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Thread: Baseball Myths

  1. #436
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    watching Dave Valle, Billy Ripken, and Jerry Hariston on MLB Network.


    All they are doing is spitting out the worst cliches in the sport, and many of them are founded in myths.

  2. #437
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    Since this basically turned into a sabermetrics thread, I have a question. Does any stat like WAR for example take into account the fact that some players take days off and some play all 162 games?

    "We the best in the league, Tony!"

  3. #438
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    Quote Originally Posted by SpecialFNK View Post
    I think that's what I'm saying.
    if the pitchers are always different, then how can you compare them all together?

    if Cabrera was batting with Fielder on deck with pitcher A pitching 100 times, then it has to be compared to Cabrera batting without Fielder, with pitcher A pitching 100 times. if it's pitcher B/C/D/E/ect then they have to be compared separate, because the outcome could be based on the specific pitchers and not because of Cabrera or Fielder or any other batter.
    if pitcher A is David Price and pitcher B is Luke Hochevar, then the results could be determined by the difference in those pitchers regardless of who is batting.

    in these studies, are they taking into account who was pitching? because that can make a difference.
    Are you serious?

    It's a large enough sample size (proven) that the variances and differences between pitchers is literally negligible. They cause situational differences but when you take a full sample size of hundreds of at bats in a season, let alone the millions of at bats through the history of the sport.
    #ClutchTime

  4. #439
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    Quote Originally Posted by LAcowBOMBER View Post
    Since this basically turned into a sabermetrics thread, I have a question. Does any stat like WAR for example take into account the fact that some players take days off and some play all 162 games?
    In a sense. WAR takes the amount of innings played into account. So if a player his hurt his WAR is obviously going to be lower. Play more? The WAR will increase as long as the level of play during those games remains equal and doesn't dip.
    #ClutchTime

  5. #440
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    Quote Originally Posted by SpecialFNK View Post
    since I'm told to prove everything with evidence, this is where I would have to say.. prove this with evidence.

    with unbalanced schedule teams might not always face the same level of competition, or the same ballparks. the better teams in the AL Central have been able to beat up on a weak team like Kansas City more than the teams from the East and West can.
    Here is an article that explains which numbers stabilize at what rate

    Essentially, the article explains what type of a sample size you need to effectively judge a player. A sample size large enough to where variance like, facing "tough" pitchers stabilizes to the point where it doesn't count, to the point where you can safely say what a player is doing with some degree of stability and reliance. You'll notice most offensive numbers stabilize around 300-500 for some of the larger numbers like OPS (which, thus, throws out your little thing of using Ludwick's OPS in 2008 as he didn't pick up 350 PA's in 3-4 spots in the lineup that year, meaning he never stabilized), and it shows batted ball data (GB's, FB's....etc) stabilize as soon as under 100 AB's. The extreme number of pitchers a hitter sees throughout the season means that one game examples of seeing one good or one bad pitcher, or even an entire series of good/bad pitchers mean that hitters generally have no variance in the level of difficulty of who they see.

    It took me, literally, 5 seconds to yet again dispute your claims. Now, if you'd like to make a point, please, use something called "evidence". You've used only opinion and conjecture. This is how this is going to continue to go until you "take the time" to find something to prove your point.
    Last edited by 1908_Cubs; 02-01-2013 at 08:28 AM.
    #ClutchTime

  6. #441
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    Quote Originally Posted by LAcowBOMBER View Post
    Since this basically turned into a sabermetrics thread, I have a question. Does any stat like WAR for example take into account the fact that some players take days off and some play all 162 games?
    Every good counting sabermetric I know of will do so.

    For instance, wOBA, wRC+, and UZR/150 are all rate stats that show how well a player did on a per-play/per-at-bat basis.

    However, their cumulative counterparts, wRAA, wRC, and UZR, all account for totals.

    Someone with a wOBA of .400 would be a well above-average hitter, but if the only made it to the plate 350 times due to injuries, their wRAA will be lower, because they had a below-average number of plate appearances. The same is true for WAR.

  7. #442
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    If a guy plays less, he has less value. Like others said there are some stats, but missing games takes away from his production and it will reflect in WAR.

    You can always project it to a full season, but that's not extremely accurate because it assumes they continue the same production for the rest of the year
    You have no idea how excited I am right now.


