moonslav59

Good points. The lux tax induced drop was on DD, though. (Also, Beni, Kopech, Beeks & Espi were Ben draftees or IFA signees.) One can also argue the Bloom crop was hampered by COVID- the short 2020 draft and the lost year of player development.

I think Espinoza was ranked more highly than Kopech ever was.

Best Draft Picks Since 2014-2019 (6 years): Beni 2015 Houck 2017 Kopech 2014 Beeks 2014 Crawford 2017 Casas 2018 Dalbec 2016 Duran 2018 Walter 2019 IFA Moncada 2015 Bello 2017 Rafaela 2017 Mata 2016 Perales 2019 Wikelman 2018 Paulino 2018 Chacon 2019 Castillo 2015 Espinoza 2015 2020-2022: Mayer 2021 Yorke 2020 Romero 2022 Drohan 2020 Anthony 2022 Meidroth 2022 Jordan 2020 Hickey 2021 E R-C 2021 Kavadas 2021 Coffey 2022 IFA Bleis 2021 Alcantara 2022 Rule 5 Whitlock 2021 Trade Wong, Valdez, Abreu, Hamilton, Koss

Going against the lefty, old friend, Wade Miley... 1. L Verdugo RF 2. R Turner 1B 3. R Refsnyder LF 4. L Devers 3B 5. R Kike CF 6. L Yoshida DH 7. R Arroyo 2B 8. R Wong C 9. R Chang SS I'd have probably gone... 1. R Kike 2. L Verdugo (hot hitter 2nd) 3. R Turner 4. L Devers 5. R Ref The rest- the same.

You act like "two separate seasons" is 300+ games. Your unbiased observation is cherry-picked to find the two widest disparity pitchers, each with just a one game sample size with one catcher. I'm really quite surprised you are putting so much faith and energy into such a tiny sample size. Honestly, it really is not much different from me using this to counter you: OPS Against: Whitlock: .000 w McGuire .819 w Wong Houck .000 w McGuire .705 w Wong My choice of cherry-picked sample sizes involves just one less game with one pitcher (zero instead of one.) How about looking at the pitchers both have caught more than 13 PAs with each catcher? First, let me point out that using 13 or more PAs as the minimum sample size goes against every bone in my body as being anywhere near a significant sample size, but I will do so to show the disparity is not as great as you think it is. No cherry-picking. These are all the sample sizes where both pitchers have 13 or more PAs with each catcher. Wink .584 w Wong (45 PAs) .377 w McGuire (19) Pivetta .719 w Wong (45) .852 w McGuire (43) Crawford .891 w Wong (45) .310 w McGuire (29) Brasier .764 w Wong (25) .880 w McGuire (30) Schreiber .681 w Wong (23) .575 w McGuire (16) Bleier .686 w Wong (18) .866 w McGuire (16) Ort .752 w Wong (37) .871 w McGuire (13) Jansen .641 w Wong (13) .220 w McGuire (14) Martin .918 w Wong (18) .482 w McGuire (11) It's 6 to 5 in McGuire's favor before the lopsided ones are counted: And your two unbalanced samples... Sale .430 w Wong (25) 1.061 w McGuire (64) Kluber .544 w Wong (19) 1.045 w McGuire (64) Wong is better with 7. McGuire is better with 6. Wong has not caught Bello. McGuire has not caught Houck or Whitlock. (That's a huge part of the 3 run differential.) This is why looking at overall CERA numbers are misleading and near insignificant, and that's before talking sample size values.

Do they? Should they? Even if they do, two in eight years is worse than 3 in Bloom's 4 years.

They were there earlier, too. People just gravitate towards gloom & doom.

He mentioned Mayer. I added Whitlock and Bleis. I do think he has a point. 4 years and only 3 blue chippers is not great. (It's not bad, either.) How many blue chippers did we acquire after Devers, who we signed in 2013 and before Whitlock, Mayer and Bleis? That was about an 8 year void.

...and every single sample size is tiny and many are lopsided and even all vs none with some pitchers. Yes, there is some significance to the fact that a wide differential skewing towards one catch vs the other, even among sample sizes, but it's just not true. When you look pitcher by pitcher, the differential is not significant. When you compare each pitcher that have more than tiny sample sizes with each catcher, separately- one by one, Wong barely has an edge at all.

