Best lefty off all time? My vote is Koufax!

[G1911]

Originally Posted by Peter_Spaeth

Maddux's success was the result of dumb luck!! 21 years of it, well, maybe 16 of which really defined him.

Well, he pitched for 21 years which seems like a lot, but it was only 5,008 innings. The sample is just too small. Maddux was lucky. Also a bum because only K pitchers who played after Spahn, except for Koufax who is exempted because I don’t know, are any good.

[Lorewalker]

Originally Posted by G1911

Well, he pitched for 21 years which seems like a lot, but it was only 5,008 innings. The sample is just too small. Maddux was lucky. Also a bum because only K pitchers who played after Spahn, except for Koufax who is exempted because I don’t know, are any good.

Snowman is always right. Just ask him.

[BobC]

Originally Posted by Lorewalker

Snowman is always right. Just ask him.

He even has a statistical algorithm to prove it. But don't ask him to show you, because he hasn't actually created it yet. And he doesn't really have the time to do it right now, unless you want to pay him. But even if you do, and then he does, it probably doesn't matter because he'll tell you you're too ignorant to understand it anyway.

[Lorewalker]

Originally Posted by BobC

He even has a statistical algorithm to prove it. But don't ask him to show you, because he hasn't actually created it yet. And he doesn't really have the time to do it right now, unless you want to pay him. But even if you do, and then he does, it probably doesn't matter because he'll tell you you're too ignorant to understand it anyway.

Pretty much sums up our snowman on every thread, Bob. Since I have been here this is the fastest I have seen someone overstay their welcome however he is very amusing because of how serious he takes himself.

[BobC]

Originally Posted by Lorewalker

Pretty much sums up our snowman on every thread, Bob. Since I have been here this is the fastest I have seen someone overstay their welcome however he is very amusing because of how serious he takes himself.

LOL

Hopefully things will change, but the fact he got bounced off Blowout makes the the question others have asked as to whether or not he's a troll, more possible than not I guess. He's a smart guy, just wish he'd be a little more open minded and realize he's not always going to be right. Oh well. Guess we'll wait to see what happens. I just put him on "Ignore" myself and don't read his posts anymore. It's better that way.

[Aquarian Sports Cards]

from MLB.com

"The formula

(H - HR)/(AB - K - HR + SF)
Why it's useful

BABIP can be used to provide some context when evaluating both pitchers and hitters. The league average BABIP is typically around .300. Pitchers who have allowed a high percentage of hits on balls in play will typically regress to the mean, and vice versa. In other words, over time, they'll see fewer (or more) balls in play fall for hits, and therefore experience better (or worse) results in terms of run prevention. The same applies for batters who have seen a high or low percentage of their balls in play drop in for hits.

That said, skill can play a role in BABIP, as some pitchers are adept at generating weak contact, while some hitters excel at producing hard-hit balls. For example, Clayton Kershaw finished the 2019 season with a lifetime .270 BABIP allowed, while Mike Trout ended the campaign with a career .348 BABIP."

My Thoughts:

The all-time leader of BABIP for starters over 1000 innings is Babe Ruth at .241, 2000 innings Andy Messersmith at a slightly higher .241, 3000 innings Catfish Hunter at .243 Those are all fine pitchers but none of them are in the running for all-time greatest status. So clearly BABIP, even to the degree it is controllable, isn't a perfect stat either.

[Lorewalker]

Originally Posted by BobC

LOL

Hopefully things will change, but the fact he got bounced off Blowout makes the the question others have asked as to whether or not he's a troll, more possible than not I guess. He's a smart guy, just wish he'd be a little more open minded and realize he's not always going to be right. Oh well. Guess we'll wait to see what happens. I just put him on "Ignore" myself and don't read his posts anymore. It's better that way.

He seems to double down and then resort to putting everyone down in every thread in which his theories, which he presents as facts, are successfully challenged. He might be smart but he is not that bright.

