Best lefty off all time? My vote is Koufax!

[cjedmonton]

Originally Posted by Peter_Spaeth

Johnson gets no hobby love. His RCs in the same sets sell for a fraction of Griffey's.

Sad, but so true.

To be fair, pitcher-hitter hobby disparity aside, Johnson was a late blooming 25 year old still trying to find himself in ‘89…and was a solid 4 years away from resembling anything like the Big Unit.

Meanwhile, Griffey hit the ground running as a teenager the same year and never looked back.

Both eventually became titans at their position, but the hobby loves the long ball. That much cannot be argued.

[Carter08]

Randy Johnson won MLB’s Warren Spahn Award as the best lefty the first four times it was issued. Not the Grove Award or the Koufax Award. Just sayin’.

[Bigdaddy]

Originally Posted by Snowman

Ignoring your personal attacks... I'd be remiss if I didn't point out that there ARE statistics that answer this question though. This is precisely what the entire field of statistics was developed for. The entire point of the mathematical discipline of statistics is to be able to make probabilistic estimates about the outcomes of future events using whatever data we have available. The more skilled you are as a statistician, the more accurate your predictions are. As far as your question goes about how much impact a SP has over final outcomes depending on how many innings he pitches, I assure you this exact problem is well understood. In fact it is extremely well understood. It is by far, the single most important factor in the models I build for betting on baseball games. It is also the single most important factor that the sports book handicappers use in their models when they set the betting lines. There are many other factors at play, but at the end of the day that entire industry is about predicting the outcomes of future events with data and statistical theory. And the casinos are pretty damn good at making predictions.

This is also how and why the entire field of sabermetrics was developed. People wanted to bet on baseball games but they quickly realized that the standard statistics that have been used for decades were not very useful for making predictions with because many of those stats are highly subject to luck. So they engineered new statistics that account for factors outside of an athlete's control and that focus in on what they actually have power over. The aspects of their game that are within an athlete's control are the only factors that have predictive power with respect to how well (or how poorly) they will perform in the future. Any statistic that cannot accurately predict future performance is a poor choice for evaluating one's skill level. Knowing that someone is hitting 0.375 at the all-star break tells us very little about how well he will hit for the rest of the season despite it being a seemingly large sample size of 350 at bats. A deceiving statistic like batting average is another great candidate for paving the way for another heated debate between a regular baseball fan and a statistician. One could ask "who is the best hitter this season?" and the casual fan will point to the guy with the 0.375 AVG, but the statistician looks deeper and points out that he benefited from having a 0.430 BABIP while player B is hitting 0.369 with a 0.300 BABIP. In this case, player B would be the clearly better hitter despite having the lower batting average since BABIP is useful for understanding how much of a role luck played in their performances.

People keep talking about wins here as ultimately being the only thing that matters. I agree. Winning games is what matters most. That's why we statisticians use Wins as the dependent (or target) variable in our predictive models. But the difference is that you guys seem to be conflating the "wins" statistic that is awarded to a pitcher with the actual wins and losses which can only be attributed to the teams. These are not the same thing. A pitcher cannot win a game. Assigning them "wins" and "losses" has always been a bad measure of performance. Not just in the modern era. And it turns out that a pitcher's win-loss record is actually an extremely poor predictor of a team's likelihood of winning a game. And furthermore that in the presence of other statistics, it is in fact not predictive at all of their likelihood of winning a game. This is why it is a poor measure of performance. It tells you nothing at all about how well they pitched or are likely to pitch in the next game. It only tells you what the outcome was of a set of prior games. If you want to know how "good" a pitcher (or hitter) is, then you have to look at statistics that only they can control. Otherwise, you're looking at how lucky or unlucky they got rather than how well they performed. This is the job of the statistician. To find the signal in the noise. To control for factors outside of their control. To remove elements of luck.

I find it humorous that when I posted in the thread about the role of artificial intelligence in grading cards that everyone praised and valued my inputs when it seemed to reinforce their views about grading. But when my views are shared here, where they are in conflict with the majority opinion, everyone shits on me.

So what did your statistics predict that Koufax would do in 1967??? That's the big hangup with Sandy - he didn't pitch long enough for many to consider him the best left-handed pitcher in MLB. Just how short does the window need to be before you deem it 'too short'? Four years? Two years? A single season? A single game? One pitch?? To me, if you are going to be considered 'the best', you've got to balance peak with longevity. Integrate under the curve.

[Peter_Spaeth]

Originally Posted by Mark17

Randy led the league in ERA 4 times and in wins once. His post season record was just 7-9. He was a solid pitcher and deserves to be in the conversation, but I'll still take Grove, then Spahn of the lefties, and Walter for best overall.

If you lined up all the pitchers in the game in 1960, the guy who all the coaches and scouts would be drooling over, concerning raw ability and potential, wouldn't be Koufax, Drysdale, Spahn, Gibson, Pierce, Ford, Pascual, or any of those guys. It would've been a fellow named Steve Dalkowski.

You're cherry picking on Johnson. Don't forget 5 Cy Youngs, 3 2nds and a 3rd. Solid pitcher is just a bit of an understatement.

[cjedmonton]

Originally Posted by Carter08

Randy Johnson won MLB’s Warren Spahn Award as the best lefty the first four times it was issued. Not the Grove Award or the Koufax Award. Just sayin’.

Touche.

Love that Spahn has his own award, but the list of winners is somewhat dubious beyond Johnson, Kershaw, and Sabathia. Then again, so is the Cy Young Award. Mike Flanagan and Willie Hernandez anyone?

https://en.m.wikipedia.org/wiki/Warren_Spahn_Award

EDIT: Hot off the press…add Robbie Ray to the list of lefty Cy Young and likely Spahn Award winners.

[bnorth]

Originally Posted by Peter_Spaeth

Johnson gets no hobby love. His RCs in the same sets sell for a fraction of Griffey's.

Some of the 89 Fleer Randy Johnson Marlboro versions have gone crazy. I know of one that recently went for $13,000. Even the more normal versions have greatly increased in price over the last year.

[Peter_Spaeth]

Originally Posted by bnorth

Some of the 89 Fleer Randy Johnson Marlboro versions have gone crazy. I know of one that recently went for $13,000. Even the more normal versions have greatly increased in price over the last year.

OK, but can't you get his Upper Deck RC in PSA 10 for not much more than $100?

[Mark17]

Originally Posted by Peter_Spaeth

You're cherry picking on Johnson. Don't forget 5 Cy Youngs, 3 2nds and a 3rd. Solid pitcher is just a bit of an understatement.

How many would Grove have won, had the award existed?

Since some want to discount or dismiss win-loss stats, is ERA to be considered the best gauge? Johnson, against his peers, led his league in that stat exactly 4 times in his 22 year career. Grove led his league in ERA 9 times in his 17 year career.

[Peter_Spaeth]

Originally Posted by Mark17

How many would Grove have won, had the award existed?

Since some want to discount or dismiss win-loss stats, is ERA to be considered the best gauge? Johnson, against his peers, led his league in that stat exactly 4 times in his 22 year career. Grove led his league in ERA 9 times in his 17 year career.

Where did I say a single word against Grove? I ranked him first and have not backed off that.

[cjedmonton]

Originally Posted by Mark17

How many would Grove have won, had the award existed?

Since some want to discount or dismiss win-loss stats, is ERA to be considered the best gauge? Johnson, against his peers, led his league in that stat exactly 4 times in his 22 year career. Grove led his league in ERA 9 times in his 17 year career.

Has a “Cypothetical Young Award” thread or poll ever been tossed around here for pre-1956?

[Mark17]

Originally Posted by cjedmonton

Has a “Cypothetical Young Award” thread or poll ever been tossed around here for pre-1956?

That's a neat idea. They have veterans committees to consider former ballplayers for exclusion in the Hall. There could likewise be some sort of committee to retroactively award Cy Young awards for pre- 1956 seasons.

It would be fun to pick a specific season and have a poll, as you suggest, to decide who the Cy winner would've/should've been.

