moonslav59

Cora and Tito stand high above all other Sox managers in the past 5 decades. A better discussion might be who is third. I say Dick Williams, but I may be alone on that one.

Huh?

I used CERA and OPS against in dozens of sample sizes chosen only by having large enough samples from multiple catchers. I did it for Posada and VTek, too, over many many years. Several sample sizes had 150 to over 200 IP by both catchers. I also did sample sizes of RPers with much smaller sample sizes, and while those results and conclusions were more mixed, even those favored guys like VTek and Leon and disfavored Posada and Vaz and Salty and Swihart. Kinda the guys you’d expect, except for some people on Vaz..

I guess it’s just coincidence the random samples mirror reality almost exactly. What I wanna know is what happens if a clutch hitter suddenly faces 25 clutch pitchers in a row and has crappy numbers. Is he no longer clutch? Talk among yourselves.

Of course it could be. I wouldn’t sat lineup slot comfort is not real. I just think it’s way overblown.

Not only did that cheap hit drop right between Kike & Hunter, it would have been a double play if caught. Judge was running full out on the crack of the bat. Time to turn the luck around.

Cora can’t win with some fans no matter what he chooses. It’s not just Cora, either.

They jettisoned Price, Buch and Wright, too. Someday Vaz will go, too. Looking at Leon’s offense, one could ask how and why he lasted so long, and why Sale wanted him as his binky.

The variances are too great to be chalked up to other factors. The fact that just about every pitcher with significant innings and even those with unbalanced and smaller sample sizes did better and way better without Vaz has meaning. One could say lefty righty splits have too many other factors involved to have any significant value, but they are still discussed. Why do some pitchers almost always pitch to just one catcher. Even if the answer is just comfort and not some skill every one not named Vaz has, its still real and meaningful. When pitchers are asked about throwing to certain catchers, of course they go out of their way to not throw ex teammates under a bus, but they all lavish great praise on catchers they had the most success with. It matters to them.

The data entered is not random. If you entered the actual data of every PA in the playoffs or every final game line every player ever generated over MLB history and had a computer program randomly create the amount of sample sizes that actually occurred in real life, the results the computer would come up with would be almost identical to what actually happened. It just would not give names like Kershaw and Schilling to those sample sizes that were on the extreme ends of the total amount of samples. Also, if you took every game line Kershaw has ever produced over his career and then randomly selected samples from here and there until you reached 189 innings (his actual playoff IP) you’d end up getting a wide variety of samples with the vast majority close to his norm, but surely you’d get some near 4.19- his actual p,ayoff ERA and some where he did much better than his career norm in the regular season. If the playoffs were totally random, we’d expect some samples to look out of whack from those player’s norms. Most would be near the norm, but some not. I don’t get what’s so hard to understand about this point. I’m fine if people don’t agree, but to even be able to see how the randomness point can relate to this debate is beyond me. The fact that people have actually done what I’m saying and the randomly generated sample sizes created came out to mirror the actual outcomes in reality- same number of samples really better than the norm and worse than the norms and by the exact same margins has to at least hint at the idea that maybe it could just be all random within the parameters entered into the sample generator. Of course, a guy like Papi’s numbers entered would create more great samples than Spike Owens. The data is not like flipping a coin on every player.

They could be and likely are.

Just because you can’t make sense of the concept of randomness does not mean it makes nosense or is not related to the issue being discussed. It boggles my mind that you can’t even conceive the idea that the randomness could be all this is. Why don’t players always have the exact numbers in any and every 189 inning sample size you pull? Is it impossible to think Keyshawn just happened to have slumps at exactly the wrong times 5 times out of all his playoff series. Can you please answer my questions like I answer yours?

Do you understand what happens when a computer takes all the data of a player like Kershaw and then spits out 1,000 sample sizes of 189 IP by randomly accumulating the data? Yes or no? If you answer yes, then good. Maybe you do get at least that part of my point. Now, next question: do you think the 1,000 sample sizes the computer spits out will all look identical to each other, or will some come out with an accumulated ERA of, let's say 4.19 or more and maybe some with maybe 1.19? Yes or no? If you answer no, you don't understand what random samples mean or how the populate a chart. Some will come out looking extreme, while most will look near his norm. My point is, if random samples can and do produce a sample that looks just like Kershaw's actual sample, how can you prove it's not just a random occurrence? You can't. Just like I can't prove the reason is the higher pressure. It seems weird that Kershaw does better with RISP and clutch moments during the season, but then turns into a pumpkin under the "extra" pressure of the playoffs.

Of course the pressure is higher, but why assume that is the only reason a player may do better or worse than their norm, when over every player's career, they often get hot and cold for seemingly no reason at all. BTW, I've played baseball- a lot.