[Carter08]

Maybe not the thread for this but why didn’t the yanks trot Ruth out to pitch more often? I assume it’s the obvious - to keep him healthy and batting and if it ain’t broke don’t fix it.

[BobC]

Originally Posted by Lorewalker

He seems to double down and then resort to putting everyone down in every thread in which his theories, which he presents as facts, are successfully challenged. He might be smart but he is not that bright.

Well, that is where the troll reference may become applicable. LOL It would seem he deep down must really get into these back and forths at some level, unfortunately, maybe more so than just the desire and interest in discussing such topics themselves that we typically end up doing on here from time to time. In other words, maybe he comes on sites like this looking for the arguments because that is what his psyche wants and needs, and doing so over the internet, he can stlll remain removed, somewhat anonymous, and thus feel safe. Which is kind of the definition for being a troll when you think about it. LOL

For example, it was much earlier in this thread that he appeared to get frustrated when people pushed back and didn't simply accept what he was saying, or the implied or overt insults. So he clearly and emphatically stated he was done with this, which pretty much every intelligent, normal person would take to mean he was done with responding and interacting with everyone on this thread anymore. Had he actually stuck to his word, I wonder if he wouldn't have garnered a little more respect from the crowd on here. But instead, it was just a few posts later, and he was right back at it without missing a beat. So does that point to some deeper, psychological urge or need, who knows?

On the positive side, even though I simply ignore and no longer waste my time reading his posts, in looking at what others are posting ang saying in this thread, it appears he's finally admitting the he may have made same errant statements and that his statistical assumptions and conclusions may not in fact always be infallible. And if I'm right, good for him. He does have and makes some very intelligent and interesting points and comments. It's just that he doesn't seem to realize, or doesn't want to admit, that as good as statistical analysis can appear to be, in the end it is nothing more than a tool to hopefully allow someone to more accurately predict an outcome, like who's going to win the Super Bowl. Unfortunately, when their ability to predict outcomes like the winner of a Super Bowl begins to have some success, such people may then try to extend that tool to possibly use it for something else that is not a totally objective question, like deciding who the greatest lefty pitcher of all time is. That is clearly not an objective question, and has no absolutely certain outcome we can then actually measure the effectiveness that some statistical analysis may have in predicting it, at least not like knowing there will be an actual Super Bowl winner. And also extremely important (and maybe the MOST important thing of all), everyone knows, AND AGREES, on exactly what the definition of and how you decide on who the Super Bowl winner is. In the case of the greatest lefty of all time, we haven't even begun to decide on the correct definition of "greatest" yet, let alone the actual measures we will then use to POSSIBLY decide an answer, if it can even be done. And untill that has been determined, everything is just someone's opinion, INCLUDING someone's statistical analysis.

And in regards to referring to statistics as just a tool.........

A statistician's wife has been bugging him for weeks to replace a light fixture on the ceiling, and he's finally going to get around to doing it (And without her having to pay him to do so, go figure!). Unfortunately, he needs a screwdriver to remove a few screws to get the job done, but doesn't have one. Well, he's up on the ladder already, so before getting down and then having to drive all the way to the store to buy a screwdriver, he goes digging around in his pocket and finds his penknife, and promptly uses that to remove the screws and complete the task. So he gets the job done using a tool that wasn't actually meant for what he ended up using it for. But he took a chance on guessing it might work and got lucky, like he got lucky to also just happen to have the penknife in his pocket when he most needed it to begin with. But before you go applauding the statistician for his fine work in completing the given task, and he triumphantly goes riding off into the sunset on his noble, white steed, with his beautiful and now forever grateful wife astride behind him, I have to finish the rest of the story.

Turns out that for maybe what little the statistician knew about tools, he knew even less about electricty. For while using his penknife to remove the screws and then replace the light fixture, he accidently knicked some wires in the ceiling and unknowingly got them crossed. So once he had the fixture replaced, he joyously called his wife to come and flip the switch to see the new fixture working, and what a great job he had done. Unfortunately, the knicked and crossed wires created a short, which blew out the fuse box, and resulted in having to call in an electrician to fix everything, at a very hefty cost. And as a result, our woebegone hero ended up sleeping on the couch for the rest of the week. So much for our happy ending!