[Carter08]

Originally Posted by Mark17

That's a neat idea. They have veterans committees to consider former ballplayers for exclusion in the Hall. There could likewise be some sort of committee to retroactively award Cy Young awards for pre- 1956 seasons.

It would be fun to pick a specific season and have a poll, as you suggest, to decide who the Cy winner would've/should've been.

I like it

[bnorth]

Originally Posted by Peter_Spaeth

OK, but can't you get his Upper Deck RC in PSA 10 for not much more than $100?

Yes it is just the 89 Fleer Marlboro versions that have taken off and it wasn't too long ago they went for a couple bucks each.

[HistoricNewspapers]

Originally Posted by G1911

First, I don't entirely disagree. If we abandon "who had the best contextual career" framing to make it "what pitcher, if in their prime, was dropped in 2021 without any preparation would do the best", it's probably Randy Johnson. His career numbers are amazing, and he was a power pitcher who didn't put it together until he was 29 years old. Imagine if he figured it out at 25. Putting things in context of time and place, I would put Randy #2 behind Grove, though he is my #1 favorite and personal preference, as he is the one I grew up watching and we share a hometown.


I do think this chart, which I believe has been posted a few times now, is extremely misleading, at best. It just stops tabulating for Grove half way down Grove pitched more than 8 full seasons that are included here, he won 9 ERA crowns alone plus other full seasons. It's just factually wrong and really should stop being used. I think any reasonable person here should agree. I'm open to being the fool if there is any good reason this chart, which ignores much of Grove's career and implies he played 8 seasons, is somehow valid.

The chart was more in relation to Koufax....Grove was just added for peak comparison....hence not all filled in for Grove and so I could have room to emphasize that Koufax was not contributing anything while Johnson was(while Grove was too).

No question Grove had a better career than Koufax.

There is no sensible argument that puts Koufax ahead of either Grove or Johnson. They both had Koufax's peak and they added a couple more four year peaks on top of that.

It really does come down to Grove and Johnson, but when you take into account the population factor of available VIABLE humans to compete against, and the fact that Grove's era actually went out of its way to eliminate a segment of the population to compete....and when you consider that Johnson had superior physical attributes that are the only known 100% measureables, then Johnson walks away as number one.

Johnson had tougher peers to outdistance.

[Snowman]

Originally Posted by AndrewJerome

This is a fascinating subject. I really enjoy analyzing baseball history and player performance.

There seem to be a few disconnects in this debate.

One disconnect is how much weight to place on counting stats. Pro-Spahn posters in this thread rely on longevity and counting stats with what appears to be a decent peak, with a pretty good ERA+ across his peak years etc. Anti-Spahn posters believe he was a pretty average pitcher in regard to “stuff” since his K/9 doesn’t blow your hair back and wins are team dependent. He pitched a lot of innings and a lot of years, but innings eaters can’t get to GOAT status if they don’t provide elite innings. Essentially that Spahn’s peak is not enough to be the best lefty ever, even with all the counting stats. Koufax’s stats are obviously much different. One very good year, 5 off the charts years, some mediocre years, early retirement and nowhere near the overall counting stats of Spahn. Anti-Koufax posters essentially dismiss him outright because his lack of counting stats eliminate him from lefty GOAT status. He essentially didn’t pitch long enough to even be in the conversation. I tend to agree that the weaknesses of both Spahn and Koufax as described above eliminate them from lefty GOAT status. Both clearly were great pitchers though.

Another disconnect here is how to compare players by era. Snowman appears to be arguing that Grove’s pitching competition was weak and therefore his stats should be discounted a great deal. The ERA titles, ERA+ etc is tainted by weak pitching competition. Essentially that Grove was much better than his pitching peers, but since his pitching peers were very bad, him being much better than them should not be as impressive as the stats appear. I have always wondered about this, but I have no way of figuring out how to crunch the numbers to argue one way or the other. The 1920s / early 1930s batting averages went nuts. Hitters went crazy. How much of this was a result of bad pitching during those years? Anyway, Snowman, I am curious how stats can help us figure out which time periods were strong and which time periods are weak. It has always been something of a mystery to me. On a similar note, WAR is a bit misleading to me since it seems to value relative to replacement where replacement level is determined differently every year. The value of a replacement level player could be very different in a time period where quality of play overall is very high as compared to a time period where quality of play was lower. But how in the world can we figure out relative quality of play?

First, I have to say thank you for actually reading my posts and summarizing my views in a way that I could actually sign off on. You're the first person here who has even made an attempt to understand what I've said without intentionally trying to distort it.

As far as how it could be calculated, there are several options. My preferred approach would be to build a hierarchical mixed-effects model (which controls for both fixed-effects and random-effects simultaneously). These models are extremely powerful. You could create time blocks for various periods where something of note happened (like 1942-1946 when the talent pool was heavily diluted due to players leaving for WW2), or pre-1950 for larger strike zones, or 1950-62 for larger strike zones, etc. You would hard code those into your data and treat them as fixed-effects. We could also control for offensive efficiencies of each era by measuring the delta between runners left in scoring position, among countless other ways (offenses were considerably less efficient when Grove was pitching). We could also control for a pitcher's ability to control the ball across eras by including their K/BB ratios and capturing the interaction of that metric against K/HRs since strikeout rates are both a function of how well a pitcher pitches and what strategies are employed by the hitters. If that relationship is non-linear, we could apply a mathematical transformation (like the square root, cubed root, log, etc.) that enables us to create a linear relationship which would then have predictive power in a model like this. Worth noting is that there is an extremely strong correlation over time between strikeout rates and HRs because swinging for the fences results in striking out more often. I would also include several rate stats that contrast the ratios between batting average and OPS over time, as this has a measurable effect on pitching statistics across eras. Also worth including is the relationship between league-wide ERA and WHIP over time and looking for gaps in that ratio. If WHIP values were high, relative to ERAs, that would be indicative of pitchers ERAs having benefitted from inefficient offenses (and something that Grove and his peers on the mound surely benefitted from, perhaps tremendously). Something else worth noting (and I suppose this is a hint of sorts for something I referenced earlier) is that it's more important to know a pitcher's strikeouts per plate appearance than it is to know their K/9. There are also differences in approach over time. Ted Williams talks about just "putting the bat on the ball" and how that made him a "better hitter" than he would have been if he tried to hit home runs. While yes, it gave him a better batting average, we now know that this isn't what makes someone a "better hitter", at least not in the sense of producing more runs and winning more games. We would also need to control for mound heights at each ballpark over time. We could treat the individual players' performances as random-effects while treating the other metrics we are interested in estimating as fixed-effects, while simultaneously adjusting for age. We could also look at the differences in slopes of the age curve calculations over time and how those slopes have changed. The flatter the curve, the less skilled their peers are, and the steeper the curve, the stronger the opposition. The beauty of using this approach with the hierachical multilevel models, as opposed to using something like standard regression or econometric type models, is that it uses recursive algorithms which output extremely accurate coefficients that are capable of producing different slopes AND intercepts for each cohort as opposed to all using the same slope with different intercepts like you'd get from multiple regression models. The overlap of players playing across different eras (in aggregate, not just cherry-picking one or two players) allows us to measure the differences in the overall skill level of each time period we are interested in (again, adjusting for age and all of the other factors simultaneously). One thing worth keeping in mind is that it's not so much that hitters from the 1930s were "worse" hitters in the sense that they were less capable (although surely, this is also true), but rather that they were "worse" hitters in the sense that they employed sub-par hitting strategies (e.g., they bunted too often and just tried to "get a bat on the ball" rather than just swinging from their heels like Babe Ruth and Lou Gehrig did). We would also want to adjust for the overall talent pool of players in the league and the populations from which they were drawn from. Professional athletes are sampled from the right tail of a Gaussian (or "normal") distribution. They are the best of the best. The ratio of the number of players in the league vs the number of total possible baseball players from which they could have been drafted is extremely important, as this effectively tells us where along that normal distribution that this talent level lies. The larger that ratio, the further to the left they are on that distribution, and the smaller that ratio, the further to the right they are. And the further the league is to the left on that curve, the less skilled they are as a whole. If one era is 3 standard deviations to the left, we can extremely confident that we're effectively watching something that amounts to something like single-A ball today with a handful of star players sprinkled in. A prime example of this is the fact that I played varsity basketball at my high-school. However, the reason I was able to make the team wasn't because I was some elite athlete, but rather because there were only about 200 students in my high-school. Had I attended a much larger school, I might not have even made the JV squad. There were probably only one or two kids on my entire team, if any, who could have made the team on a much larger school. However, their stats would have certainly gone down if they did. They might have averaged 20 ppg and 8 rebounds on my team, but only 12 ppg and 5 rebounds on the team with better players and stronger opponents. Baseball is no different. Player talent pools grew over time. The earlier years, while still fun and nostalgic, were simply not nearly as strong as they are today. Just watch some of the available footage from that era. Half those pitchers look like Weeble Wobbles on the mound with their "deliveries". Those guys were not throwing heat.

