Best lefty off all time? My vote is Koufax!

[Snowman]

Randy also posted a 0.337 BABIP during his time with Seattle in 1998 before being traded, which was almost the highest BABIP he posted in his entire career. This means that the ever so slightly elevated numbers he posted that season in Seattle were entirely explainable simply by bad luck. Nothing about his statistics from 1998 are indicative of him throwing games or pitching worse than he was capable of during his stint with Seattle. This is not just my opinion or me trying to say something controversial. It's a simple fact. If you disagree, you simply don't understand how statistics works with sample sizes, variance/luck, and confidence intervals.

[Tabe]

Originally Posted by Snowman

Randy also posted a 0.337 BABIP during his time with Seattle in 1998 before being traded, which was almost the highest BABIP he posted in his entire career. This means that the ever so slightly elevated numbers he posted that season in Seattle were entirely explainable simply by bad luck. Nothing about his statistics from 1998 are indicative of him throwing games or pitching worse than he was capable of during his stint with Seattle. This is not just my opinion or me trying to say something controversial. It's a simple fact. If you disagree, you simply don't understand how statistics works with sample sizes, variance/luck, and confidence intervals.

"ever so slightly elevated numbers", LOL.

[Peter_Spaeth]

If 2/3 of a season is too small a sample size to make any meaningful observations that exclude good or bad luck, as apparently is the case for Randy Johnson 1998 and his slightly elevated first 2/3 numbers, why is a full season really that much better? Maybe we should just junk the Cy Young award, since it's just rewarding randomness.

[BobC]

Originally Posted by Peter_Spaeth

If 2/3 of a season is too small a sample size to make any meaningful observations that exclude good or bad luck, as apparently is the case for Randy Johnson 1998 and his slightly elevated first 2/3 numbers, why is a full season really that much better? Maybe we should just junk the Cy Young award, since it's just rewarding randomness.

Careful there Peter, you're using too much logic and sense for some people!

[Peter_Spaeth]

Originally Posted by BobC

Careful there Peter, you're using too much logic and sense for some people!

I also question some "oh it's too small a sample size" arguments. Those always seem to me to reflect cherry-picking, to dismiss inconvenient stats that don't fit the theory. We used to see that argument all the time here to rebut the theory that Kershaw was not a good post-season pitcher; his lousy performances were just random events and couldn't possibly reflect that he wilted under pressure. Of course after a full season worth of postseason outings there's still a huge disparity so maybe that argument has been retired.

Of course when the stats do fit the theory, we don't see the sample size argument so much.

[BobC]

Originally Posted by Peter_Spaeth

I also question some "oh it's too small a sample size" arguments. Those always seem to me to reflect cherry-picking, to dismiss inconvenient stats that don't fit the theory. We used to see that argument all the time here to rebut the theory that Kershaw was not a good post-season pitcher; his lousy performances were just random events and couldn't possibly reflect that he wilted under pressure. Of course after a full season worth of postseason outings there's still a huge disparity so maybe that argument has been retired.

Of course when the stats do fit the theory, we don't see the sample size argument so much.

And by any chance could the fact that pitchers end up facing the best teams during the playoffs and WS possibly be a factor in their not-so-stellar playoff performances also? Or how about those pitchers where age, injuries, the long regular season, and other factors would then catch up to them at playoff time? Corey Kluber may be a great example of that particular set of circumstances. A fantastic pitcher and Cy Young winner, Corey was always focused and ready to go. But as he'd head into the postseasons, it always seemed like he'd run out of gas or nagging regular season injuries finally caught up to him. Still, when he was right and rested, he could hang with the best of them.

The one other thing you said that I really like is in reference to the possibility that someone like Kershaw could also possibly wilt under post season pressure. Now I'm not saying he does, but I think ALL people realize and recognize that stress can and does affect every single one of us, and does so differently depending on the unique set of facts and circumstances a person is presented with. That is a prime example of one of those human elements I keep harping on about that statisticians can't possibly ever effectively measure and fully account for in their equations, formulas, and algorithms. They may try to tell that they in fact do have such variables and factors accounted for, until you ask them to show you and prove it to you, and then you get the excuses about how you wouldn't understand, or it would take too long, and so on.