And as for statistics always being able to measure and actually predict human nature and outcomes, go read some Asimov!

[Snowman]

Originally Posted by BobC

He even has a statistical algorithm to prove it. But don't ask him to show you, because he hasn't actually created it yet. And he doesn't really have the time to do it right now, unless you want to pay him. But even if you do, and then he does, it probably doesn't matter because he'll tell you you're too ignorant to understand it anyway.

And I'll give you $1k right now if you can explain in detail why a pitcher's win totals and ERA from any given season should not be used to evaluate pitching performance. And you can't just say "sample size". Good luck.

[Snowman]

Originally Posted by G1911

Well, he pitched for 21 years which seems like a lot, but it was only 5,008 innings. The sample is just too small. Maddux was lucky. Also a bum because only K pitchers who played after Spahn, except for Koufax who is exempted because I don’t know, are any good.

Maddux also pitched in the NL, in a pitcher's park, and with one of the greatest defensive center fielders of all time catching balls for him. His BABIP would be expected to be lower than MLB average. If you look at Smoltz and Glavine's numbers during the same time, they also both beat league average MLB BABIP.

Perhaps you should read up on BABIP? I somewhat excuse the level of ignorance on these topics by the non data savvy people in this thread because it's not exactly their job to understand numbers. But if you are serious about being a data analyst, your perpetual ignorance displayed throughout the entirety of this thread with respect to just basic statistics and simple statistical concepts is remarkably embarassing. You should be ashamed of yourself. Go read a book. Or three.

[G1911]

Originally Posted by Snowman

Maddux also pitched in the NL, in a pitcher's park, and with one of the greatest defensive center fielders of all time catching balls for him. His BABIP would be expected to be lower than MLB average. If you look at Smoltz and Glavine's numbers during the same time, they also both beat league average MLB BABIP.

Perhaps you should read up on BABIP? I somewhat excuse the level of ignorance on these topics by the non data savvy people in this thread because it's not exactly their job to understand numbers. But if you are serious about being a data analyst, your perpetual ignorance displayed throughout the entirety of this thread with respect to just basic statistics and simple statistical concepts is remarkably embarassing. You should be ashamed of yourself. Go read a book. Or three.

The only person being embarrassed in this thread is you. You’ve progressed into actually having some points beyond claiming to be infallible and have a statistical model you can’t show that proves your claims, but any good point in it is lost by the constant insults of everyone else here and the childish immaturity of your ‘over the top brag - insult’ pattern that never ceases. I’m well aware of what BABIP is and already said the defense behind the pitcher needs to be adjusted for. Regardless of what you claim, great contact pitchers find success at not giving up many runs, often equal to or even better than great K pitchers. Dismissing all non K centric pitchers, which seems to be your implied basis for ignoring Spahn but including his exact contemporary Koufax, is not supported by the data. It does not appear to be random luck, and they tend to have lower BABIP’s over large sample sizes.

But I’m illiterate and homeless, among many other things.

[Snowman]

Originally Posted by G1911

The only person being embarrassed in this thread is you. You’ve progressed into actually having some points beyond claiming to be infallible and have a statistical model you can’t show that proves your claims, but any good point in it is lost by the constant insults of everyone else here and the childish immaturity of your ‘over the top brag - insult’ pattern that never ceases. I’m well aware of what BABIP is and already said the defense behind the pitcher needs to be adjusted for. Regardless of what you claim, great contact pitchers find success at not giving up many runs, often equal to or even better than great K pitchers. Dismissing all non K centric pitchers, which seems to be your implied basis for ignoring Spahn but including his exact contemporary Koufax, is not supported by the data. It does not appear to be random luck, and they tend to have lower BABIP’s over large sample sizes.