I often use these sorts of models when I'm building predictions for NFL games. If a team's starting center is injured and will miss the game on Sunday, I can use these types of models to predict the impact that his absence will have on the spread (hint, it's more you'd probably think).

We could also make retrodictions about things like how fast they pitched in the 1920s by looking at the evolution/progression of other similar sports for which we actually do have data. One option could be to look at the history of javelin and discus throwing records in the Olympics over time and see how well human performance correlates to the progression of pitching stats during the periods for which we have data for both, and regress pitching stats retrodictively against those other throwing sports to yield directionally accurate estimates for the pitching stats from the eras where we didn't have radar guns. While I haven't run the numbers yet, I'm extremely confident that there's no way in hell anyone in the 1920s was throwing a baseball 100 mph. It's worth pointing out that all of these anectodal stories about players saying that Walter Johnson (or pick your favorite hero) was the hardest pitcher they ever saw don't really mean all that much. The plural of anecdote is not data. When I was in middle school, I played against pitchers who were throwing ~70-75 mph. I still vividly remember to this day, going to the batting cages during that time and entering the 90 mph cage. I just remember laughing and thinking, "how the hell am I supposed to hit that?" Speeds are all relative. Walter Johnson throwing the ball 10 mph faster than the 2nd fastest guy doesn't mean all that much when we don't know how hard the other players are throwing. Everyone just knows that he throws "heat" relative to what they're accustomed to. He very well might have been throwing the ball a mere 90 mph, but it "felt like 100 mph" to anyone standing at the plate who was used to swinging at 80 mph "fastballs".

[HistoricNewspapers]

Koufax had 23 shutouts in 85 career starts at Dodger stadium.
Koufax had 17 shutouts in 229 career starts everywhere else.

If someone looks at that and still believes that Koufax was not helped by pitching in Dodger stadium, then they are simply not taking an objective look at things.

Which like I said above...since Koufax backers like to use the "what if." What if Koufax pitched half his games in Coors field in the 1990's early 2000's....you would never hear a thing about his complete games, shutouts, or World Series wins....they wouldn't exist and neither would this thread.

[Snowman]

Originally Posted by HistoricNewspapers

Randy Johnson is best lefty of all time and is in serious discussion for best pitcher of all time as well.

To get to your question, any argument to be made that Koufax's peers were better than Grove's also means that Randy Johnson's were better than Koufax's. Johnson's were indeed better than Koufax's, as were Koufax's better than Grove's.

The measurable's such as running speed, throwing speed, height, strength, bat speed, all show that players have gotten continually better generation after generation. This is fact. I can show more charts in another post. It is not a matter of evolution, although selective breeding is a factor. Most of it is a result from the sheer number of population growth and the addition of more parts of the world to draw players from.

Realize that we are on the cusp of having 8 billion people in the world right now to draw from, compared to 2001 where there were 6.2 billion, to 1965 where there were only 3.8 billion people in the world to draw from...and in 1935 appx 2.3 billion.

In reality, Grove and Koufax's population in the US and world wide viability of players to choose from, were closer in comparison. Wheras Johnson had it tougher, and anyone after Johnson even tougher.

People from yesteryear don't like to hear that. I'm from yesteryear, but the reality is the reality.

When you add the selective breeding of people who have found mates with the purpose of creating athletic off spring to make millions, and the advances in sports science to train them at a young age to maximize their MPH(with command) and their bat speed, that creates a vast difference between generations above and beyond what the logic of more people to draw from creates.

Of course Grove's generation actually excluded minorities from the US, making his peers even more worse than Koufax's.

However, in 1965 the league was still 78% white. In 2001 it was only 60% white so it is clear that the pool of players reached further out in 2001 than in even 1965. 1965 was still more homogonized than 2001.

That is X many more people in the world who can throw 95 MPH(with control) for Johnson and modern players to compete against, X many more people who can hit 430 foot home runs, X many more people who can throw a cannon from the hole at SS, etc...

There is more of that to expound upon and I will in a week, but Johnson does not even need that aspect to best Koufax. It really isn't that close, and I address some of the common things the Koufax camp says(and have addressed them earlier in the thread).

Best ERA+ seasons:
Johnson....Koufax.....Grove
197........190............217
195........186............189
193........160............185
188........159............185
184........143............175
181........122............165
176........105............160
152........101............160
135.........93
135.........Not good enough to pitch enough innings to qualify
118.........Not good enough to pitch enough innings to qualify
112.........Not good enough to pitch enough innings to qualify


Johnson had unrivaled physical tools. No pitcher in MLB history can match his physical tools. He was six foot eleven and threw over 100 MPH with a ridiculous slider....WITH COMMAND(after a few year learning curve). Some pitchers had one or two of those tools, but nobody had ALL of those tools like he did.

Let me explain why the physical tools are of such importance. Why would you take another pitcher over Johnson if the other pitcher was ten inches shorter, threw three miles an hour slower, had lesser command, and similar or less breaking pitches? The only other factor would be mental make up. Do they have the ability to handle being a professional player? Johnson obviously answered that question. Do they have the mental ability to thrive for a long time? Johnson answered that question YES.

Environments a player plays in severely muddles or hides statistical measurements, but the tools are concrete. The tools are a known. A lot of the statistical measurements are unknowns because environment muddles them. An environment can give false perceptions of ones true ability. Six foot eleven cannot be muddled. 100 MPH cannot be muddled. Nasty slider cannot be muddled. Command cannot be muddled. The only other obstacle is mental make up and thrive to succeed. He obviously passed that only unknown hurdle.

So when you are weighing all this, the physical tools play a vital role in solving the dilemma of cross era comparison.

Johnson had the results to back it up.

Johnson was umpire proof. He didn't need the inches off the plate like Maddux and Glavine often did to excel to the levels they did.

He was era proof. He didn't need lineups in the league where numbers six through nine were zero threats and hit basically zero power...like which occurred in other eras where scoring was depressed, or era's like the 30's where only the elite few were legit power threats.

In fact, he pitched in probably the toughest era to be a pitcher, with the live ball, DH, and steroids. Any pitcher that can handle the toughest environment to pitch in, surely would have no problem in the eras where it was pitcher friendly.

He didn't need a dead ball to excel or last a long time.

Johnson was stadium proof. He didn't need to rely on a certain stadium to make him dominant. Make no doubt, DOdger stadium helped Koufax tremendously.

Johnson had peak dominance and longevity dominance.

He was the guy that if you lined all these historic pitchers up at a local baseball field standing shoulder to shoulder, then watched him unleash what he had, he would be the guy every single coach would pick. Coaches would be drooling.

If you want to play the "what if" game people do with Koufax, realize that JOhnson missed two plus seasons worth of starts in his prime too. What if johnson didn't get hurt?

What if Clemens was not taking steroids and then the second place finisher(randy johnson) adds TWO MORE Cy Youngs?

My favorite what if? What if Johnson got to pitch off an eight inch higher mound, and had strikes called at the chest??

What if Koufax pitched in Coors Field half his career games...then there wouldn't even be this thread because Koufax's numbers would look much different, even though his ability would not be any different

^^^This guy knows what he's talking about.

And while I say that I don't "know" who was best (because I haven't run the calculations necessary), gun to my head I'm picking Randy Johnson as well.