Now I actually don't doubt that statisticians may in fact try to account for human variables like luck, stress, heart, competitiveness, or whatever, but since there is no real way to effectively measure and quantify such human variables in their work, the things they do to account for them are at best, SWAGs, and at worst, WAGs. And a guess is basically no more than someone's opinion, maybe an educated one, but still an opinion, no more, no less. Not ever saying a statisticians work is bad, just that they should be honest and admit what it actually is, their (very) educated guess more often than not.

[Peter_Spaeth]

Is there a statistic that tracks the deer in the headlights look that (unfortunately, as I like him) Kershaw gets time after time after time in the post season?

[cammb]

This is way off the subject. You guys are probably boring other readers. Let’s end it now. Koufax is the GOAT period. Good night

[cardsagain74]

Originally Posted by Peter_Spaeth

I also question some "oh it's too small a sample size" arguments. Those always seem to me to reflect cherry-picking, to dismiss inconvenient stats that don't fit the theory. We used to see that argument all the time here to rebut the theory that Kershaw was not a good post-season pitcher; his lousy performances were just random events and couldn't possibly reflect that he wilted under pressure. Of course after a full season worth of postseason outings there's still a huge disparity so maybe that argument has been retired.

Of course when the stats do fit the theory, we don't see the sample size argument so much.

And sometimes people don't look at it a little deeper (when they want to dismiss an argument). Like you said, it's not always just as simple as "postseason doesn't matter" because of the sample size.

Willie Mays hit one homer in 134 postseason plate appearances, and that was at the end of a game that was 8-1. So, basically none.

If you assume that 100 of Mays' 134 postseason PAs were relevant (for lack of a better word), the chance of him hitting no homers in those (given his lifetime HR rate) is around .005.

Even if you factor in how it's tougher to hit homers against the quality of championship-level pitching, that's still way too out there on the bell curve to assume that it's just random statistical noise.

[Snowman]

Originally Posted by Peter_Spaeth

If 2/3 of a season is too small a sample size to make any meaningful observations that exclude good or bad luck, as apparently is the case for Randy Johnson 1998 and his slightly elevated first 2/3 numbers, why is a full season really that much better? Maybe we should just junk the Cy Young award, since it's just rewarding randomness.

If it gets awarded to whoever has the best W/L record and the best ERA, then yes, it is borderline meaningless. As has been mentioned earlier in this thread, the award has gone to countless pitchers over the years who clearly did not deserve it.

But it wouldn't be that difficult to make it meaningful. They just need to look at the right statistics. They finally figured this out for offensive players. Maybe they'll come around sooner or later with pitchers too? Who knows.

[Peter_Spaeth]

Originally Posted by Snowman

If it gets awarded to whoever has the best W/L record and the best ERA, then yes, it is borderline meaningless. As has been mentioned earlier in this thread, the award has gone to countless pitchers over the years who clearly did not deserve it.

But it wouldn't be that difficult to make it meaningful. They just need to look at the right statistics. They finally figured this out for offensive players. Maybe they'll come around sooner or later with pitchers too? Who knows.

Sample size is just as small for all statistics, no?

[carlsonjok]

Originally Posted by Snowman

IThey just need to look at the right statistics. They finally figured this out for offensive players.

Oh, really?

[Snowman]

Originally Posted by Tabe

"ever so slightly elevated numbers", LOL.

Laugh all you want, but the numbers that actually matter, the ones that aren't subject to luck were nearly identical to his prior years (12.0 K/9 vs 12.3, 3.4 BB/9 vs 3.3, 3.35 FIP vs 2.82 and 3.42). If that's not "ever so slightly elevated", then I don't know what is.

But you can keep looking at ERA if you want to. The imbeciles always do.

[Peter_Spaeth]

Originally Posted by Snowman

Laugh all you want, but the numbers that actually matter, the ones that aren't subject to luck were nearly identical to his prior years (12.0 K/9 vs 12.3, 3.4 BB/9 vs 3.3, 3.35 FIP vs 2.82 and 3.42). If that's not "ever so slightly elevated", then I don't know what is.

But you can keep looking at ERA if you want to. The imbeciles always do.

Those are the product of the same set of games you dismissed as being too small a sample size to be meaningful, so why are they now meaningful when they favor your argument?

