Tangotiger Blog

Monday, June 03, 2019

Ballast of Swing Rates

Ballast

?Regression Toward The Mean (RTTM) is an important concept, a critical concept.  But boy what a terrible name.  Michael Lopez proposed Reversion To Form, which is a definite improvement.  Regression has its own non-statistical definition, while Reversion really is about resetting the expectation from the observation.  And To Form, as opposed to Toward The Mean is also better, as RTTM makes it seem that the player's talent is changing toward the population mean.  Reversion To Form is really about setting our expectation of his talent level given the observation.

Bill James since the 1980s (and I can attest to this, since I remember everything he wrote, and I started reading him in the 1980s) has always used the term Ballast.  In a nod to his brilliance, he knew he needed to do something, without the concept of Bayes being at the forefront.  Which is why Bayes is beautiful, because we all use it, even without formality.

Priors

In order to establish the true rate of something based on the observation of that thing, we need to know something about the population that this thing was drawn from.  This is called your Prior Distribution.  The Prior requires both the mean and an amount.  For something like OBP, the mean is the league mean, say .330, but more importantly is the regression amount.  This is what Bill James calls Ballast.  It's how much your observation of a player needs to be pulled toward the population of all players.  For OBP, historically, it's in the 200-300 PA range.  For something like K/PA, it's much lower, while for something like BABIP, it's much higher.  In other words, the amount of Ballast you need is linked to how much that observation tells you about the player.

In sports, the skill that requires the least amount of Ballast is free throw shooting.  As a general rule, the less "layers" there is between the physical effort required, and the end-result, the less Ballast you need.  For free throws, there's the player at the free throw line, and the basket.  There's no defense, there's no varying distance.  In addition, because players are not chosen on their free throw skills (think Shaq), there's a naturally wide talent base to choose from.  The wider the talent base, the less Ballast needed as well.

For things like BABIP, it's a crucial skill for a pitcher, so they are selected for it.  (If a pitcher is hit too hard, he won't make it to MLB.)  So, we already have a tight range.  But in addition to that, you have the batter, the park, and the fielders.  There's alot of layers to get through from pitcher physical skill to outcome.  We need alot of Ballast.

Swing Rates

How about swing rates?  We break up the area at the plate into four regions:

• Heart of the Plate
• Shadow Zone
• Chase Region
• Waste Region

A hitter has a hitting approach.  A hitter does not really change his hitting approach, since that hitting approach is what has brought him to MLB in the first place.  However, he will tinker, and as the years go by, he will start to adapt.  So, while we suspect we're going to need more Ballast than free throw shooting, we also think he won't need as much as with Strikeouts.

Heart of the Plate

Let's look at the data.  For pitches in the Heart of the Plate, hitters will swing 70-75% of the time, with one standard deviation being about 6% (among our sample hitters, who averaged 480 PA).  Technically, I should be using number of pitches, not PA, but PA is an easier standard if comparing to other skills.  As it so happens, there's about a 1:1 relationship between number of pitches in Heart of Plate and number of PA.

Anyway, since one standard deviation is 2% and our observed is 6%, that gives us a z-score of close to 3.  Our Reversion To Form (or Regression Toward The Mean) is 1/z^2, or close to 12%.  The Ballast (or Regression Amount) is .12/.88*480 = 65.  In other words, we need to add 65 PA of Ballast to an observed swing rate for pitches in Heart of the Plate.

Shadow, Chase, Waste

Shadow Zone also requires about 65 PA of Ballast. However, since there are 1.7 pitches per PA in the Shadow Zone, the amount of Ballast of Pitches is closer to 40 Pitches.

Chase Region requires close to 40 PA of BAllast, or about 45 Pitches of Ballast.

Waste Region is 45 PA of Ballast or 125 Pitches of Ballast.  In other words, how a batter swings in the Waste Region is not as indicative of his approach in the other regions.  

For the sake of simplicity, let's add 50 PA of Ballast for each Region.

Adjacent Regions

Now, we can also learn about each Region by looking at the other three regions.  After all, how a hitter approach the Heart of the Plate can be informed by how he approaches the Shadow, Chase, and Waste regions.