[Snowman]

Originally Posted by Mark17

Randy led the league in ERA 4 times and in wins once. His post season record was just 7-9. He was a solid pitcher and deserves to be in the conversation, but I'll still take Grove, then Spahn of the lefties, and Walter for best overall.

If you lined up all the pitchers in the game in 1960, the guy who all the coaches and scouts would be drooling over, concerning raw ability and potential, wouldn't be Koufax, Drysdale, Spahn, Gibson, Pierce, Ford, Pascual, or any of those guys. It would've been a fellow named Steve Dalkowski.

Here you go again with the Wins and Losses records as if they mean anything at all. Who cares if he was 7-9 in the post season or if he only led the league in Wins one time? You might as well be criticizing his hair color or number of tattoos. Please stop with this nonsense. Wins attributed to a pitcher do not matter. At all.

[Snowman]

Originally Posted by Mark17

How many would Grove have won, had the award existed?

Since some want to discount or dismiss win-loss stats, is ERA to be considered the best gauge? Johnson, against his peers, led his league in that stat exactly 4 times in his 22 year career. Grove led his league in ERA 9 times in his 17 year career.

No. Even ERA is highly subject to variance (read "luck"), which league they pitched in, and whether or not they pitched in a pitchers park.

Just go pick your favorite pitching seasons by your 10 random favorite pitchers. Then scroll down to the advanced stats section and look at the corresponding BABIPs for those seasons. I guarantee you those BABIPs will all be super low. In other words, those were the seasons they got the luckiest, not necessarily the seasons where they had the best stuff.

[Mark17]

Originally Posted by Snowman

As far as how it could be calculated, there are several options. My preferred approach would be to build a hierarchical mixed-effects model (which controls for both fixed-effects and random-effects simultaneously). These models are extremely powerful. You could create time blocks for various periods where something of note happened (like 1942-1946 when the talent pool was heavily diluted due to players leaving for WW2), or pre-1950 for larger strike zones, or 1950-62 for larger strike zones, etc. You would hard code those into your data and treat them as fixed-effects. We could also control for offensive efficiencies of each era by measuring the delta between runners left in scoring position, among countless other ways (offenses were considerably less efficient when Grove was pitching)..........

All of this is just listing many variables involved, and I'm sure many more can be added. The obvious difficulties that remain are:

1. How do these variables play together? Are they additive, multiplicative, subtractive, and to what degree. How do you combine and weigh them?

2. How do you value them, with respect to specific players?

For example, let's say you are comparing 2 pitchers who both have a right fielder with a .985 fielding average. But one has a weak throwing arm and the other is Clemente. How much does having Clemente help, with his reputation discouraging runners taking an extra base?

First you'd need to give a weight to the variable - what impact does the right fielder's reputation play? Second, you have to value Clemente.

Suppose there are two catchers with equal fielding percentages, and throw out equal percentages of baserunners. But one is a very astute signal caller and the other is a dolt. Take Grove having Cochrane for example. First, how much can a smart, observant catcher help a pitcher? Second, what value do you assign to Cochrane (or Roseboro?)

All you have done is thrown out a bunch of factors to consider. The real trick would be to come up with an algorithm that can effectively combine and weigh the variables, and then, there's the (sometimes subjective - like the brains of a catcher) value you assign to each specific player involved.

In short, the above is not anywhere close to an actual predictive model.

[Snowman]

Originally Posted by Mark17

All of this is just listing many variables involved, and I'm sure many more can be added. The obvious difficulties that remain are:

1. How do these variables play together? Are they additive, multiplicative, subtractive, and to what degree. How do you combine and weigh them?

2. How do you value them, with respect to specific players?

For example, let's say you are comparing 2 pitchers who both have a right fielder with a .985 fielding average. But one has a weak throwing arm and the other is Clemente. How much does having Clemente help, with his reputation discouraging runners taking an extra base?

First you'd need to give a weight to the variable - what impact does the right fielder's reputation play? Second, you have to value Clemente.

Suppose there are two catchers with equal fielding percentages, and throw out equal percentages of baserunners. But one is a very astute signal caller and the other is a dolt. Take Grove having Cochrane for example. First, how much can a smart, observant catcher help a pitcher? Second, what value do you assign to Cochrane (or Roseboro?)

All you have done is thrown out a bunch of factors to consider. The real trick would be to come up with an algorithm that can effectively combine and weigh the variables, and then, there's the (sometimes subjective - like the brains of a catcher) value you assign to each specific player involved.

In short, the above is not anywhere close to an actual predictive model.

The answers to most of your questions are explained above. The fact that you don't understand how a hierarchical mixed-effect model works (or even my high-level explanation of it) does not mean that it in fact does not work. I was responding to AndrewJerome, who asked, "The value of a replacement level player could be very different in a time period where quality of play overall is very high as compared to a time period where quality of play was lower. But how in the world can we figure out relative quality of play? If you want the coeffecients (or "weights") from such a model, you'd have to build one. But it's a LOT of work, and I don't see anyone here volunteering to pay me for my efforts. I'm simply explaining, at a very high level, how one could solve for it. I have better things to do with my time than to prove to you guys that Lefty Grove benefitted greatly from pitching in an era where his competition was lacking or that Babe Ruth was effectively swinging at home run derby "pitches" a significant percentage of the time. That much should be obvious to anyone operating on the right side of the bell curve.

[G1911]

Originally Posted by Snowman

The answers to most of your questions are explained above. The fact that you don't understand how a hierarchical mixed-effect model works (or even my high-level explanation of it) does not mean that it in fact does not work. I was responding to AndrewJerome, who asked, "The value of a replacement level player could be very different in a time period where quality of play overall is very high as compared to a time period where quality of play was lower. But how in the world can we figure out relative quality of play? If you want the coeffecients (or "weights") from such a model, you'd have to build one. But it's a LOT of work, and I don't see anyone here volunteering to pay me for my efforts. I'm simply explaining, at a very high level, how one could solve for it. I have better things to do with my time than to prove to you guys that Lefty Grove benefitted greatly from pitching in an era where his competition was lacking or that Babe Ruth was effectively swinging at home run derby "pitches" a significant percentage of the time. That much should be obvious to anyone operating on the right side of the bell curve.

No one's paying you to claim Ruth played in a home run derby (there were less home runs when he played than now) or that Spahn was mediocre or that Grove sucked because of his birth year. Yet here you are, incessantly making unsupported claims. Your time doesn't seem to be all that valuable either.

[BobC]

Originally Posted by cjedmonton

This has been a truly enjoyable thread, even if I’m out of my depth with much of the analysis.

Can’t help but wonder how the narrative would’ve unfolded with just the slightest tweak to the title:

Best Most revered lefty of all time? My vote is (still) Koufax!

Despite the iron clad arguments for Robert Moses, Warren Edward, and Randall David, none…and I mean none carried the mystique and the aura of Sanford. Metrics cannot adequately quantify that.

Also, his peak fell during a perfect storm of West Coast expansion, the end of the Golden Era, and the ushering in of the pitching era. It was the right time and the right place for a guy like Koufax to dominate the scene like he did. There were so many great pitchers during his time, but Koufax’s artistry was unmatched…even if his stats don’t support it.

CJ

Great points and interesting thought by slightly changing the question like that. Problem I can see in answering it though is that it gives an unfair bias/advantage to modern pitchers, like a Koufax, who we may have grown up with, or maybe our Father did and told us how great he was. We can read and learn about earlier players, but I fear for the vast majority of people, they're much more likely to throw their reverence towards a player they'd actually seen and grew up watching. Just basic human nature. And you can't really base a question like this on just people here on this forum. Let's face it, we're mostly a bunch of pre-war baseball card collecting nerds, and an extreme outlier when talking about the public in general. LOL

[Snowman]

Originally Posted by G1911

No one's paying you to claim Ruth played in a home run derby (there were less home runs when he played than now) or that Spahn was mediocre or that Grove sucked because of his birth year. Yet here you are, incessantly making unsupported claims.