But I’m illiterate and homeless, among many other things.

In one breath, you claim to understand BABIP and its implications, and in the very next breath you use the completely nonsensical term of "great contact pitchers" as if such a thing exists. This is what I'm trying to tell you. There is no such thing as a "great contact pitcher". They are the Loch Ness Monster of baseball. A myth. If you don't understand this, then you don't understand BABIP and why it is important.

This isn't exactly news either. Every franchise in the league today knows this. You might find some old school uneducated managers here and there who still reject it, but the front offices and owners across the league all accept this fundamental truth. It's been well known for the better part of 20 years now.

You should read this. It's a link to the original research article by the guy who discovered this fundamental truth about pitchers not being able to control contact after the pitch.

https://www.baseballprospectus.com/n...-hurlers-have/

[G1911]

Originally Posted by Snowman

In one breath, you claim to understand BABIP and its implications, and in the very next breath you use the completely nonsensical term of "great contact pitchers" as if such a thing exists. This is what I'm trying to tell you. There is no such thing as a "great contact pitcher". They are the Loch Ness Monster of baseball. A myth. If you don't understand this, then you don't understand BABIP and why it is important.

This isn't exactly news either. Every franchise in the league today knows this. You might find some old school uneducated managers here and there who still reject it, but the front offices and owners across the league all accept this fundamental truth. It's been well known for the better part of 20 years now.

You should read this. It's a link to the original research article by the guy who discovered this fundamental truth about pitchers not being able to control contact after the pitch.

https://www.baseballprospectus.com/n...-hurlers-have/

And yet, throughout the entirety of baseball history, we have great pitchers who are not strikeout pitchers (and thus getting their outs on contact) having very long careers and performing far above most pitchers. If there is no such thing as a great contact pitcher, how are pitchers like Maddux great? Or do you think Maddux and the numerous other pitchers like him are all sheer luck?


I'm familiar with McCracken's article and Bill James' positive take on it. I think some of the points are true indeed. But I also am aware that some contact pitchers have high inning careers of greatness. These sample sizes seem unreasonable to chalk up to sheer dumb luck. If it was purely the team defense behind them, pitchers like Maddux and the number 5 starter on the team who isn't a strikeout pitcher would chalk up about the same numbers on the whole. Maddux is a good example, he wasn't a great K pitcher. He pitched to contact. And he won 4 ERA crowns, 4 FIP crowns, led the league in fewest hits per 9 once. How do we explain his 5,000IP career if contact pitchers are all bad or mediocre?


Are you capable of making any argument whatsoever without insulting anyone? I think you've actually started to bring up good points that can coalesce into a coherent, rational argument, but your absurd egotism and propensity to just resort to the ad hominem at every single turn obscures even your good points.

[Carter08]

Originally Posted by G1911

And yet, throughout the entirety of baseball history, we have great pitchers who are not strikeout pitchers (and thus getting their outs on contact) having very long careers and performing far above most pitchers. If there is no such thing as a great contact pitcher, how are pitchers like Maddux great? Or do you think Maddux and the numerous other pitchers like him are all sheer luck?


I'm familiar with McCracken's article and Bill James' positive take on it. I think some of the points are true indeed. But I also am aware that some contact pitchers have high inning careers of greatness. These sample sizes seem unreasonable to chalk up to sheer dumb luck. If it was purely the team defense behind them, pitchers like Maddux and the number 5 starter on the team who isn't a strikeout pitcher would chalk up about the same numbers on the whole. Maddux is a good example, he wasn't a great K pitcher. He pitched to contact. And he won 4 ERA crowns, 4 FIP crowns, led the league in fewest hits per 9 once. How do we explain his 5,000IP career if contact pitchers are all bad or mediocre?


Are you capable of making any argument whatsoever without insulting anyone? I think you've actually started to bring up good points that can coalesce into a coherent, rational argument, but your absurd egotism and propensity to just resort to the ad hominem at every single turn obscures even your good points.