As it turns out, the weighting is close to:

• 75% Heart
• 25% Shadow

The other regions are more iffy.  Guys like Votto, the less you Chase, the more you swing in the Heart.  For guys like Baez, the more you Chase, the more you swing anywhere.

Repeating for the other three regions, and we have the following for Shadow:

• 20% Heart
• 50% Shadow
• 30% Chase

In other words, the surrounding regions inform alot, but Chase is more indicative of the approach to Shadow, than Heart.

Chase:

• 25% Shadow
• 50% Chase
• 25% Waste

Chase is fairly equally informed from the other two.

Waste:

• 40% Chase
• 60% Waste

So, there you have it.  In order to establish the skill level of a hitter at swinging in each of the 4 regions, you apply a 50 PA Ballast, along with the weighting of the adjacent skills.  The aspiring saberist can of course focus more on pitches than PA, and be a bit more rigid in their approach.  And especially focusing on players who might have a new "established" change in hitting approach.

Sunday, June 02, 2019

Do Successful Zoners keep Zoning?

This study, Do Successful Launch Anglers keep Angling?, is one of my favorites. The framework is simple enough.  And since I like it, and it's simple enough, I will reuse it for this new study: Do Successful Swingers keep Swinging?  Eh, not as good a title.  How about: Do Successful Zoners keep Zoning? 

I am focused on the swing rates of batters in the Heart of the Plate (where they swing about 70-75% of the time) and in the Chase Region (where they swing about 20-25% of the time).

If you are a batter, and you need to chase fewer pitches, one of the ways that has to happen is that the batter is going to have to swing less in the Heart of the Plate.  But, not always.  Let's look at hitting genius Joey Votto who from 2016 to 2017 increased his swing rate in the Heart of the Plate from 73% to 79%, while at the same time dropping his swing rate in the Chase Region from 13% down to 6%.  Rest assured, this is not common.  His wOBA in 2016 was .418, while it jumped, as you'd expect, to .435 in 2017.

I'd call that a Successful Swinger.

More generally, I looked at the difference in swing rates between Heart of Plate and Chase, year to year.  Votto was +61% (73-13, rounding error) in 2016 and 73% (79-6) in 2017.  That's an increase of 13% (73-61, rounding error).  That was 5th best for the 2016 to 2017 time period, behind: Kike Hernandez, Aaron Altherr, Jed Lowrie, and Nick Castellanos.  ALL of them increased their wOBA from 2016 to 2017.  Indeed, the top 9, and top 13 of 14, all increased their wOBA.

Vottos, Successful Swingers

Among these 13 Successful Swingers, their wOBA in 2016 was .322, and .364 in 2017.

Now, the key question: did these guys keep Swinging, and, how did they end up doing in 2018?  Their wOBA in 2018 was .338, which SEEMS not much different than splitting the two previous wOBA years.  

I should point out that the league average in wOBA is not that stable in this time period.  Among the 235 hitters in my pool (min 150 PA in each of 2016, 17, 18, which itself is a selection bias by the way), the simple average wOBA

• 2016: .337
• 2017: .343
• 2018: .326

So, relative to league average, their wOBA was:

• 2016: -15 wOBA points
• 2017: +21
• 2018: +12

Therefore, the smarter approach did allow them to continue to perform better.

Did they maintain their new approach?  In 2016, their Heart-minus-Chase rate was +44% and in 2017 it was +56%.  League-average remember is +50%.  What happened in 2018?  +53%.  So, that's something.

The Successful Swingers kept (mostly) Swinging, and they did maintain (most of) their new success.  In other words, their new approach led to new results.  

Anti-Vottos: Adam Jones Group

How about the flip side, the anti-Vottos?  Adam Jones seems representative.  He swung at 86% of pitches in the Heart of the Plate in 2016, and Chased 37%.  In 2017, that went to 81% and 40% respectively.  So, a terrible change in approach, both swinging less in the Heart, and swinging more in the Chase.  His wOBA however went from .326 in 2016 to .352 in 2017.  Not really the kind of thing you'd expect.