The notion that modern athletes are far superior to those of a century ago isn't exactly a controversial statement in the real world. This might be the only community on earth who wishes to pretend otherwise.

Your time doesn't seem to be all that valuable either.

It takes minutes to respond to your ignorant drivel. It would take multiple weeks of full time effort to build out a statistical model like the one I described above. I build statistical models for people who are capable of understanding and appreciating them; of which there is no shortage.

[brianp-beme]

I am not following this thread, but thought I would chime in...I am tired of seeing the misspelling on the title thread "Best lefty OFF all time".

The thing is I can't shame the OP to change it because he is banned...maybe a moderator or Leon can make my life a little more 'of' and little less 'off'.

Brian (best Lefty is Lefty Grove, because he was obviously better than Lefty Gomez).

[G1911]

Originally Posted by Snowman

The notion that modern athletes are far superior to those of a century ago isn't exactly a controversial statement in the real world. This might be the only community on earth who wishes to pretend otherwise.



It takes minutes to respond to your ignorant drivel. It would take multiple weeks of full time effort to build out a statistical model like the one I described above. I build statistical models for people who are capable of understanding and appreciating them; of which there is no shortage.

I've never argued that modern athletes are not superior in many ways. You take it to extreme lengths, and apply it very inconsistently where it is true for one pitcher and not true for his exact contemporary. All you do is make up some crap, fail to back up any of it, and insult people.

[Snowman]

Originally Posted by G1911

I've never argued that modern athletes are not superior in many ways. You take it to extreme lengths, and apply it very inconsistently where it is true for one pitcher and not true for his exact contemporary. All you do is make up some crap, fail to back up any of it, and insult people.

You interpret my claims as being extreme because I say something like "I'm taking Hyun Jin Ryu over Warren Spahn any day". Obviously, I said that knowing it would get a rise out of you, but I'm also not joking. Hyun Jin Ryu has better stuff than Warren Spahn had. Ryu is a pretty good pitcher. He was 2nd and 3rd in CYA voting in 2019 and 2020, and he led the league in ERA+ with 179 in 2019 as well, and he had an ERA+ of 198 the year before that. In contrast, Warren Spahn's top 3 ERA+ seasons were 188, 170 and wait for it... 130! Yes, that's right, the year Warren Spahn won the CYA his ERA+ was 130. That's a staggering statistic. 130 is NOT great. In fact, I wouldn't be surprised to learn that no other pitcher since has won the CYA with a lower ERA+ than that. And ERA+ is better than ERA (though still not as good as xFIP or SIERA). ERA+ adjusts for ballparks and peers. It's less useful when comparing across different eras, as you'd need to control for other variables too, but it's still useful when examining performance within a single season. You can interpret an ERA+ of 130 as meaning he was 30% better than an average pitcher that season. However, it fails to account for luck. But you can get a pretty good sense of that just by looking at a pitcher's BABIP during that season as well. It should come as no surprise then, that the two seasons where Spahn had his best ERA+ values of 188 and 170 were also his two luckiest seasons where batters only hit 0.243 against him on balls in play (pretty damn lucky). In contrast, Ryu wasn't so lucky when he had 198 and 179 ERA+ values, as his BABIPs were 0.282 and 0.303 those seasons. This means that Ryu's two best seasons were not just a little bit better. They were better despite Spahn benefitting from being extremely lucky those two seasons and Ryu not. Add in that level of luck to Ryu, and his ERA+ jumps significantly. Or conversely, take away the luck that Spahn benefitted from those two seasons and his ERA+ values drop signficantly. And remember, these values are relative to the overall talent level of the league that season.

So in Spahn's BEST season, he was 88% better than the average 1953 MLB pitcher AFTER benefitting from a significant amount of good luck. In Ryu's best full season, he was 79% better than the average 2019 MLB pitcher WITHOUT benefitting from good luck. Once you adjust for luck and for how much better the average 2019 pitcher was than the average 1953 pitcher, then it's really not even close at all if you're asking who had the better peak or who had the best "stuff". Obviously, I fully realize that Ryu's overall career is hardly a shred of Spahn's overall career, and that there is tremendous value in being an above average pitcher for a very long time. But if you could teleport Ryu back to the 1940s and 50s, he's would absolutely terrorize the league. We'd probably all be talking about him being the GOAT right now. The same is true of any other top 10 pitcher in the league today. They would just absolutely rape hitters from the 40s and 50s.

As far as your claim about me being "inconsistent", again, that's nonsense. You're the one who keeps claiming I only discount Grove's era and Spahn's era but not Koufax's. That's nonsense. You made that assumption and keep perpetuating it. I said no such thing. Koufax's numbers would absolutely suffer from any statistical model I would build. He pitched in a pitcher's park (so did Spahn), he pitched from a high mound, he pitched from an expanded strike zone in his best 4 years, he also had a lucky BABIP (though the entire league had a low BABIP at that time). His numbers would absolutely suffer from controlling for these variables. The reason I haven't focused on that fact is because it simply doesn't matter. I don't need to discount Spahn's era in order for Koufax to have a better peak 4, 5, or 6 years. Koufax's numbers themselves are simply miles better than Spahn's, WIHTOUT demoting Spahn for having pitched in a weaker era. But even if I did make the necessary adjustment to be able to compare apples to apples, Koufax's numbers would go down, Spahn's numbers would go down even more, and Grove's numbers would go down even more than Spahn's. The talent pool of the league gets worse the further back in time you go, not better.

Here's a glimpse of a few stats from Spahn's best 5 year peak and Koufax's best 5 year peak that are actually predictive, unlike Wins and ERA.

Spahn - 136 ERA+ average
Koufax - 168 ERA+ average

Spahn - 3.21 FIP average
Koufax - 2.02 FIP average

Spahn - 1.18 WHIP
Koufax - 0.94 WHIP

Spahn - 2.8 BB/9
Koufax - 2.1 BB/9

Spahn - 5.2 K/9
Koufax - 9.5 K/9

Spahn - 1.9 K/BB
Koufax - 4.6 K/BB

These differences are remarkable. There is no amount of adjusting (sizes of strike zone, talent level of their contemporaries, mound heights, ballparks, BABIP, etc) that you could possibly implement that would put these 5-year numbers on an even remotely similar playing field. Perhaps you should read those deltas again if you're not getting this. The differences between 5-year-peak Koufax and 5-year-peak Spahn are difficult to exaggerate. I could probably find 100 pitchers between them value-wise. That's how far apart these guys were. The only possible argument anyone could ever make for Spahn is by looking at cumulative career value. He was an above-average pitcher for a very long time. Value adds up, and WAR gives him extra credit because his peers sucked. But he was never even the best pitcher in a single season. Not even when he won the CYA, and not even in his best two seasons.

[BobC]

Originally Posted by Mark17

All of this is just listing many variables involved, and I'm sure many more can be added. The obvious difficulties that remain are:

1. How do these variables play together? Are they additive, multiplicative, subtractive, and to what degree. How do you combine and weigh them?

2. How do you value them, with respect to specific players?

For example, let's say you are comparing 2 pitchers who both have a right fielder with a .985 fielding average. But one has a weak throwing arm and the other is Clemente. How much does having Clemente help, with his reputation discouraging runners taking an extra base?

First you'd need to give a weight to the variable - what impact does the right fielder's reputation play? Second, you have to value Clemente.

Suppose there are two catchers with equal fielding percentages, and throw out equal percentages of baserunners. But one is a very astute signal caller and the other is a dolt. Take Grove having Cochrane for example. First, how much can a smart, observant catcher help a pitcher? Second, what value do you assign to Cochrane (or Roseboro?)

All you have done is thrown out a bunch of factors to consider. The real trick would be to come up with an algorithm that can effectively combine and weigh the variables, and then, there's the (sometimes subjective - like the brains of a catcher) value you assign to each specific player involved.

In short, the above is not anywhere close to an actual predictive model.

