pete the dog

It was still ridiculous to leave Harden in the game. If you can't replace Harden at that point, then your team cannot win anything important.

Sheesh. How little faith does Lou have in the bullpen? It was ridiculous to leave Harden in the game, with a pinch hit opportunity and Harden having struggled for 2 innings. Just ridiculous.

Yes I've sent them comments. I guarantee I'm not the only one calling foul on these guys. I have a few problems with the paper: There is a voluminous body of research on racial bias, a less emotionally charged word than discrimination, which these authors use in the title. There is no overt claim in the paper that the effect they study is the result of willful conduct, so why did they put racial discrimination front and center? And yes, Table 3 is where statistical significance of their main argument is examined. But if you read the paper, time and time again they try to support their argument with utterly insignificant statistics, e.g. the 11 games I mentioned in my previous post. And re Table 3 my question is, where are the results for White umpires?! Why did they only cite t-stats for less than 10% of the cases, the games called by Black and Hispanic umpires? They admit to leaving out White umpires without justification or any attempt to explain why. It's not hard to guess: their tenuous claim to significance probably evaporated quickly when they added the 90% of the games called by white umpires. And they say this: No, your results are either significant or they're not. You are not allowed to say things like "suggestive patterns emerge" and other weasel words in an academically honest paper. Who said it was published? It would have been much more impressive had it been peer-reviewed and submitted for publication before calling up MSNBC (note the publication date and the date MSNBC reported the story), rather than throwing it out there with a "COMMENTS WELCOME" slapped at the top. Another ridiculous quote: "The results suggest that standard measures of salary discrimination that adjust for measured productivity may be flawed, and we derive the magnitude of the bias generally and apply it to several examples." Really?? The results purport to prove MLB umpires employ racial discrimination in their ball/strike calls. Isn't a stretch to extrapolate "wage discrimination" metrics from pro athletes making $500k/yr and up to standard cases? Well, I guess I should have actually read the paper before I posted. I didn't realize that this wasn't published, but was simply made available to the public and (more importantly) the media for inspection. In my opinion, alerting the media to un-peer-reviewed, unpublished data is a major no-no. Maybe the science is sound, maybe not. But this practice of science is pretty slimy. Talking about "suggestive patterns" is also pretty weak, and would certainly need to be presented with serious caveats in any respectable journal. Finally, as noted above, this paper may be about bias, but it most certainly is not about discrimination. These guys look like media whores. Nevertheless, the data do show a significant bias, and I do think it matters.

The funny part about that is that the article implies intetional discrim. on the part of the umpires. Accordingly, the theory goes that the home plate ump decides to discrim against blacks on 2-3 times out of 250 opportunities. Sure - that makes sense. I didn't see where they made it look intentional. It certainly doesn't need to be intentional to be real. As for the statistics, I assume if the paper was published that this is a statistically significant effect. It would be nice to have information about the effect size, but those of you claiming a 1% difference can't possibly be important are just plain wrong. Small effects can produce big disparities in results. A few marginal calls going one way or another in a game can make a huge difference. Why are people so defensive about this stuff (same author reported a similar effect in basketball)? Is it really that hard to believe? We know that there are subtle (unintentional) racial biases in law enforcement, judges' sentences, medical treatments, loan decisions, housing decisions, and on and on and on. Few of these effects have huge effect sizes, but how many people need to receive poorer treatment before it's important? When you're talking about large numbers of people, a small effect (e.g., 1% of cases) affects a whole lot of people (1% of 1 million instances is 10,000 people). How many marginal pitches do you think there are in a season?

Can you say "unnecessary distraction?" I think bringing Sammy back would be a terrible idea. Can you imagine the media circus? Not to mention the bad blood with players and management. The team is playing well, and there are plenty of other good options for an additional outfield bat. I hope Jim is working hard on it. Either that, or hope Murton starts to contribute.

I love Kerry Wood. How can anyone question his toughness and commitment? And, yeah, I see it questioned here all the time.

I hate the cubs.

journeyman, he made a few starts for the Cubs last year (and sucked) and pitched a little bullpen in september. Ever since spring training he's been lights out. I just don't get it. Those stats Fred posted clearly show how terrible he was last year, the only bright spot being his high K rate, which was completely overshadowed by his inability to prevent hits or walks. Oh, and I guess it's spelled "Walrond". Looking at his Baseball Cube stats I can see that he's really just been everywhere, never really finding success. The guy is 30 now! I keep thinking that "Walrond" is a cross between a Walnut and and Almond, but I can't figure out where the stupid R comes from. It's a cross between *walrus* and almond.