Let's focus on the top 20 anti-Vottos, here's how it looks:

• in 2016, 74% swing in Heart, 20% swing in Chase, +54%, .312 wOBA
• in 2017, 72% swing in Heart, 26% swing in Chase, +46%, .329 wOBA

As you can see, a worse approach, but leading to better results.  What happened the following season?

• in 2018, 73% swing in Heart, 23% swing in Chase, +51%, .303 wOBA

So, relative to league average, their wOBA was:

• 2016: -25 wOBA points
• 2017: -14
• 2018: -23

Ah-ha!  So, guys changed their approach for the worse, but managed to do better in 2017.  Their new (worse) approach had their performance reverted back to 2016.

So, I think there is something here, that guys who improve their strike zone approach can continue to find success, while those who don't are simply going to continue to get worse.

That's one way to look at it.  The other way is that this is 20 batters.  All we have is an indication that something might be worth pursuing.  And that is where you, dear aspiring saberist, come in.  As Bill James noted: I can't do this all by myself.  

Let me recap the Vottos, as a comparison point, so you can see them similar to the Adam Jones group:

• in 2016, 68% swing in Heart, 25% swing in Chase, +44%, .322 wOBA
• in 2017, 76% swing in Heart, 20% swing in Chase, +56%, .364 wOBA
• in 2018, 73% swing in Heart, 19% swing in Chase, +53%, .338 wOBA

Friday, May 10, 2019

Convergence of Starting Pitchers and Relievers

?We were just discussing this at the office, and if you want to know what we were saying, well, Ben Clemens essentially repeated word for word what we said, without him actually being here!  Terrific stuff from Ben.

The main cause, I was suggesting, was the dilution of talent.  I'm a little concerned with how Ben approached it, since that will cause a selection bias.  In order to get around that bias, Ben can look at first-half performance, establish the identity of pitchers at that point, then look at second-half performance.

The other cause, as Mike and Matt in the office were suggesting, is that if you know you will pitch less, you will then pitch more like a reliever.  Ben tackles this as well.

And of course, we always have the "Third Times The Harm" effect for starting pitchers, which Ben also tackles.

Note that looking at the first 7 batters in the lineup is a clever way to get around pitchers-as-batters.  Note that you'd want to split between home/away, for reasons we've talked about many times in the past: the visiting pitcher is "cold" against the home batters in the 1st inning.

A home run of an article for an Opener on the subject.

Sunday, November 04, 2018

Statcast Lab: Do Successful Launch Anglers keep Angling?

?Yes. Yes they do.

***

Now, what in the world is that question, and more specifically, what do all those angle-based words even mean? So, let me tell you what I did, and hopefully this will start to make sense.

I looked at all batters who had at least 150 plate appearances (PA) in each of 2016, 2017, and 2018. There are 238 of them. I am interested in players who had a increase in performance between 2016 and 2017. The face of this movement is Ryan Zimmerman. His wOBA (including walks and strikeouts) jumped by 0.103 (or 103 points), going from the 10th percentile in wOBA to the 90th percentile. Coincidentally, or more specifically, not coincidentally, his sweetspot launch angle...

Uhhhmmm... just realized I created a metric called Sweetspot Launch Angle. (Coming soon to a Savant site near you.) What I did was take every hitter's one-third hardest hit balls, and found the average launch angle of those balls. The idea being that the harder you hit the ball, the more likely you "got all of it", and so, the launch angle was your intended launch angle. You got it on the sweetspot of the bat, and so, the byproduct of that is your... Sweetspot Launch Angle.

... his sweetspot launch angle was 6 degrees in 2016 and 12 degrees in 2017. Zimmerman BELIEVES that changing his Sweetspot Launch Angle helped, because in 2018, it was 11.3 degrees. In this article, I won't talk about whether the launch angle helped or not, whether it's a placebo. I simply want to know: are hitters consciously changing their approach.

There were 109 batters who increased their wOBA between 2016 and 2017 by at least 10 points. Of those, their launch angle in 2018 was LARGELY linked to their 2017 launch angle by an 82/18 split. That is, their 2018 launch angle was hugely influenced by their 2017 launch angle. As I said, whether this link is real or placebo, all that matters, for this article, is that the batters believe in their launch angle.