Mark,

I think you bring up some great points, along the same lines I was alluding to, that there are going to be so many variables to factor into answering a question like this that it is virtually (and likely literally) impossible to effectively factor them all into any statistical equation or formula. You can attempt to do it, but at the of end of the day you'll only end up with what a statistician thinks is the right answer. And who elected them to decide that their opinions and points of view speak for all of us, or automatically overide what everyone else may think. I understand they can create these great statistical equations and algorithims to come up with a predictive formula to help decide who MAY be the best at something, but how can one be so certain of the outcome of such an equation or formula until they've actually created it and been able to show and prove it works. I thought in science that is what is known as a theory, which is unproven, and remains as such till someone can actually prove it is true and works. I don't seem to remember any true scientists ignoring questions about their work in regards to such theories, and simply telling people to trust and believe them because they have neither the time nor the inclination to fully explain their position. Nor to claim they know the answer to a question based on such a formula, when that formula has yet to be created, tested, and proven.

And that goes for key assumptions that are part of such theories and thinking, like the making of a blanket statement that ballplayers from 60-70-80+ years ago are much weaker players than they are today. How, why, what empirical data is there to factually prove that? You can pull up all the numbers and speculate and manipulate them all you want. And I understand about the increases in the population and how that factors in and, and yadda-yadda-yadda. But has the human male really evolved and changed that much physically in that last 100 or so years, or is it more so from advances in science, training, nutrition, medicine, education, even economics playing a huge part, and on and on. Heck, I've even heard somewhere that overall male testerone levels have been dropping generation by generation over the last century or so, which would initially make you think that earlier male generations may have actually been considered more masculine (and by extension athletic) than they are today. So maybe those differences in how players played back then are more due to all the other cultural and outside influences that were affecting them than most people (especially statisticians) would think. And how, unless you took players (not pitchers) from today and had them grow up to play 60-70-80+ years ago, and then likewise had the players (again not pitchers) from back then grow up to be playing today, could you really even begin to tell which era's players were stronger or weaker. Now according to blanket statements and assumptions by some statistically minded people, by switching the players like this we would expect to have the transplanted players to back then hitting tons of home runs, while probably striking out more, but overall crushing the pitchers from back then. In fact, the way these statisticians may talk and seem to think, you'd expect that all of Ruth's home run records would have been easily eclipsed way back 60-70-80+ years ago, and as a result he might not be carried anywhere close to the esteem he is today. And as for the transplanted players from back then now playing today, following some statisticians thinking you'd expect them to be completely overwhelmed and effectively having their collective asses handed to them on a daily basis by today's pitcher's, and not even have the league as a whole batting even close to .200.

But somehow I don't think all that would happen. Because humans are affected by and react, change and evolve to fit the situations and circumstances that surround and are constantly changing around them. No one can say with any meaningful certainty how a Grove or Spahn would pitch today. No statistician can honestly measure a person's drive, ambition, competitiveness, and any other intangibles that truly make them the player/athlete they are. And in demeaning and putting down an entire era or generation's ballplayers, without at least trying to factor in all the potential contextual differences between players from different times/eras, is simply insulting to those players. Especially since there is no truly effective way to account for, measure, and quantify all of the infinite number of cultural, contextual, and human differences (in addition to the differences in the game of baseball itself) that would need to be included in such a comparative and predictive formula. But a statistician can get away with saying they can in fact create such a formula or equation to accurately say who or what era/generation was better than another, even though they can't actually or empiracally prove they're right, because they know you or I, for the exact same reasons, can't definitively prove them wrong either.

To illustrate how times and context can be be ignored in statical analysis, the greatest ever left handed pitcher could have been someone born in the 20's who ended up dying in WWII and never even got to play in the majors. Or, they were born in the 20's, but got hurt coming out of high school when there was no Tommy John surgery back then yet, so they never got to play in the majors either. Or what about the time Randy Johnson spent on the injured list, what if he was pitching 100 years ago and got injured, but the medical knowledge back then couldn't completely cure him and he never pitched again, or at least never pitched anyhere near as well as he could have? Or here's a good one, Johnson's in college in the early '50's, and we know from his actual career it would would take him a few years to get his pitching act together. Back in the early '50's, ballplayers didn't get the kind of money they got later on when Johnson actually played. Since he's what '6"10 - '6"11, who is to say the school's basketball coach approaches him about playing BBall, so he does and ends up good enough to make the NBA because of his natural height, and never even goes to pitch in the majors. So how does a statistician ever account for and measure any of these instances in their formulas and equations? They don't, because it doesn't fit into their formulas and equations, but these examples do illustrate how in trying to look at a particular player and how well they may perform in a different time or era, the context of playing in that other time/era could result in a dramatic change to how their career would look or end up.

One last example, though a different sport. Tom Brady graduates from college and ended up being drafted in the 6th round, with what was it, 32 teams in the league then. So what if Brady had actually graduated 40 years earlier, and with a lot fewer teams in the NFL, he never gets drafted and becomes the GOAT. Different time, different context, totally different career outcome.

Statisticians create statistical formulas and equations to predict current game outcomes for gambling purposes. And after doing so, they see what the actual outcome of their game is, and can then tweak and improve their formulas as needed. The main thing is, they can actually test and prove it by looking at how well they did gambling. So they think they have these formulas and equations down and can use them to now try and determine something else like who was a better player, looking at multiple players playing in different times and eras. The problem is, you don't have any actual game or competition that will occur to tell you who won, like you do when you bet on a ball game and their is an actual winner. So there is no way to actually test that type of statistical formula or equation in picking who's the greatest at something all time, and thus be able to prove if that statistical formula or equation is in fact right or wrong. Statisticians will tell you that their statistics are all that can be accurately used to make such decisions, but since they can't ever be proven right or wrong for this type of question, statistics in this regard are nothing more than talking points, no more and no less. Something to maybe talk about, but certainly not the final answer!

[Snowman]

Originally Posted by BobC

Mark,
I think you bring up some great points, along the same lines I was alluding to, that there are going to be so many variables to factor into answering a question like this that it is virtually (and likely literally) impossible to effectively factor them all into any statistical equation or formula. You can attempt to do it, but at the of end of the day you'll only end up with what a statistician thinks is the right answer.

You say that, yet this is precisely what the entire mathematical discipline of Statistics was developed for. It is absolutely possible to measure the impact that something like pitching mound heights or strike zone dimensions has on performance with remarkable precision. This is not "pin the tail on the donkey". It is pure mathematics. If something has an effect, it can be measured, given a sufficient amount of data. The more data you have, the more accurately it can be estimated. It's all about sample sizes. And in baseball, we have a TON of data.

[cjedmonton]

Originally Posted by BobC

CJ

Great points and interesting thought by slightly changing the question like that. Problem I can see in answering it though is that it gives an unfair bias/advantage to modern pitchers, like a Koufax, who we may have grown up with, or maybe our Father did and told us how great he was. We can read and learn about earlier players, but I fear for the vast majority of people, they're much more likely to throw their reverence towards a player they'd actually seen and grew up watching. Just basic human nature. And you can't really base a question like on just people here on this forum. Let's face it, we're mostly a bunch of pre-war baseball card collecting nerds, and an extreme outlier when talking about the public in general. LOL

You’re spot on with this take, Bob. By and large, the players we admired and revered the most are those we have a direct (firsthand) or semi-direct connection with (through a parent’s or grandparent’s direct connection). Recency bias in full effect.

But there are only a handful of players whose reverence endures across generations…even if the vast majority of us never saw them play (or if we did, only a small percentage have a vivid and meaningful recollection). Seeing Roberto
patrol RF at Forbes Field in ‘66 as a 5 year old does not really count, as cool as that may be.

IMO, the list is a short one:

Babe
Lou
Jackie
Roberto
Willie
Mickey
Hank
Sandy

Not a slight to any of the other bonafide legends, but these 8 have a staying power in our consciousness and imagination like no others.

Then again, sentimentality has no place in this thread…even if we are all just fan(atics) at heart!

[Aquarian Sports Cards]

Originally Posted by Snowman

The notion that modern athletes are far superior to those of a century ago isn't exactly a controversial statement in the real world. This might be the only community on earth who wishes to pretend otherwise.

