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QUOTE (Soxbadger @ Mar 4, 2014 -> 04:11 PM) Its not really skewed. The Chicagoland area (that includes Lake/Cook county) likely pays a disproportionate amount of the taxes in IL. The majority of the money is also likely spent here, but Id bet if you did the math that Lake/Cook county are subsidizing the rest of the state and that some of our tax money is going to fund things in southern IL. Which is why Southern IL would be silly to split. But Id be glad to let them. I think it is likely the other way around. Most of the money is made and spent in the Chicagoland area. With the way chicago separates themselves in things like pensions, it shows how chicago cannot sustain itself. Madigan and the group wants to have other districts from around the state fund their own pensions and conyribute to chicagos while none of the chicago money would go to other counties. Thankfully, this part of the pension reform did not go through.

QUOTE (Jose Abreu @ Mar 2, 2014 -> 02:36 PM) I saw a few 91s/92s but surely he's better than that. Right? He had better not be throwing full speed in the first spring training game.

QUOTE (Eminor3rd @ Feb 28, 2014 -> 09:07 AM) Here's something that just came out today and illustrates greatly the effect of context on GB pitchers: http://www.fangraphs.com/blogs/exceptional...uches-everyone/ The concepts in the article are really good. I still don't like WAR as a reference to current play but the concepts are undeniable about defense partially because good pitchers will tailor pitching to the strength of the defense.

QUOTE (witesoxfan @ Feb 28, 2014 -> 08:29 AM) As a caveat, SIERA actually predicts what the ERA should look like with the numbers the pitcher has allowed, and it's incredibly accurate and usually is very close to the pitcher's ERA. It is also a solid predictor of future ERAs as well. However, it should not be used like that simply because those factors which a pitcher can't control - primarily luck and defense - can change drastically in one offseason. As an example, Justin Verlander's SIERA was 3.61 last year with an ERA of 3.46. I expect both of those to actually go down this year. Last year, for much of the year, the Tigers were running with Miguel Cabrera at 3B, Johnny Peralta at SS, and Prince Fielder at 1B, three very good hitters who have limited range in the field. This year, the Tigers should have 3 defensive upgrades in all 3 positions. This is something that SIERA cannot account for, so while we as fans expect Verlander's ERA to go down, SIERA does not because it cannot. This is true. However the formula they use with ground balls and line drives and flyballs and such is much more accurate and makes more sense than any others. This formula takes out as much of luck and defense as possible while including more factors than FIP and xFIP. No stat is going to be perfect as we are dealing with humans not numbers but as far as any I've found it comes the closest to really looking at how a pitcher can control runs and thus giving the team a better chance to win.

QUOTE (witesoxfan @ Feb 27, 2014 -> 10:49 AM) FanGraphs has it, it's just a little bit lower. Here's a brief write-up on it with more detailed explanations (including the math behind it) down below. http://www.fangraphs.com/library/pitching/siera/3 I'll link Sale's page because he's awesome: http://www.fangraphs.com/statss.aspx?playe...&position=P SIERA is listed under the heading batted ball, but it's actually separate from the batted ball statistics. It's listed alongside tERA (which also takes into account batted balls, but does not appear to be anywhere nearly as accurate), xFIP-, and xFIP. This is an outstanding stat. It takes into consideration all of the variables at which I was looking. It also does not use somewhat arbitrary multipliers like FIP and xFIP. I don't think as of right now there is much of an improvement on looking at how many runs a pitcher gave up based mostly on what he can influence. I can't find the numerical predictive model on which it's based on however I really like this one and will use it as the best indicator of how a pitcher can influence wins.

QUOTE (witesoxfan @ Feb 27, 2014 -> 10:34 AM) Actually, maybe we should be paying more attention to SIERA, as it does actually take into accounts balls in play to try and determine talent level. What is that and where can I find it?