There were 113 batters whose wOBA dropped. Their 2018 launch angle was essentially a split of their 2016 and 2017 launch angles (56% 2017, 44% 2016). In other words, because their performance dropped, they were likely to revert back to their prior launch angle.

Both these groups had similar launch angles in 2016 (11.5 for the Zimmerman group and 11.7 for the other). 

So, for whatever reason, hitters are more likely to maintain their launch angle if it was followed by an increase in performance. The successful launch anglers are angling.

Monday, September 03, 2018

Lead runner or go for 2?

?This scenario.

Starting State:

0.829 Bottom of 9th, 1 out, bases loaded, tie game

Ending State, option A, throw home:

(1) 0.658 Bottom of 9th, 2 outs, bases loaded, tie game

(2) 1.000 walkoff slideoff

Ending State, option B, go for 2:

(1) 0.500 Extra Innings

(2) 1.000 walkoff slideoff

Option A: If you throw home, let's say you have a 73% chance of getting the runner.  Home team chance of winning is 0.750

Option B: If you go for 2, and you have a 50/50 chance to turn 2, that's a 0.750 chance of winning for home team.

On the other hand, suppose chance of getting lead runner is 85%, then option A is 0.709.  If you have a 59/41 chance to turn 2, that's an equivalent 0.705.

In other words, if  you have about a 25% more chance of getting the runner on 3rd as you have at turning 2, it's breakeven what you do.

Monday, July 16, 2018

Handedness wOBA, BABIP, TTO etc

?Just a collection of charts I just posted on Twitter.  More description in the tweets.

Thread and bonus tweets.

Thursday, April 26, 2018

Defensing the bunt

?Pizza has an article on the bunt.  MGL has a comment on it, which I'm not sure if non-subscribers can read, so I'm copying it below (with MGL's permission).  

Read More

Does an increase in launch angle lead to an increase in strikeouts?

?In a terrific piece by Eno, he shows this graphic:

The key parts are at the tail-end, showing that guys who increase their launch angle by 3+ degrees (let's assume +5 degrees) will increase their K rate by 2-8% (let's assume +5%).  On the bottom side, you need a severe drop in launch angle, about -10 degrees to affect a -5% change in K rate.  I think this 5% change in K rate is 0.05 K / PA, as opposed to going from 0.20 K/PA to 0.21 K/PA.

You can also see however that a SLIGHT change in launch angle won't affect your K rate, meaning that you just need to make  small adjustments rather than overhauling your whole swing.

In addition, this should be broken down by whether you have a low launch angle to begin with.  If you already have a high launch angle, then further increasing it likely will severely affect your K rate.  

Regardless, Eno's opened the door here, so I look forward to more research in this area.  

Saturday, July 16, 2016

Does having your starting pitcher knocked out early hurt your chances of winning the next game?

?That's the basic idea, right, that having your SP knocked out early means burning through your bullpen, exposing your bullpen the day after.  Bill James looked at the issue and could find no such impact.

What he did was straightforward: starting with game 1 of a series, made sure that game 2 was played on the next day.  He used the end-of-season win% of each team to Log5 their win expectation, and then adjusted for home/away.  So, a .550 v .450 team would win 64% of the time at home and 56% of the time on the road.

He compared the actual win% with the expected win%, based on how many outs the previous day's starting pitcher recorded.  For example, when the SP of the previous day recorded 12 outs, meaning he was knocked out after 4, or before he could get the first out in the 5th inning, the current day's team won 49.3% of the time.  The expectation, based on the quality of the team and home/away was 47.7% wins.  That is, they won MORE with the depleted bullpen.  And this example is the LARGEST gap James could find, at only 1.6 standard deviations from the mean. That's the z-score. When you slice up your data into 27 bins, you are going to find some outlier.  Having the most extreme at only 1.6 shows you've found nothing.  The standard deviation of these 27 z-scores was 0.90.  If it was purely random, it would be 1.00.  If there was something to find, the SD of the Z-scores would be greater than 1 (and the greater the effect, the larger the number).  Instead, it was less than 1, almost certainly pointing to a bias.