Again, examples are easy. Were I properly motivated, I guarantee you I could find plenty of examples where this level of ptiching (even "high stress" pitching) did not result in injury. Interesting as they may be, examples are not useful data for understanding cause and effect. What the hell are you talking about? I just showed you 7 pitchers whose career were shortented or their effectiveness was lessoned, or were out of baseball at an early age after a) high innings and b) high pitch counts. Sonofsamiam just provided you with five more. You don't need to do regression analysis or complicated statistics to look at those data and be able to draw an inference. The obvious answer is that pitching all those IP and pitches per inning contributed to whatever results that occured. However, that doesn't rule out other factors too. Yet, it also doesn't take a Rhodes scholar to come to the conclusion that it's probably not a good idea to have a young pitcher throw when they are fatigued. No, what the hell are you talking about? You obviously have no understanding of inferential statistics. But thanks for posting the PAP data. It's nice that someone out there understands the kinds of data that are required to back a claim. Sheesh. I understand inferential statitics quite well. However, you don't use them to show a cause and effect relationship becuase in fact they cannot show a cause and effect relationship. Individual injuries after high pc over a prolonged period can show a cause and effect relationship although other factors cannot be ruled out. Using huge data sets like the study I referenced only hammer home the obvious. No, you don't understand inferential statistics. You don't seem to understand the meaning of "variable" or "effect." The analysis of the "huge data set" does much more than "hammer home the obvious." If you're convinced by a few memorable examples, that's your problem. Shall I reference peer reviewed scientific studies I've published? It's not about "being convinced by a few memorable examples". If it (whatever it happens to be) occurs once that's all the data one needs. Then one begins to ask other questions, like has it happend to anyone else? If it has, then you find out how many more. But 1 is all you really need. It's called induction and is a much more powerful method at discovering truth than hypothesis testing using inferential statistics. But like Bob Sanders just posted. In essence I agree with Mephistopheles, poor mechanics probably has a lot to do with arm injuries, but then you have to ask what causes poor mechanics. If it's fatigue born by high pitch counts then I would think that one would want to mimimize those instances. Wow. Just wow. If I have more peer-reviewed papers than you does that make me right and you wrong? Let me ask you a simple question. Do you believe that a batting average based on 2 at-bats is as informative as one based on 550 at-bats?

Again, examples are easy. Were I properly motivated, I guarantee you I could find plenty of examples where this level of ptiching (even "high stress" pitching) did not result in injury. Interesting as they may be, examples are not useful data for understanding cause and effect. What the hell are you talking about? I just showed you 7 pitchers whose career were shortented or their effectiveness was lessoned, or were out of baseball at an early age after a) high innings and b) high pitch counts. Sonofsamiam just provided you with five more. You don't need to do regression analysis or complicated statistics to look at those data and be able to draw an inference. The obvious answer is that pitching all those IP and pitches per inning contributed to whatever results that occured. However, that doesn't rule out other factors too. Yet, it also doesn't take a Rhodes scholar to come to the conclusion that it's probably not a good idea to have a young pitcher throw when they are fatigued. No, what the hell are you talking about? You obviously have no understanding of inferential statistics. But thanks for posting the PAP data. It's nice that someone out there understands the kinds of data that are required to back a claim. Sheesh. I understand inferential statitics quite well. However, you don't use them to show a cause and effect relationship becuase in fact they cannot show a cause and effect relationship. Individual injuries after high pc over a prolonged period can show a cause and effect relationship although other factors cannot be ruled out. Using huge data sets like the study I referenced only hammer home the obvious. No, you don't understand inferential statistics. You don't seem to understand the meaning of "variable" or "effect." The analysis of the "huge data set" does much more than "hammer home the obvious." If you're convinced by a few memorable examples, that's your problem.

Again, examples are easy. Were I properly motivated, I guarantee you I could find plenty of examples where this level of ptiching (even "high stress" pitching) did not result in injury. Interesting as they may be, examples are not useful data for understanding cause and effect. What the hell are you talking about? I just showed you 7 pitchers whose career were shortented or their effectiveness was lessoned, or were out of baseball at an early age after a) high innings and b) high pitch counts. Sonofsamiam just provided you with five more. You don't need to do regression analysis or complicated statistics to look at those data and be able to draw an inference. The obvious answer is that pitching all those IP and pitches per inning contributed to whatever results that occured. However, that doesn't rule out other factors too. Yet, it also doesn't take a Rhodes scholar to come to the conclusion that it's probably not a good idea to have a young pitcher throw when they are fatigued. No, what the hell are you talking about? You obviously have no understanding of inferential statistics. But thanks for posting the PAP data. It's nice that someone out there understands the kinds of data that are required to back a claim. Sheesh.