QUOTE (Eminor3rd @ Feb 27, 2014 -> 10:27 AM) Right, I'm saying that since those are such high factors in runs allowed, then if you can do the same analysis for what accounts for HR and BABIP totals, and find a significant result, you could forecast regression for pitchers. Of course, maybe that's what xFIP does already, not sure. xFIP doesn't do it. This really doesn't show a regression for pitchers. It will predict how many runs they will give up if HR or BABIP values change. For example if a pitcher gives up an abnormally high number of HR, you can predict the runs for the following year if you change the value. Same with BABIP. If it's high one year, you can predict the decrease in runs if you lower the BABIP to what the average pitcher had that year. The regression model just uses past variables to determine their weight in the dependent varible. You can use this to predict fututre performance. This is what I use to determine which applicants to our DPT program have a good chance to pass our license exam thus which applicants we accept.

QUOTE (Eminor3rd @ Feb 27, 2014 -> 09:41 AM) If you can isolate factors that account for the variability of HR and BABIP, you may be stumbling upon a revolution. I'm not sure what you're asking. With this sample HR accounts for 47% of the predictive factor in the runs a pitcher gave up. Add BABIP into the mix and it's 69%. All you need to do is plug their values into the equation and it will show the predicted runs scored.

QUOTE (chw42 @ Feb 27, 2014 -> 09:16 AM) They are? Yes. If you've ever been in a pro locker room they know who they are and usually just stay away from each other with some incidences.

QUOTE (LittleHurt05 @ Feb 27, 2014 -> 09:02 AM) Eagles sign Riley Cooper to a 5 year, $25 mil contract with $10 mil guaranteed, but a gay player is too distracting for a NFL locker room to handle. Players are used to racists in locker rooms. Players are not used to gay players in locker rooms. It's all about player comfort levels.

QUOTE (witesoxfan @ Feb 27, 2014 -> 08:34 AM) I'd be surprised to even see 40. I ran a very basic regression looking at runs scored for teams over like a 2 year period of time just to see which numbers correlated more heavily with it, but it was very poorly done. My conclusions at the time were that stolen bases and batting average showed nothing conclusive at all about runs scored, while OBP was the most highly correlated at around 37-40%, something like that. Still not a significant figure, which tells you that it's more than just getting on base because so much of baseball is contextually based and luck plays such a large factor, but being that high tells you it's the most important aspect of scoring runs at the very least. I ran the numbers this morning and was shocked. I looked at variables predicting runs given up by pitchers over the last two years. The R2 was 47.5 for HR alone, 69.6 for HR,BABIP; 82.2 for HR, BABIP, BB; 86 for HR,BABIP,BB,HR/9 and 90 for HR,BABIP, BB, HR/9 and FIP. All of the models had a sig. of .01 or lower. This was using a stepwise linear regression. Granted it should have gone up when including HR/9 and FIP as one of the internal variables there is HR which is 47.55 of the variability on it's own. So in the two year sample (i only included pitchers with a combined 300 innings in the last two years) there is a high predictability of runs scored against a pitcher with HR, BABIP and BB. I guess FIP is a very good predictor of pitchers performance in giving up runs. I'm going to run a larger sample for a lrger number of years to see if it still holds true over time.

QUOTE (witesoxfan @ Feb 26, 2014 -> 04:34 PM) I'm incredibly interested in seeing the R-squared and standard deviation of these results. I have no doubt that std dev will be high as the variability is high in many of the factors. I would love to see an r2 of at least 60 but I'm not confident.

QUOTE (witesoxfan @ Feb 26, 2014 -> 04:07 PM) Well, then it's worth pointing out just his 2013 too 9.49 K/9 1.93 BB/9 46.6% GB% That is a K/BB of almost 5. The only problem thus far has been that his flyballs have a tendency to leave the yard a bit more often than others. Fangraphs is a great sortable resource. I think I found all the data I need to start. Thanks for showing it. I'll run a few models and post the results.

QUOTE (witesoxfan @ Feb 26, 2014 -> 12:30 PM) I think they've done quite a bit of this and it's where they derive the statistics from. So many of these variables show such little significance towards the runs scored with such high variability that it's impossible to say that one is more important than the other, but it essentially follows basic guidelines and sounds logic. 1) A strikeout is the best guarantee for an out. 2) A walk is never an out. 3) If the batter hits it, you prefer it to be on the ground because it's almost never a home run and the batter will usually not advance beyond 1B. 4) A flyball is preferable to a line drive, but those can be dangerous. 5) You do not ever want to give up line drives. Your ideal pitcher is one who has good command, gets a fair amount of strike outs, and keeps the ball on the ground. I'd argue that the best pitcher - starter or reliever - of the modern era is Mariano Rivera. His numbers: 8.22 K/9 2.01 BB/9 52.5% GB% Those can be supplemented, and you can be great without 1 of them, but I generally think you need at least two of them to be a great pitcher. That makes sense. So if you run the step wise regression you should get something like K is 30% of the variability, low walk rate is 15% and GB% is 10%. I'm not saying those are the numbers but just for example. I'd like to see that information compared to runs. I'm going to use the fangraphs info and runs the data over break and see what comes up.