Now, James admitted that the next phase of the study is to control for the identity of the SP, which is one source of the bias.  Since a great pitcher rarely gets knocked out early, the next day's SP is more likely to be a good pitcher rather than bad pitcher.  So, rather than the expectation of winning being only 47.7%, it will rise to.... well, how much could it rise to... 48.1% or 48.8% or something?  Whatever it is, it won't be say 51.2%.

So, yeah, people say all kinds of things that sound reasonable.  But, it's on THEM to prove it's true, and not on us to prove they are wrong.  Therefore, unless someone provides evidence to support their claim, the claim is a summary opinion without evidence.  And we know what I call that.

Wednesday, July 06, 2016

Performance by plate count

?We talked about this alot in the old blog, but since it occasionally comes up, and given the massive change in strikeout rates since 2010, I figured it would be worthwhile to update this for the 2015 season. These are the "through counts" and not the "at counts".

Read More

Monday, March 28, 2016

Are offenses most efficient when they have a 3 to 4 run lead?

?I looked at how many runs each team scored each inning, based on the score differential to start the inning, for each year from 2010-2015, for every inning through the 8th.  That gives us six years times 30 teams, or 180 groups for each class of score.  The scores I looked at was from 5 runs (or worse) behind to 5 runs (or better) ahead, and everything in between.  That's 11 classes of score differential.

When the batting team was behind by at least 5 runs to start the inning, they'd average 0.490 runs per inning (each team-season equally weighted).  When they started 5+ runs ahead, they'd average 0.491 run per inning.

When they were 4 runs behind, they'd average 0.478 runs.  When they were 1, 2, 3 runs behind, they'd average .466, .462, .465 runs respectively.

When it was a tie game, they'd average .482 runs and when they were 1 run ahead they'd average .479 runs.

So far, so uninteresting.  Start the inning with a 2 run lead, and they average .506 runs.  Hello.  Starting to get interesting.  With a 3 run lead, it shoots all the way up to .544 runs and with a 4 run lead, it's .545 runs.  And remember, with a 5+ run lead, it drops all the way back to .491 runs.

Now, I expected to see some small consistent increase on the idea that if you have a larger lead, you are probably playing against a worse defense.  But I expected the increase to be slight and consistent.  The results at 5+ runs undoes all of that.  Which makes me think that something is going on when there's a 3 or 4 run lead to start the inning.

***

This kind of phenomenon occurs in hockey, when there's (exactly) a 2 goal lead.  At that level, the offense and defense changes their style of play, as the game is still hanging in the balance, the offense desperate to protect the lead, and the defense ready to risk to score a goal.  At a 3 or 4 goal lead, the gap is too wide to do anything drastic.  And the results bear that out.

But in baseball?  I guess I never gave it much thought.  Well, in The Book, we do show how the SB is more favorable at a bigger lead.  So, maybe there are styles of play to consider here.  I'm just very surprised at how large a difference we are talking about here.

So, this is another one for the aspiring saberists to flex your Retro-muscles, and show me the data prior to 2010.  Am I seeing a blip, or is this something real?

Wednesday, March 23, 2016

How the fielding shift in baseball plays out in football

?Well, well, well.  The NFL is changing the touchback rule on kickoff so that it goes back to the 25 yard line.  Since the breakeven point is right around the 20 yard line, the returning team is HIGHLY incentivized to do a touchback.  You can't just automatically give one side 5 yards and expect nothing to change.  Well, they will change.  The kicking team is now incentivized to kick it short enough to not allow a touchback to begin with.

See, if the touchback was the 10 yard line, the kicker would simply do one thing: kick it as hard as he can.  If the touchback was the 40 yard line, the kicker would simply do one thing: make the trajectory a high enough launch angle so that distance is "sacrificed", a sacrifice that benefits the kicker.  At 20 yards, there was harmony.

How does this apply to fielding shifts in baseball?  Well, if a hitter is smart, he (a) wants the fielders all to one side and (b) he would continually poke the ball or bunt the ball to the open side.  But if the fielders see the batter adjusting, the fielders will suddenly play defense normally.  In which case the huge advantage for the batter disappears.  Which forces the batter to now pull the ball more, forcing the fielders to shift more, which allows the batter to not pull as much... until we have harmony.  The batter therefore doesn't want to do this too much.  He has to hit suboptimally (not always bunt) to keep the fielders to continue to play suboptimally!  It's just a matter of how suboptimally the hitter is to maintain the oppositions suboptimization.  Weird, I know.