Plus one. And I without looking at stats I will just say the eye test can tell a great pitcher. It’s fun to watch a guy where no one can touch the ball - thinking DeGrom when he’s actually healthy - but it’s also fun to watch a guy that paints corners and throws junk down the middle that ends up with dribblers.

[cardsagain74]

Originally Posted by G1911

I'm familiar with McCracken's article and Bill James' positive take on it. I think some of the points are true indeed. But I also am aware that some contact pitchers have high inning careers of greatness. These sample sizes seem unreasonable to chalk up to sheer dumb luck.

The article did have some good points, but I agree that its whole "FIP is all that matters" conclusion is too simplistic and goes too far. And some of the points were really grasping at straws; the quotes from Maddux and Pedro were an especially poor attempt to help prove the merits of the study (of course a long scoreless innings streak will have a lot of luck...what does that have to do with that specific discussion?)

I've noticed that when it comes to sports and gambling, statisticians love to claim as many "this is completely random" findings as they possibly can. A lot of that probably has to do with being the devil's advocate about the general public's often faulty attempts to find reason in trends or insufficient statistics.

And with having such a passion to do so, it's easy for them to go too far in the other direction (and be too quick to dismiss the possible meaning in some numbers)

[Snowman]

Originally Posted by cardsagain74

The article did have some good points, but I agree that its whole "FIP is all that matters" conclusion is too simplistic and goes too far. And some of the points were really grasping at straws; the quotes from Maddux and Pedro were an especially poor attempt to help prove the merits of the study (of course a long scoreless innings streak will have a lot of luck...what does that have to do with that specific discussion?)

I've noticed that when it comes to sports and gambling, statisticians love to claim as many "this is completely random" findings as they possibly can. A lot of that probably has to do with being the devil's advocate about the general public's often faulty attempts to find reason in trends or insufficient statistics.

And with having such a passion to do so, it's easy for them to go too far in the other direction (and be too quick to dismiss the possible meaning in some numbers)

The underlying problem is that every statistic you read really should come with a confidence interval attached to it. But of course that's just too confusing for most people, and it would probably just annoy everyone. Plus, it's just impractical. But the reality for most of these statistics is that they are actually estimates of the athlete's underlying "true" abilities. Mike Trout's "true" batting average is some unknowable number, but we can estimate it using statistics. And that's precisely what we do. After the first game, he goes 3 for 4, we estimate it to be 0.750. Well, that's not going to fool anyone, because nobody hits 0.750, so we wait for more data. After a month, he's still hitting 0.414 though. Hell, by the all-star break, he's still hitting 0.392. That's after nearly 100 games and 400 at-bats! Surely, that's a large sample, right? Has he turned a corner? Rumors start spreading about him "putting in work in the off-season". They say he's "really focused now", etc. But none of this fool's the statistician, because we don't read his batting average as 0.392. We understand that 0.392 is just an estimate of his "true" batting average and that we can calculate a 95% confidence interval around this estimate by looking at the standard deviation and sample size associated with it. So, instead of reading it as being 0.392, we more appropriately read it as something like 0.392 +/- 0.130. In other words, his "true" batting average is 95% likely to be in the range of 0.262 to 0.522, which ultimately, just isn't all that helpful. Because we know this, we are hesitant to say things like "Trout is a better hitter this season than Harper since Trout is hitting 0.392 and Harper is only hitting 0.333 at the all-star break". The truth is, we just don't have enough data to make that determination. The sample sizes are simply too small, the standard devaition is too large, and thus the confidence intervals are too wide to be able to make claims "with confidence" about that statistic.