QUOTE (witesoxfan @ Feb 26, 2014 -> 09:20 AM) My hypothesis would be that you'd see some slight correlation to GB% and run prevention, but it wouldn't be significant. Your best groundballers (as SP) since the statistic has been kept have been Brandon Webb, Derek Lowe, Jake Westbrook, Chien-Ming Wang, Tim Hudson, Aaron Cook, Zach Day, Fausto Carmona/Roberto Hernandez, Kirk Saarloos, and Justin Masterson. That's a pretty mixed bag. The one thing I notice when looking over those pitchers is that the most successful ones have been those that have been able to accrue some strikeouts. http://www.fangraphs.com/leaders.aspx?pos=...=0&sort=6,d You can mess around with that a little bit. One thing's for certain - you don't make it starting if you are throwing flyballs unless you pitch in a big ballpark. Chris Young and Jered Weaver are really the only starters to find some success. I know that GB% alone isn't a key factor. Maybe it's K/BB or K% and GB%. I think the best place to start is to look at the pitchers who gave up the least runs and do a step wise linear regression to see what factors pop up.

QUOTE (Eminor3rd @ Feb 25, 2014 -> 04:05 PM) Well, LD rate correlates very highly with high BABIP, which correlates highly with successful hitting metrics in general. So you can't link LD rate directly to wins, but you can link it directly to good hitting and then link good hitting directly to wins. The reason it's important to find year-to-year correlations is to help you evaluate if a hitter's success is sustainable. Again, it's trying to boil down metrics to representatives of "true talent," which should be less likely to disappear. I was looking at it from the pitching aspect of GB% not the hitting. Still seems to be that good pitching beats good hitting especially in the post season. If LD rate is correlated to BABIP, it makes sense that a high GB% or lower LD rate would be correlated with better pitching and poorer hitting. I need to find the numbers though.

QUOTE (Eminor3rd @ Feb 21, 2014 -> 01:32 PM) That makes intuitive sense, but research has shown no significant year-to-year correlation between LD rates at all. GB rate is less reliable than you'd think, but is more consistent than LD -- the problem is that it cannot be considered an inherently good or bad thing because it doesn't fit into the equation of linear weights. In other words, it is a class of event, but it isn't a final outcome. Therefore, it cannot hold a run value. A GB can become one of several types of hits or outs, and the odds of each event occurring are entirely dependent on defense, chance, and the ability of the hitter -- all context-dependent and infinitely variable. I understand the GB is dependent on the defense, however has it shown that the GB rate has an influence on runs scored. There cannot be a direct correlation due to the variability of events however is there a place that lists the GB% and runs scored. This summer this will be a project to research.

QUOTE (Eminor3rd @ Feb 21, 2014 -> 01:32 PM) That makes intuitive sense, but research has shown no significant year-to-year correlation between LD rates at all. GB rate is less reliable than you'd think, but is more consistent than LD -- the problem is that it cannot be considered an inherently good or bad thing because it doesn't fit into the equation of linear weights. In other words, it is a class of event, but it isn't a final outcome. Therefore, it cannot hold a run value. A GB can become one of several types of hits or outs, and the odds of each event occurring are entirely dependent on defense, chance, and the ability of the hitter -- all context-dependent and infinitely variable. To what are they trying to correltate LD Or GB? I'm looking for some type of correlation with winning games. I know they aren't consistent from year to year but niether are wins. Canthey use a pearson or rho correlation to find GB with wins in a given year? I don't have the answers and I cant find much from anyone else either.

QUOTE (Marty34 @ Feb 24, 2014 -> 07:03 PM) It's not about name value it's about track record and Paulino's track record is going to severely limit any return they may get for him. That's in a BEST case scenario. I disagree. If he is throwing well and showing he is healthy, he will have good value.