Indeed, the NFL can make the rule so that the defense decides on what the touchback line is!  A team can say "touchback to 40", in which case the kicker will "bunt" it (i.e., high short kick).  A team can say "touchback to 20", in which case the kicker will "pull" it (long straight kick).  Basically, letting the defense call the touchback line is just like fielders positioning themselves on a baseball diamond!

Monday, February 29, 2016

Times Thru the Order Penalty

?This was one of the key findings in The Book, that the more times you go through the order, the higher the offensive output.  It's gotten to the point that this has become accepted conventional wisdom.

The question is whether it was due to pitch fatigue or the number of times the batter comes to bat (sees pitcher's arsenal).  MGL took my general idea from The Book and turned it into a great research piece a few years ago, enough that he is now the leading voice on understanding the TTOP.  As Bill James once noted, when we publish our work, that work is now an orphan.  We can't really control or contain it, and someone will get inspired enough by it that they'll eventually take it to places you didn't.  This is what happened here.

MGL responded to a claim from Pizza Cutter with additional research and theory.  But what I liked beyond everything MGL did was the little nugget about pinch hitters.  This would be a terrific offshoot project for an aspiring saberist.  We always look for "controlled" studies in our line of work, and a pinch hitter offers that.  What a great idea to look at whether pitch counts impacts performance than to look at how pinch hitters respond to pitchers who have, say 60 or fewer pitches and 90 or more pitches (or whatever might be a good demarcation point).

Wednesday, February 24, 2016

Bayesian Umpire

?Long (long, long) time Straight Arrow commenter GuyM has a sensational article over at BPro.

But why do umpires shift their error rates at all, unless it is to lend a helping hand to the underdog? The answer is, because they know (more or less) what’s coming. Umpires are changing their decision rule on close calls—“lean ball” vs. “lean strike”—based on the likelihood that the pitch will actually be a strike. With two strikes, they know the pitcher will usually throw outside the zone, and they know the hitter will typically swing at anything close—so guessing “ball” on any taken pitch is the percentage play. By adjusting their decision rule at each count to reflect their prior knowledge of the true distribution of pitches, they make better guesses and fewer mistakes. In short, umpires are Bayesian, not compassionate.

Friday, January 29, 2016

Saturday night special

Any rookie starting pitcher should be limited, by CBA, to a maximum of one start per week.

Now, you may think, this will mess up the entire rotation.  Except, it will not.  Not if you make him pitch games on Saturdays, and only Saturdays.  I did this exercise back with Strasburg a few years back, and it works.  The reason it works with Saturdays, and only Saturdays, is because there's never an off day on Friday or Sunday.  So, you might occasionally push Kershaw or Price for an extra days rest, but that's really the maximum.  And over the course of a season, no starts will be lost by the top-end guys.

This gives the rookie 26 starts.  26 starts sounds low, but it would rank as 85th highest in MLB in 2015.  Basically, third highest for a team.

Indeed, you might think: oh, I need 5 starting pitchers on my team, each making 32 or 33 starts.  That implies 150 SP in MLB doing that.  Except, the 150th highest number of starts was 15 starts!  The top 150 pitchers in starts accounted for 3944 starts, or an average of 131.5 starts per team.  There's still a whole 30 other starts that you need to find outside your top 5.  And considering your 5th starter is only making 15 starts, those 30 other starts are going to come from at least two other starting pitchers. 

Basically, each team has to be going in thinking they are going to need seven starting pitchers making at least 15 starts.  Some teams like the Mets are lucky, and they needed 5 pitchers to make 143 starts, so they only needed to find another 19.  So, if you are really lucky, you need six SP.  But the Yankees are the more likely scenario, as they needed 6 pitchers to make 141 starts, and they still needed to find 21 more starts.

Anyway, the Saturday night special pitcher.  It helps the pitcher and it helps the team.