The same is true for something like ERA from season to season. It is a highly volatile statistic. When we say something like "it has too much variance", we mean that literally. Mathematically speaking, variance is the square of the standard deviation. Some statistics have extremely wide standard deviations, like ERA, batting averge, OBP, etc. Whereas other statistics have MUCH lower variance/standard deviations. Stats like FIP vary far less than ERA. This means we can compare two pitchers at the all-star break with much greater confidence by comparing their FIPs than we can by comparing their ERAs. It is a mathematical property of the inherent differences between those statistics. The same is true of K/9 and BB/9. They have lower variance than ERA, and thus have much narrower confidence intervals. A statistician might be able to read Koufax's K/9 rate at the all-star break with a fairly narrow confidence interval because of this. So they might read his K/9 of 10.1 as being something like 10.1 +/- 0.4, making comparisons against other pitchers much more possible. If two pitchers' statistics do not overlap when taking into consideration their confidence intervals, then you can say that you are 95% confident that Koufax is a better strikeout pitcher because his 10.1 +/- 0.4 K/9, or as an interval, read (9.7, 10.5) is greater than some other pitcher whose K/9 confidence interval is (8.8, 9.6). Note the bottom of Koufax's range (9.7) exceeds the top of the other pitcher's range (9.6), so we can state with confidence that he is indeed better. However, this is rarely possible to say with ERAs. The confidence intervals with those are just absolutely massive. Even after an entire season. One pitcher's ERA of 3.05 may look quite a bit better than someone else's 2.64, but we just can't state that with confidence because their intervals might be something like 3.05 +/ 0.65 and 2.60 +/- 0.75 resulting in ranges of (2.40, 3.70) and (1.85, 3.35). And since those intervals overlap, we cannot state with confidence that they are truly different or that one is clearly better than the other. This is why an asshole like myself says something along the lines of, "that doesn't mean shit", whereas someone more tolerant might say something like, "the standard deviations of that statistic are too wide and the sample sizes are too small for us to be able to make a determination about the differences between those two data points". One of the most fascinating aspects about baseball, which is probably a big part of why I love the game as much as I do, is that the game truly is subject to a MASSIVE amount of variance. Great hitters can hit 0.348 one season and 0.274 the next. People will come up with all sorts of explanations about what is causing the slump, whether his home life is affecting him too much, if he's injured or just experiencing a mental lapse, etc. However, the informed fan knows that this is simply within expectations, and looks to statistics like BABIP to help shed light on what the actual underlying cause is (the guy just got some lucky bounces last season and some favorable ones this season. Or perhaps he didn't. Perhaps his BABIPs are the same, and there actually really is something going on in his personal life or he really is injured. But variance/luck needs to be ruled out first, because if it's present, then you already have your answer). This is also precisely why I stated earlier that I see no reason to believe that Randy Johnson was tanking games in Seattle in 1998 before being traded to Houston that season. At first glance, his numbers appear to tell a significantly different story (ERA of 4.33 in Seattle and 1.28 in Houston). But when you dig in closer and look at the confidence intervals associated with those deltas, and look at his FIP, K/9, and BABIP values, and the confidence intervals around those, you'll see that they all overlap. We simply don't have enough data to say that those numbers are truly different, even though they certainly appear to be, and read that way to the non-statistician.

But these things do in fact matter. This isn't just some statistician's "opinion". We can actually calculate these things mathematically. We can also calculate the precise probability that pitcher A will have a lower ERA than pitcher B by the end of the season based on their differences at the all-star break. And if the formula says that pitcher A is 50% likely to have a higher ERA than pitcher B, based on their current ERAs and the confidence intervals associated with them, and if we run those comparisons for all pitchers in the league, we really will be "wrong" on 50% of them at the end of the season because these confidence intervals are real-world probabilities that will play out in the future. That's the beauty of the discipline of statistics. It's all based on sound theory that has been proven mathematically.

[Snowman]

Originally Posted by G1911

Well, he pitched for 21 years which seems like a lot, but it was only 5,008 innings. The sample is just too small. Maddux was lucky. Also a bum because only K pitchers who played after Spahn, except for Koufax who is exempted because I don’t know, are any good.

I'll give you $1k right now if you can repeat my arguments in a way I'll sign off on. Good luck.