So all the talk about us not being able to beat good teams or good pitchers is on hold for a while. 3-0 v DET (DEt is 7-8 vs rest of league) 1-0 v MIL (14-5 v rest) 3-1 v LAA (9-7 v rest) 2-1 v MN (10-7 v rest) 2-1 v BAL (11-5 v rest) 0-3 v PIT (11-7 vs rest) 0-4 v TBR (13-3 vs rest of league)

I've looked at the average offense by catchers for many years. It certainly is a lower average than any other position and way lower than some. That being said, the line between starting catcher and back-up is often blurry for many teams. To get a sample size of 60 catcher seasons over the last 2 years (30 teams x 2 seasons= 60 top samples) you have to lower the PAs to 300- by far the lowest of any position. Here is what I found: The top 30 samples range from a .710 OPS to .939 (Grandal '21). The 2022 Vazquez ranked 29th out of 60. The 2021 Vaz ranked 41st at .659. Combine 2021 and 2022 and raise the min PAs to 577 and you get a sample size of 30 catchers (1 per team.) Vaz places 17th out of 30 at .685. He's been average- not really above average. It is telling to see the bottom quartile cut off is .643. Ten catchers were at .600 or lower. On the larger scale, there are only 63 catchers with 1000+ PAs since 2014. Vaz is ranked 37th at .695. #30 is .707. #15 is .745.

On Vaz's offense: OPS+ 64 '14-'16 (385 PAs) 71 '17-'18 (614 PAs) 105 '19-'20 (710) 87 '21-'22 (924- some with HOU) In fairness, an OPS+ of about 90 is probably good for a catcher. Vaz has been a good MLB hitter among catchers, and he had some big hits along the way, but an 86 OPS+ over his career is not really all that good.

Both of our catchers are works in progress. It's a 21 game sample size. No definitive judgments should be made on that.

Playing way less games vs our own division should increase the chances of the ALE last place team to break that record. All ALE teams cannot make the playoffs, so we will have to pass at least one ALE team to make the show. It won't be easy, since 4 of the top 5 AL teams are from the ALE. Not even harmony has anything to say about the near complete ALE dominancy. The 4th place teams are 12-8. That's on pace for 108-54 records! 4 teams on pace for 108+ win seasons! All this being said, I still like our chances. I'm sticking to my belief that our SP'ing is not nearly as bad as it has looked. The rotation has already started to look better, and there is room for more, as well as chances that guys like Paxton, Mata or Walter, and of course Crawford might infuse some pluses, when needed. Since April 4th, some ERAs are not great, or even good, but some are vast improvements on what they were over the first 14 days of the season: 1.26 Crawford 2.03 Winckowski (not a starter but is 5th in IP over the last 14 days) 3.94 Houck (3.40 last 14 days) 4.43 Pivetta (just one bad start, all year) 4.50 Whitlock (showing great signs he is back from his injury) 5.40 Sale (needs some back-to-back good outings, starting now.) (7.36 Kluber is "weak link" that may need replacing after a few more starts.)

Develop not draft. Steal from other teams not draft.

Bleis

Whitlock

I'm still hoping they move Yoshida to the lead-off slot. Maybe it gets him thinking "get on base" not "hit a double." Devers second. Dugo fourth. The rest seems to be interchangeable. Kike seems to be warming up, so maybe.... vs RHP L Yoshida LF L Devers 3B R Turner DH L Dugo RF R Kike 2B L Casas 1B L Duran CF L McGuire C R Chang SS

1. Dugo RF 2. Devers 3B 3. Turner DH 4. Yoshida LF 5. Kike 2B 6. Casas 1B 7. McGuire C 8. Duran CF 9. Chang SS

Yes. Winner keeps it going.

McGuire starting, tonight. (I don't see a game thread.)

No name calling.

The rotation has gotten a lot of attention, too, as has SS, 2B and CF. Maybe the position most underrepresented, in terms of it being a very high need area is maybe 1B. We have sucked at 1B for way too long.

LOL. Nobody needs my permission to think or talk about anything they want and for as long as they want. They can also feel free to tell me they think I'm focusing on one area too much, too, and I think they have a few times.

I do agree that a catcher has more to do with wins than 2B. I also think the fact that only Wong has caught Houck and Whitlock, any numbers will be skewed. Let's see how all these numbers pan out over a full season.