QUOTE (Marty34 @ Feb 24, 2014 -> 05:27 PM) Scott Feldman is going to get you more in a trade than Felipe Paulino. Feldman had enough suitors last offseason to command $6M. I disagree. Paulino is known as a very talented pitcher who just hasn't stayed healthy. This is where Cooper and Herm come in. They work with him and see where it goes. If it goes well there are many options. If it goes poorly you don't pick up his option and either Surkamp or rienzo get time.

QUOTE (HickoryHuskers @ Feb 24, 2014 -> 12:06 PM) I've always thought of him first as a writer/director. Ghostbusters was a funny movie, but you don't make that (Insert Celeb Here) is Dead thread based just on that role. Stripes was a much better role. He deserves celebrity based on that and SCTV work alone.

QUOTE (HickoryHuskers @ Feb 24, 2014 -> 11:19 AM) Harold Ramis, writer/director/actor, 69. Going to have to watch Caddyshack tonight in his honor. Great screen writer. Many laughs. "Not practicing but willing to learn" RIP

QUOTE (Athomeboy_2000 @ Feb 21, 2014 -> 02:47 PM) There will be no sober Canadians on Monday. Are there ever any? All green but too good to pass up.

QUOTE (witesoxfan @ Feb 21, 2014 -> 11:31 AM) That's pretty close. I think they basically use those 3 because most of the time, there is absolutely no way a fielder can catch that ball. What FIP suggests is that a pitcher can force ground balls exactly to where he wants the hitter to hit it (or infield flies or regular fly balls), but if he has statues that can only field what hits them and then only throw playing behind him, he can still give up an absolute ton of hits. FIP just tries to isolate the difference between a pitcher having a good fielding infield and a poor fielding infield while also taking lucky seeing eye singles out of the equation. Sabermaticians do realize that putting the ball in play, but weakly, is a very good thing. Regarding runs scored, I'm curious to know what you are looking for specifically? There was actually breakthrough research done regarding run expectancy quite a few years ago that suggested that the sacrifice bunt is a poor decision in almost all situations except in a situation where you are playing for 1 run (either to tie or win), there's a runner on 2nd, and 0 outs. It can be 1st and 2nd too with no outs, but in all other situations, bunting simply works against the likelihood that you'll score a run. Was there anything else you had in mind on that? I know that the pitcher can't control the fielders. However, FIP is being used frequently for pitchers performance. I think that a combination using a GB and line drive percentage maybe along with the others may be able to show more of the pitchers influence on the game rather than only BB, K, and HR which is the only pure control variables. For the runs scored, I know I'm in the minority but I'm less concerned about an individuals performance than how the individual impacts a win or loss. The performance aspect is for arbitration and salaries. A players impact on winning a given game is more what I would be interested in. The only way I can see to start breaking it down is how he impacts scoring runs at bat and prevents runs on defense. WAR doesn't really do it because that really looks at how his performance is better than another player of lesser performance. The runs prevented stat seems to make sense on defense and OPS and OPS+ kind of start it for offense but there are still too many variables not taken into account for it to do too much.

QUOTE (Chilihead90 @ Jan 16, 2014 -> 10:13 AM) To try and make this as short as possible, bWAR tells more about past performance, but fWAR tells more about future performances. It's more of a true talent indicator. Like for pitching, fWAR uses Fielding Independent Pitching numbers to figure in the calculation, whereas bWAR uses runs, and team wins. You get more outliers it seems with bWAR than fWAR. I think the large majority of the Sabr community would say that fWAR is the better number to use overall. After doing research on many of the stats this is one that bothers me the most, I think. If I understand it correctly (which is highly doubtful) FIP is predicated on the fact that pitchers can only control 3 factors: HR, BB and K. I think there is valid reasons to say that some pitchers can control the number of groundballs and thus control the game a little more. I realize it's not totally in the pitchers control because the fielders need to make plays. However, if the number of groundballs is increased the number of runs scored would decrease. There needs to be more stats focusing on runs scored versus runs allowed. I know there are some but there should be more focus on runs due to the fact that nothing else really matters in winning a game.