I actually don't think most here question that. They question the idea that they are somehow evolved in 3 or four generations. Their superiority is of methods and science not innate. Therefore if you could magically transport a Grove to 2021 and allow him to grow up in this era he would, in all likelihood, still be a superior player because he also would benefit from these advances.

In short, players today are of COURSE superior, but they aren't genetically any different than their forerunners, so the best way to compare across eras is to compare a player to his peers and then compare the comparisons.

Where THAT falls short is, as everyone has access to today's advances it flattens the curve of greatness and reduces outliers like Ruth or possibly Grove, because today's "lesser players" have made themselves greater through modern methods, whereas the players with greater natural advantages can only improve so much.

[Aquarian Sports Cards]

[QUOTE=Snowman;2165342] Yes, that's right, the year Warren Spahn won the CYA his ERA+ was 130. That's a staggering statistic. 130 is NOT great. In fact, I wouldn't be surprised to learn that no other pitcher since has won the CYA with a lower ERA+ than that.

Um, not even close:

Pete Vuckovich 1982 (the worst Cy Young winner ever) 114
Steve Stone 1980 - 123
Bob Welch 1990 - 125
Mike McCormick 1967 - 118
Early Wynn 1959 - 120

and I'm going to stop because there's too many to list them all. 130 is actually lower tier of the middle of the pack.

"Record" appears to be Jim Lonborg 1967 at 112

[Snowman]

[QUOTE=Aquarian Sports Cards;2165354]

Originally Posted by Snowman

Yes, that's right, the year Warren Spahn won the CYA his ERA+ was 130. That's a staggering statistic. 130 is NOT great. In fact, I wouldn't be surprised to learn that no other pitcher since has won the CYA with a lower ERA+ than that.

Um, not even close:

Pete Vuckovich 1982 (the worst Cy Young winner ever) 114
Steve Stone 1980 - 123
Bob Welch 1990 - 125
Mike McCormick 1967 - 118
Early Wynn 1959 - 120

and I'm going to stop because there's too many to list them all. 130 is actually lower tier of the middle of the pack.

"Record" appears to be Jim Lonborg 1967 at 112

Ouch! That's disturbing. Smells like some serious politics involved.

[Carter08]

[QUOTE=Aquarian Sports Cards;2165354]

Originally Posted by Snowman

Yes, that's right, the year Warren Spahn won the CYA his ERA+ was 130. That's a staggering statistic. 130 is NOT great. In fact, I wouldn't be surprised to learn that no other pitcher since has won the CYA with a lower ERA+ than that.

Um, not even close:

Pete Vuckovich 1982 (the worst Cy Young winner ever) 114
Steve Stone 1980 - 123
Bob Welch 1990 - 125
Mike McCormick 1967 - 118
Early Wynn 1959 - 120

and I'm going to stop because there's too many to list them all. 130 is actually lower tier of the middle of the pack.

"Record" appears to be Jim Lonborg 1967 at 112

Yup. Plus Sandy led the league in the category exactly twice. Spahn led the league in it, yup, twice. Not equating the two. Just defending Spahnie from a certain Spahn hater. Again, they named the darn award after the guy.

[cardsagain74]

Originally Posted by Snowman

Ouch! That's disturbing. Smells like some serious politics involved.

Not politics there. Just the typical reverence for wins that the era had.

Palmer and Sutcliffe had the best seasons in the AL that year, but at 15-5 and 14-8, it was heresy to give them the Cy Young. Vuckovich 18-6 with that low ERA+ and a WHIP of 1.502. Now that is something that's probably a record for the worst WHIP of any CYA winner.

And it wasn't even close. 14 first place votes for Vuck. No one else had more than five.

But as far as politics (or would it be better described as simply popularity and reputation)....look at Steve Carlton winning the NL CYA over Steve Rogers that year ('82). Though that also included the obsession with wins. Because even though Rogers went 19-8 and had vastly superior numbers, a 23 win Steve Carlton season was all that mattered.

Oh and 20 out of 24 first place votes for that one

[Aquarian Sports Cards]

[QUOTE=Snowman;2165360]

Originally Posted by Aquarian Sports Cards

Ouch! That's disturbing. Smells like some serious politics involved.

A lot of them were based on wins. Notice a dearth of post 2000 players on that list.

Nolan Ryan should've won in 1987 leading the league in ERA, ERA+, FIP, K/9, H/9 and K/BB but there was no way in hell an 8 - 16 pitcher was going to win an award back then. It's amazing that he finished 5th actually.

[BobC]

Originally Posted by cjedmonton

You’re spot on with this take, Bob. By and large, the players we admired and revered the most are those we have a direct (firsthand) or semi-direct connection with (through a parent’s or grandparent’s direct connection). Recency bias in full effect.

But there are only a handful of players whose reverence endures across generations…even if the vast majority of us never saw them play (or if we did, only a small percentage have a vivid and meaningful recollection). Seeing Roberto
patrol RF at Forbes Field in ‘66 as a 5 year old does not really count, as cool as that may be.

IMO, the list is a short one:

Babe
Lou
Jackie
Roberto
Willie
Mickey
Hank
Sandy

Not a slight to any of the other bonafide legends, but these 8 have a staying power in our consciousness and imagination like no others.

Then again, sentimentality has no place in this thread…even if we are all just fan(atics) at heart!

Makes perfect sense, and that is a great list. But the majority of people on your list are still recent enough that we, or a family member, would possibly still be affected by that familiarity bias. Ruth and Gehrig (and possibly Robinson) are back enough that we wouldn't likely have that familiarity bias. But those earlier players have movies and shows about them to keep them in the public eye long after they were done playing. So that helps as well.

[John1941]

Originally Posted by Snowman

No. Even ERA is highly subject to variance (read "luck"), which league they pitched in, and whether or not they pitched in a pitchers park.

Just go pick your favorite pitching seasons by your 10 random favorite pitchers. Then scroll down to the advanced stats section and look at the corresponding BABIPs for those seasons. I guarantee you those BABIPs will all be super low. In other words, those were the seasons they got the luckiest, not necessarily the seasons where they had the best stuff.

That is true, but it's more to helpful to look at this individual case. Using ERA+ eliminates the bias of park effects. Here's Johnson and Grove (100 is average):

Career #Led League
Randy Johnson 135 6
Lefty Grove 148 9

Because FIP (Fielding Independent Pitching) only looks at strikeouts, walks, and home runs allowed, it eliminates the bias of BABIP.

Career #Led League
Randy Johnson 3.19 6
Lefty Grove 3.20 8


These two put Grove ahead.

[BobC]

Originally Posted by Aquarian Sports Cards

I actually don't think most here question that. They question the idea that they are somehow evolved in 3 or four generations. Their superiority is of methods and science not innate. Therefore if you could magically transport a Grove to 2021 and allow him to grow up in this era he would, in all likelihood, still be a superior player because he also would benefit from these advances.

In short, players today are of COURSE superior, but they aren't genetically any different than their forerunners, so the best way to compare across eras is to compare a player to his peers and then compare the comparisons.

Where THAT falls short is, as everyone has access to today's advances it flattens the curve of greatness and reduces outliers like Ruth or possibly Grove, because today's "lesser players" have made themselves greater through modern methods, whereas the players with greater natural advantages can only improve so much.

Good post Scott. I've been saying the same thing all along trying to get people to understand that in looking at and comparing players from different times and eras, you can't just look at baseball numbers and statistics alone, and completely ignore the context of all non-direct baseball factors. As you said, there are superior methods and science, among other things, that really explain the differences in today's players to those of the past. But statisticians still try to explain everything with just the baseball numbers and stats they have. They completely ignore the human element and all the intangibles athletes bring to the table. Statisticians ignore those kinds of things because they can't measure a player's heart or their competitiveness, and they just tell you those are meaningless things anyway because their baseball numbers and stats override all. And don't ask them to prove anything as they'll just keep telling you they don't have time, and you wouldn't understand them anyway. Statistics are fine and have a very good place in predicting behaviors and outcomes, but there is no definitive outcome to a question like who's the best lefty of all time. And because there is no outcome to prove that some statistician's formula is right or wrong, they simply assert their formula is the answer. And in doing so, ignore the context of players in different times and eras, the human element, and in my opinion, commen sense. The statisticians can't prove they're right, but we can't prove they're definitively wrong. So they get away with it.