Again, examples are easy. Were I properly motivated, I guarantee you I could find plenty of examples where this level of ptiching (even "high stress" pitching) did not result in injury. Interesting as they may be, examples are not useful data for understanding cause and effect.

http://www.baseball-reference.com/b/brogler01.shtml (Brogleio) 60s http://www.baseball-reference.com/k/koufasa01.shtml (Kaufax) 60s http://www.baseball-reference.com/f/fidryma01.shtml (Fidrych) 70s http://www.baseball-reference.com/h/hamptmi01.shtml (Hammpton)90s http://www.baseball-reference.com/m/millewa04.shtml (Miller) 90s http://www.baseball-reference.com/m/martira02.shtml (Martinez) 90s http://www.baseball-reference.com/b/boydoi01.shtml (Boyd) 90s That's all I could come up with in a spare five minutes Uh, thanks for the effort, but I want statistics, not examples. Anyone can come up with examples of pitchers who pitched a lot of innings and had arm trouble, and anyone can come up with examples of pitchers who pitched a lot of innings and had no problems. Summary statistics are needed.

The certainty with which people ascribe Prior's and Wood's problems to over-use is absurd. I'm no fan of Dusty's, and it's possible that over-use had something to do with their problems, but I'm very skeptical. The right way to do this would be to go back and look over the years at the relationship across all pitchers between innings pitched and different injuries in the following year(s). I'd be willing to bet a fair chunk of money that innings pitched has a very small statistical effect on the likelihood of career-threatening injuries in the subsequent 1-3 years. People just can't seem to get comfortable with the idea that sometimes stuff just happens. Most likely we just had the bad luck of having two of our top prospects be injury-prone for reasons of genetics, mechanics, whatever. It's fun to speculate about the role of over-use, and it's even more fun to blame Dusty. But the certainty and self-righteousness of the "over-use" believers is just hard to fathom. Anyone have any actual data on the health effects beyond this sample of 2?

Thank you for saying it! I've said it before and I'll say it again: I've never seen a forum so obsessed with reducing the number of new threads. If there's a new piece of information that could possibly be attached to a 4-year old thread that's 87 pages long, it'll be done. Rant over.

My guess is that they didn't see the race as that close. Even if Prior was brilliant tomorrow, they were more comfortable with starting Miller in the rotation at the beginning of the season. Because of this, they announced it now so the controversy wouldn't be as large if Prior does pitch great tomorrow. It just doesn't make sense considering what Lou said in yesterday's Tribune: Who is that in your sig? :shock:

I'm no huge fan of Piniella, but I don't understand the extreme animosity toward him on this board. I mean, at least his tantrums are entertaining. Can someone please summarize for me why Lou is the devil? Thanks!

Don't forget about the Bosox, who also will be major players for starting pitchers in the offseason. Zito & Schmidt are going to make a freaking fortune, given the teams that are desperate for starting pitching.

:lol: :lol: :lol: :lol: :lol: :lol: :lol: :lol: :lol: :lol:

I was at that game, too. Sigh. Seems like a decade ago... :cry:

Well, I feel damn bad for Kerry, and appreciate what he tried to do for his team. I believe he pitched through pain, maybe when he shouldn't have. I believe he stayed too long last year and came back too early this year. I think he gave his all to help a nowhere team, and may have lost his career as a result. The coaches/management who convinced/tolerated him pitching relief last year should probably be liable for his lost career earnings. Reckless and selfish. But then again, who knows exactly what Kerry was telling them. Kerry Wood has been a great Cub, and I will be very sorry to see him leave the team. I hope Andy and Jim try to bring him back next year (at a very reduced rate).

I can't believe another NSBB-er who lives in Davis. Great to know there's another fan in town. BTW, I agree that it's nice to have a good bullpen. It definitely helps my blood pressure in the late innings.

Nice post. Is there a way to calculate what the loss of Lee will do to Walker batting in front of him and to the productivity of the rest of the lineup?

Ohman blew it by not being aggressive enough. He had Lofton 0-2 and nibbled. Then Lofton fouls off a few pitches and gets the walk. Knowing Lofton's speed along with the fact that Drew is coming up next, there is no way you should walk Lofton. He absolutely has to earn his base there. Dusty did not blow that. Ohman blew it. Again.

I can't really understand all the anger and drama about who knew what and when did they know it. This just all deflects attention from the real issue: Our star young pitchers can't stay healthy. Are their techniques faulty? Is the coaching poor? Are these guys really just physically fragile? What the hell is going on?