Wednesday, January 06, 2016

Is there anything better than good sportsmanship?

?One of the beautiful things about golf is that the lack of an official almost obligates that players make calls on themselves, to their detriment.  (Except Tiger, who will never call himself on anything, especially his bullsh!t.)

In head-to-head sports and team sports, you do have an official, and so, players aren't going to call themselves to their detriment.  Here's Derek Jeter when he did not get hit by a ball, but he takes 1B anyway.  This is a rule, not an exception, and so, Jeter is just like everyone else.

Everyone that is, except.... here we have it in tennis, which DOES have an official, yet a player is telling his opponent to use his challenge so that his opponent benefits.  And it's not like his opponent is one of those nice guys like Federer.  No, his opponent was Lleyton Hewitt. This is a beautiful thing.

Monday, November 23, 2015

Can Bob Stanley 1982 be the new norm?

?Bill James wonders if we can make a 3-man "rotation" work. 

What it really comes down to is forgetting about the notion of a "starting pitcher", since in his setup, there's really no obvious benefit for the 5-inning pitcher to start the game as opposed to say entering the game in the 3rd or 5th inning.  He simply is going to get his 5 innings of work in.  (From a W/L perspective, this "long man" would actually benefit the most by entering the 3rd inning.)  And in the case of an already lost-cause game, he could be delayed one day.

Anyway, Bill argues that this pitcher has to be capped at 5 innings or 80 pitches, whichever comes first.  (I would also add the provision of a maximum of 18 batters, which really sets the effective cap at 70 pitches, but let's set that aside for now.)  That would likely average out to 70 to 75 pitches per start, down from 95 average since 2002.  Figuring a realistic number of games for the long man of 50, that gives us 3500 pitches, a typical workload in the pre-2000 time period.

But the harder sell is really the setup time, the warmup pitches, the whole process.  There's a reason that relievers don't approach 3500 pitches.  Take for example, or for extreme, Bob Stanley in 1982.  He threw 48 games as the long man, facing nearly 700 batters, which would mean about 2500 pitches.  With a league-leading ERA-, he was obviously extremely effective.  The next season, he threw in 64 games, facing closer to 600 batters, or about 2100 pitches at an even better performance level.

So, I think that's the kind of tradeoff you get in terms of increasing games and decreasing workload.  At 35 games, you can get your 3500-4000 pitches.  At 50 games, it's down to 2500 pitches.  At 65 games, it's down to 2000 pitches.

Going back to Bill's proposal, if we're going to create a series of long-men, say 3 or 4 per team, that would have them average out to 55 pitches per game with 50 games, maybe setting a hard cap at 60 pitches.  Which also means setting a hard cap at 18 batters, which of course The Book has shown would be very effective at an individual pitcher level.

Therefore, going with that, can the Straight Arrow readers construct a viable plan with 3 or 4 long-men, each given a cap of 60 pitches or 18 batters (whichever comes first), with 50 or so games?

Wednesday, September 30, 2015

Greinke felixes his muscles

?I couldn't resist using Felix as a verb.  Greinke gives us insights into his changeup.

Tuesday, September 22, 2015

Joey Votto and the Science of Hitting

Terrific piece by Eno as we get inside the mind of Votto.  I love these smart hitters, like Votto and John Jaso who have hitting figured out pretty well.

Sunday, September 20, 2015

What’s the rule on a runner stealing home with 2 outs, 2 strikes?

?David asks a good question if the runner beats the pitch into the strike zone.

Suppose the runner touches the plate and the batter then swings at the pitch, foul.  In that case, the pitch takes precedence, just as it would at any base, and the runner has to go back.

Suppose the runner touches the plate and the batter is then hit by the pitch, making the ball dead.  In that case, does the pitch take precedence?  I don't think so.  You can imagine say a runner on 2B with a big lead who steals third and then the batter is hit by the pitch in the same sequence.  They wouldn't send the runner back to 2B would they?  I don't think so anyway.  So, in this case, the pitch does not take precedence.

Therefore, I would conclude that other than a foul swing (and when I think about it... why??), you use real-time sequencing.  I think anyway.