change in win probability).
The breakeven point is 82%. He has to make the out at home 82% of the time in order for that play to breakeven. If he thinks he can make that play 90% of the time (chance of losing for Rangers goes down to .144), then he should go home. If he thinks he can make that play 75% of the time (chance of losing goes up to .200), then he should get the sure out at first. If it’s somewhere in-between, then it’s pretty much a gray area.
Things get more complicated with Pujols on deck. Going for the sure out at 1B allows Pujols to be placed at first base. According to page 306 of The Book, with the defense up by 1 in the bottom of the last inning, and runner on 2B and 2 outs, the defense BENEFITS by walking the batter, if his true talent wOBA is 120% that of the guy on deck. In his last three years, Pujols has a .418 wOBA, while Berkman is at .380, or Pujols is 110% of the guy on deck. When you include the platoon disadvantage for Pujols, it becomes even more of a reason to not walk Pujols. But, let’s just say there’s enough uncertainty in our estimate of Pujols’ true talent and Berkman’s true talent in a Game 6 do-or-die situation that maybe Pujols was at least 120% the hitter that Berkman was, and so, it’s a net benefit to the defense for not wanting to face Pujols.
I’d love to hear Beltre’s (and Washington’s I suppose) reasoning in wanting to go to first on that play.
Probably a dozen plays at least to talk about. I’m going to bed, so I’d be interested to hear what you guys think.
Matt Holliday picked off third is what sticks in my mind.
Wednesday, October 26, 2011
By , 02:56 AM
The overwhelming consensus on BP, FG, this blog, and lots of other sites I have visited is, “No!” How did all these people come to that conclusion? Because it failed and it “cost” the Cardinals a good chance to tie or win the game. Does that make any sense? Of course not. Not in a rational sense. Can the outcome of a play that swings the percentages one way or the other maybe 1 or 2% inform us of the “correctness” of the play? Not in one single instance and not enough that a human being could possibly discern even after dozens or even hundreds of such plays. But people are irrational beings. When it comes to sports, they are out of their minds irrational.
So, can one determine whether running was correct in that instance without “running the numbers?” Not a chance. One can take a guess and be right 50% of the time, I guess. If you are a good sabermetrician, you might be able to do some quick mental calculations and maybe come up with the right answer with some degree of certainty, as long as the actual answer is not particularly close (i.e., the WE from each alternative is not a dead heat).
So what are all those people doing with their, “opinions?” I have no idea. To me, opinions should be reserved for ice cream flavors, what color car you like, and whom you would choose for your dream date. To me, there is no such thing as an “opinion” on which of two strategies yields the highest win expectancy. That is a matter of fact. That seems to be lost on 99.7% of the population.
So what is the right answer? I’m not going to tell you because I don’t know. I could know if I “ran the numbers” but I don’t want to deprive some aspiring sabermetrician of doing the work and making a name for himself.
OK, in all honesty, I can’t “know for sure” because I can only estimate the value of the requisite variables. Some more than others. But when the smoke clears, I could tell you one of three things with almost exactitude:
1) It is clearly a “run.”
2) It is clearly a “no run.”
3) It is close, depending on the exact values of all the variables, so we’ll just call it a draw.
Nowhere does my opinion matter…
Tuesday, October 25, 2011
There are different variations of the “double walk”. The first time I read it was from Bill James’ Baseball Abstract, but according to Peter Morris, it originated with a sportswriter in 1937. Anyway, one version is that a batter has the option to decline ANY walk, which resets the ball count, but maintains the strike count. A second walk moves the batter to second base: the double walk. (Any runners that have to be forced over are forced over.)
One version that we discussed a few years ago focused only on 4-0 walks walks.
The rule is simple: Any 4-0 walk, intentional or not, results in a two-base penalty. If you have a runner on 2B, the 4-0 walk gets you runners on 1B and 3B. If you have a runner on 3B, then it’s guys on 2B and 3B. And, with runners on 2B and 3B, the batter goes to 1B, the runner on 2B stays put, and the runner on 3B scores. Under this scenario, how often would a pitcher not give the batter at least one strike?
Of course, you’re going to have to tie this in with a change to hit batter, as you don’t want to avoid the 4-0 walk by plunking the batter. Therefore, a hit batter (or perhaps a no-strike hit batter) counts the same as a 4-0 walk.
The law of unintended consequence may creep in. Batters will look to get hit, the pitcher will groove too many in, etc.
The challenge is out. Give me your proposals, and please, don’t maintain the status quo, or knock down every thing you see. This is a brainstorming session. Be creative.
Monday, October 24, 2011
By , 08:10 PM
I’m pretty busy getting ready to head back west tomorrow, but I’ll probably watch the game and pop in here from time to time. Hopefully, you guys can keep a lively discussion going…
Sunday, October 23, 2011
By , 08:05 PM
Saturday, October 22, 2011
By , 06:44 PM
Here we go again, in Texas!
from Amazon
Recent comments
Older comments
Page 1 of 344 pages 1 2 3 > Last »Complete Archive – By Category
Complete Archive – By Date