[Snowman]

Originally Posted by Peter_Spaeth

Those are the product of the same set of games you dismissed as being too small a sample size to be meaningful, so why are they now meaningful when they favor your argument?

Because the sample sizes needed for those statistics is remarkably smaller than it is for ERA, and thus their corresponding confidence intervals are much narrower. This is because they are not nearly as subject to luck as ERA is. It takes years for ERA to converge. It takes months for K/9, BB/9, and even FIP.

[Tabe]

Originally Posted by Snowman

Laugh all you want, but the numbers that actually matter, the ones that aren't subject to luck were nearly identical to his prior years (12.0 K/9 vs 12.3, 3.4 BB/9 vs 3.3, 3.35 FIP vs 2.82 and 3.42). If that's not "ever so slightly elevated", then I don't know what is.

But you can keep looking at ERA if you want to. The imbeciles always do.

So a 20% jump in FIP is "ever so slightly"?

His home runs were up 40%. OPS was up 20%. Line drive% was up 33%. All that stuff says guys were hitting the ball hard off of him A LOT more than the previous year - and the rest of 1998 and the next four years.

Please specify the EXACT number of starts and/or innings to qualify as NOT a small sample size. Just for grins.

p.s. Name-calling reflects poorly on you. Do better.

[Peter_Spaeth]

Originally Posted by Tabe

So a 20% jump in FIP is "ever so slightly"?

His home runs were up 40%. OPS was up 20%. Line drive% was up 33%. All that stuff says guys were hitting the ball hard off of him A LOT more than the previous year - and the rest of 1998 and the next four years.

Please specify the EXACT number of starts and/or innings to qualify as NOT a sample size. Just for grins.

p.s. Name-calling reflects poorly on you. Do better.

Irrelevant man. Once the ball leaves the bat, it has nothing to do with the pitcher, it's just dumb luck and coincidence, or a function of other factors beyond the pitcher's control such as fielding. BABIP is binary -- either it's a hit or it's not -- and the rest is meaningless. Besides, every number you cite suffers from small sample size and confidence interval issues -- only numbers that support the thesis that his first half was just random are reliable.

All pitchers are essentially fungible beyond their ability to strike batters out. Maddux is the same as any other 6K/9 pitcher you can name. Johnson's K's stayed up, so all the rest is noise.

[G1911]

If it was all dumb luck, then BABIP would, over the course of long careers, all come out about the same when you factor in the defense behind the pitcher. There would not be pitchers who have incredibly successful and long careers, not giving up many runs, while being contact instead of strikeout pitchers. It doesn’t.

If it’s all dumb luck, how are contact pitchers often just as successful as strikeout pitchers? Maddox and Randy Johnson put together similar total careers. Johnson’s BABIP is league average, Maddux, like most hall of fame contact pitchers, is well below it. They achieved similar ERA’s and total careers via very different methods, in huge sample sizes.

[Peter_Spaeth]

Originally Posted by G1911

If it was all dumb luck, then BABIP would, over the course of long careers, all come out about the same when you factor in the defense behind the pitcher. There would not be pitchers who have incredibly successful and long careers, not giving up many runs, while being contact instead of strikeout pitchers. It doesn’t.

If it’s all dumb luck, how are contact pitchers often just as successful as strikeout pitchers? Maddox and Randy Johnson put together similar total careers. Johnson’s BABIP is league average, Maddux, like most hall of fame contact pitchers, is well below it. They achieved similar ERA’s and total careers via very different methods, in huge sample sizes.

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

[Tabe]

Originally Posted by Peter_Spaeth

Irrelevant man. Once the ball leaves the bat, it has nothing to do with the pitcher, it's just dumb luck and coincidence, or a function of other factors beyond the pitcher's control such as fielding. BABIP is binary -- either it's a hit or it's not -- and the rest is meaningless. Besides, every number you cite suffers from small sample size and confidence interval issues -- only numbers that support the thesis that his first half was just random are reliable.

All pitchers are essentially fungible beyond their ability to strike batters out. Maddux is the same as any other 6K/9 pitcher you can name. Johnson's K's stayed up, so all the rest is noise.

I appreciate you clearing it up for me. It seems so simple when you explain it that way.