[tschock]

Originally Posted by BobC

Good post Scott. I've been saying the same thing all along trying to get people to understand that in looking at and comparing players from different times and eras, you can't just look at baseball numbers and statistics alone, and completely ignore the context of all non-direct baseball factors. As you said, there are superior methods and science, among other things, that really explain the differences in today's players to those of the past. But statisticians still try to explain everything with just the baseball numbers and stats they have. They completely ignore the human element and all the intangibles athletes bring to the table. Statisticians ignore those kinds of things because they can't measure a player's heart or their competitiveness, and they just tell you those are meaningless things anyway because their baseball numbers and stats override all. And don't ask them to prove anything as they'll just keep telling you they don't have time, and you wouldn't understand them anyway. Statistics are fine and have a very good place in predicting behaviors and outcomes, but there is no definitive outcome to a question like who's the best lefty of all time. And because there is no outcome to prove that some statistician's formula is right or wrong, they simply assert their formula is the answer. And in doing so, ignore the context of players in different times and eras, the human element, and in my opinion, commen sense. The statisticians can't prove they're right, but we can't prove they're definitively wrong. So they get away with it.

To put it another way: If a statistician's model is good at analyzing the past, then it should be reasonably good for predicting the future. Otherwise your model needs adjusting to consider other factors. That didn't seem to play out very well when 'the best team in baseball' this year didn't even get close to winning the World Series (as one example).

[Peter_Spaeth]

It's funny, if you were to have a discussion of (for example) who was the best midfielder ever in soccer, statistics probably wouldn't enter into the discussion at all. Baseball is unbelievably rich in statistics and even more so with all the advanced metrics, but they don't seem to settle anything.

[BobC]

Originally Posted by tschock

To put it another way: If a statistician's model is good at analyzing the past, then it should be reasonably good for predicting the future. Otherwise your model needs adjusting to consider other factors. That didn't seem to play out very well when 'the best team in baseball' this year didn't even get close to winning the World Series (as one example).

Dead on!

If you go back and read an earlier post in this thread it was stated that sabermetrics and statistical analysis was basically developed for gambling purposes. Well that is only for predicting games between two teams today. And over time, statisticians could tweak and refine those as they'd actually get to see how well it predicted the winner of a game. But there is no outcome or winner when you try to use statistics to decide the best lefty of all time. The formulas being used don't predict anything, and there is no winner decided that allows you to prove your formula was right, or to tweak your statistical formula if it was proven wrong. Statisticians just use the numbers they pull directly from baseball, ignoring outside and human influences, and interpret those stats in how they feel they would. The stats and formulas are nothing but talking points, as they can't prove or disprove anything regarding who really was the best. You can interpret the numbers how you want.

And they are certainly not infallible for gambling purposes either, as they don't always pick the winner.

[BobC]

Originally Posted by Peter_Spaeth

It's funny, if you were to have a discussion of (for example) who was the best midfielder ever in soccer, statistics probably wouldn't enter into the discussion at all. Baseball is unbelievably rich in statistics and even more so with all the advanced metrics, but they don't seem to settle anything.

You're right, there are too many variables in play, especially when comparing people or games from different times/eras. And you can't prove who really is right or wrong. It is really no more than an educated guess.

[Snowman]

Originally Posted by tschock

To put it another way: If a statistician's model is good at analyzing the past, then it should be reasonably good for predicting the future. Otherwise your model needs adjusting to consider other factors. That didn't seem to play out very well when 'the best team in baseball' this year didn't even get close to winning the World Series (as one example).

At the end of the regular season, every statistical model worth its salt would have said that the Dodgers were the best team in baseball this season. They also would have given the Dodgers a mere 25% chance of winning the world series despite being the best team because there is a tremendous amount of short term luck involved in baseball. This doesn't happen in football, basketball, hockey, or soccer. The best teams in those sports win the championship far more often.

[Snowman]

Let y = 2x + 3

If x = 5, then y = 13

BobC - "Well that's just like, your opinion, man."

[Mark17]

Originally Posted by Peter_Spaeth

It's funny, if you were to have a discussion of (for example) who was the best midfielder ever in soccer, statistics probably wouldn't enter into the discussion at all. Baseball is unbelievably rich in statistics and even more so with all the advanced metrics, but they don't seem to settle anything.

Players in various sports serve their team best by finding the role that is most helpful for his/her team. If a guy like Grove has a 6-0 lead after 4 innings, he serves his team best by not trying for perfection, but by laying the ball over the plate and making the opposition hit it. If they get a couple base runners, then he has to bear down to prevent too much damage, but otherwise, for expediency, he'd rather throw 90 pitches and win 6-3 than throw 120 pitches, striking out 10, and winning 6-0. In the age of the 4 man rotation and no relief specialists, complete games helped the rest of the staff get through the long season, especially when rain-outs made double-headers pile up towards the end. And if a pitcher can save a little wear on his arm, that's common sense. I don't remember who it was, but some pitcher said he very rarely threw over to first to hold a runner on, because he figured he only had so many throws in his arm.

Your soccer midfielder is a great example of a player's value being non-statistical. The best way to help your team win might have nothing to do with stats.

When I was in grade school, we played a game called Battle Ball. It was like Dodge Ball except you could catch the ball. If you dropped it, or if the opposition caught your throw on the fly, you were out and had to go to the sidelines where you could still throw at the other team whenever you got the ball.

We played it during gym class, at recess, and after school. Not to mention weekends. We had about 100 kids in each grade, divided into 4 classrooms. So the first day of each school year, we'd eagerly look at all the class lists to see what room/teacher we had, and also to see what room would have the best Battle Ball team. Well, in 6th grade, I was in room 303 and we had an all star team. The first time we played another class during our 30 minute gym time, we won 4 games - wiping out their class, starting a new game, doing it again, and again, and again.

So, one of our best and smartest players, Richard Lord, started getting out on purpose at the beginning of each game, so he could move to the out sideline and set up a crossfire attack. If we'd kept stats, Lord would look like the worst player in the whole grade, getting out in the first 10 seconds of every game. But with our team loaded, there was no chance we would lose - so eliminating the opponent as quickly as possible was the goal and he figured that out and played his role superbly.

[Peter_Spaeth]

On the soccer question, if you had the discussion among the world's most knowledgeable fans, players, coaches, writers, etc., you might not get to a complete consensus, but the same few names would be in the discussion -- all without the benefit of statistics. The "witness of the eyes" as I think John Updike called it.

[tschock]

Originally Posted by Snowman

At the end of the regular season, every statistical model worth its salt would have said that the Dodgers were the best team in baseball this season. They also would have given the Dodgers a mere 25% chance of winning the world series despite being the best team because there is a tremendous amount of short term luck involved in baseball. This doesn't happen in football, basketball, hockey, or soccer. The best teams in those sports win the championship far more often.

Then I would counter that your statistical model needs tweaking because it's not accounting for all the variables. The Dodgers weren't "The Best Team in Baseball" as they didn't win the championship. Though they may have had the best group of individuals in baseball playing for the same team. There's a difference.

[Snowman]

Originally Posted by Peter_Spaeth

It's funny, if you were to have a discussion of (for example) who was the best midfielder ever in soccer, statistics probably wouldn't enter into the discussion at all. Baseball is unbelievably rich in statistics and even more so with all the advanced metrics, but they don't seem to settle anything.

Statistics may not enter the discussion, but it probably should. Interestingly, I also build predictive models for soccer that estimate the value of every midfielder, both offensively and defensively. I've used it to bet on each of the past 3 world cups, and it's been by far my best ROI of all the sports I bet on.

[BobC]

Originally Posted by Peter_Spaeth

On the soccer question, if you had the discussion among the world's most knowledgeable fans, players, coaches, writers, etc., you might not get to a complete consensus, but the same few names would be in the discussion -- all without the benefit of statistics. The "witness of the eyes" as I think John Updike called it.

+1