Career CERA/OPS Against (IP) Sale 2.51/.622 AJ P (226) 2.79/.578 Leon (436) 4.61/.762 Vaz (84) ERod 4.05/.700 Leon (118) 4.23/723 Vaz (566) Porcello 4.19/.728 Leon (576) 4.93/.800 Swihart (122) 4.96/.794 Vaz (211) Price 2.96/.647 Leon(204) 4.27/.738 Vaz (360) Eovaldi 4.30/.765 Vaz(147) 4.85/.421 Salty (124) Buccholz 2.83/.642 VMart(241) 3.01/.646 Leon (155) 3.95/.737 Salty (207) 4.44/.705 Vaz (130) 5.12/.801 VTek (118) Wright 2.94/.611 Hanigan (95) 3.49/.700 Vaz(101)

Here's the "Cherry-picked" pitchers who just happen to be the ones who pitched the most IP with the Sox since Vaz came up: CERA/OPS Against (IP) Sale 2.51/.622 AJ P (226) 2.79/.578 Leon (436) 4.61/.762 Vaz (84) (No catcher on the CWS had a CERA worse than 3.53) ERod 3.78/.778 Hanigan (50) 4.05/.700 Leon (118) 4.23/.723 Vaz (566) 4.44/.692 Swihart (75) Porcello 4.19/.728 Leon (576) 4.93/.800 Swihart (122) 4.96/.794 Vaz (211) 5.38/.831 Holaday (55) (Nobody on Detroit with over 30 IP w Porcello had a worse CERA than 4.43) Price 2.96/.647 Leon (204) 4.27/.738 Vaz (360) (All other catchers with 30+ IP with Price had a CERA better than Vaz's. One guy, Gregg Zaun with only 43 IP had one close at 4.19. Everyone with more than 100 IP had a CERA or 3.61 or better.) Eovaldi 2.66/.419 Wong (20) 3.54/.657 Plawecki (69) 4.30/.765 Vaz (147) 4.53/.735 Leon (44) 4.85/.421 Salty (124) Buccholz 2.83/.642 VMart (241) 3.01/.646 Leon (155) 3.79/.629 Lava (36) 3.95/.737 Salty (207) 4.44/.705 Vaz (130) 4.68/.683 D Ross (73) 5.12/.801 VTek (118) 5.63/.836 AJ P (62) Others: Alex Avila 1.55/.587 in 52 IP Barnes 3.69/.624 Vaz (197) 3.83/.697 Leon (99) 4.50/.803 Swihart (42) Pomeranz 3.32/.721 Holaday (41) 3.92/.745 Vaz (198) 6.02/.934 Leon (46) Kelly (Y Molina 2.81/.721 in 176 IP) 3.23/.619 Vaz (98) 3.94/.580 D Ross (32) 4.48/.698 Swihart (74) 4.63/.785 Leon (56) 4.83/.761 Hanigan (91) Wright 2.94/.611 Hanigan (95) 3.49/.700 Vaz (101) 4.06/.716 Swihart (71) 5.83/.935 Leon (59) Some sample sizes are rather small with some catchers and some are highly unbalanced. Some are during different parts of a pitcher's career, but the numbers astound me every time I look them up. The totals: 10 top pitchers by IP Leading in CERA: 2 Leon 2 Han 2 Vaz (Barnes & Joe Kelly- not the biggest sample size pitchers) 1 by AJP, Holaday, VMart, Plawecki OPS Against: 4 Leon 1 Hanigan, Holaday Lava, Salty, Ross & Vaz Last place with 100+ IP by 2+ catchers: CERA 5 Vaz 1 VTEk (w Buch) 1 Leon (w Barnes) OPS 4 Vaz 1 Swihart (Porcello) 1 VTek (Buch) 1 Leon (Barnes) Out of the 9 pitchers who had 80+ IP with 2 or more catchers, Vaz finished last or second to last in 7 out of the 9 cases in CERA and 6 of 9 in OPS Against.

How do you prove it's the "environment" that caused the difference? Nobody knows why players slump and get hot during the season, but suddenly, when they do in the playoffs, we know for sure why. That really makes sense to you?

Obviously.

So, without Houck and Duran, our farm may fall in the rankings, this winter.

I didn't hand pick sample sizes. I took the largest sample sizes available. The sample sizes where 2 catchers caught the same pitcher a significant amount of time. I didn't discard any pitcher- catcher sample size that was large enough to evaluate. Even if you dive deeper into smaller and more unbalanced sample sizes, they nearly all show the same thing: each pitcher does better with almost anyone not names Vaz. I even took the career numbers of all the Sox pitchers with a lot of IP'd since Vaz came up and compared those. The numbers were frighteningly bad for Vaz. Go ahead and look at the overall season CERA, where one catcher catches some pitchers way more than others- some almost exclusively, and use those numbers- like they mean more. The fact is, pitcher by pitcher, the back up get better results.

Yup. Hard to hit that one, anyway.

Damn! Thought we had a big shot, there!

Did Shaw even have his eyes open on those swings?

What I'm saying is, there are plenty of reasons to be optimistic about this year's team. I should not be one of just a few that see that.

I'm not always an optimist. I knew we had zero chance, last year and was one of the first to jump ship on 2019. Don't give up on this year's team: it has shown grit and determination.