  8. #443
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    Quote Originally Posted by 1908_Cubs View Post
    In a sense. WAR takes the amount of innings played into account. So if a player his hurt his WAR is obviously going to be lower. Play more? The WAR will increase as long as the level of play during those games remains equal and doesn't dip.
    Quote Originally Posted by WadeKobe View Post
    Every good counting sabermetric I know of will do so.

    For instance, wOBA, wRC+, and UZR/150 are all rate stats that show how well a player did on a per-play/per-at-bat basis.

    However, their cumulative counterparts, wRAA, wRC, and UZR, all account for totals.

    Someone with a wOBA of .400 would be a well above-average hitter, but if the only made it to the plate 350 times due to injuries, their wRAA will be lower, because they had a below-average number of plate appearances. The same is true for WAR.
    Thanks. Since I'm a sabermetrics convert I figure I better learn about them lol

    "We the best in the league, Tony!"

  9. #444
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    Just as a general aside; SpecialFNK have you ever taken a college level basic statistics course or quantitative methods class?

    I ask, in all seriousness, because much of the incompatibility between your views and what individuals like Jeffy, 1908 Cubs, and I have been attempting to tell you are entirely based in statistical method.

    If you do not understand the concepts of sample size, variance, standard deviation, correlation, and causation, et al you are not going to get anywhere.

    And for the record this has nothing to do with "advanced stats," and can be demonstrated with as basic traditional slash line of average, on-base percentage, or strikes and balls seen.

    The Ludwick example was perfect.
    You noticed that he seemed to hit better in 190 ABs with Pujols behind him than in the preceding few hundred. Your selection of a sample size was too narrow as a simple comparison of his total at-bats demonstrated he did not vary significantly from his career numbers.

    This is basic statistics:

    You need a representative sample size, a control (career #'s), defined variables, and you need to determine trends, variations, and correlations before declaring proof for causation.

  10. #445
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    Quote Originally Posted by LAcowBOMBER View Post
    Since this basically turned into a sabermetrics thread, I have a question. Does any stat like WAR for example take into account the fact that some players take days off and some play all 162 games?
    Yes, durability and longevity matter.

    It's still a counting stat that you gain the most value by playing consistently and the longest above replacement level players.

    Part of what made Pete Rose a 90 WAR player was that he played more than any other player of all time. (and he was well above average, not just an accumulator).

  11. #446
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    if there are pitchers that believe protection exists, that's all the evidence I need. how can one come up with evidence of what's going on in a pitchers head? any results that occur could be because of many different factors.
    I posted an article before from ESPN where Rays manager Joe Maddon said protection exists in a pitchers head. any statistical evidence whether it's good or bad could be effected because of other factors, so those results wouldn't mean anything.
    I also mentioned before that to me protection doesn't mean batter A in front of player B HAS TO have better production for it to be considered "protection". but when there are thousands of other variables, they can cause many different results.
    so basically any evidence is going to be able to be picked apart, and when there is evidence to maybe suggest protection it's going to be considered a small sample size.

    when the on deck batter is in the pitchers head and can cause the pitcher to pitch differently to the batter, I can consider that protection. and when a major league manager says protection can be in a pitchers head, I'm going to believe him.

    I don't know if this helps anything.
    if pitcher makes a perfect pitch to the batter exactly where he wants it, the batter can still get a hit.
    if pitcher makes a mistake and hangs a pitch, the batter can still miss it.

    I did find this. what does this mean?
    http://mlbresearch.blogspot.ca
    Protection Exists

    The sabermetric community has generally been successful at challenging baseball’s conventional wisdom. However, Bill James has noted a troubling historical pattern: sabermetric research often labels a phenomenon (e.g., clutch hitting) as non-existent when it can not be measured or detected. James suggests previous methods may be flawed and we may be “underestimating the fog” (note: that's a PDF link). Similarly, baseball statisticians may simply have too few instances when trying to measure something. Millions of pitches and at bats may not be sufficient given the statistical methods we are utilizing and the delicate trends we are attempting to find. Perhaps if baseball games lasted 100 innings and we had data sets containing 100 million at bats, we would then be able to detect more of the game’s mysteries.

    My suggestion?
    A production function – and its inputs – can provide clearer methods for measurement.

    Take protection, as an example. Is a batter’s success at the plate affected by having Barry Bonds rather than Neifi Perez in the on-deck circle? Previous research has answered this question by looking at a batter’s outcome with varying hitters on-deck. Such analysis consistently arrives at the same conclusion – protection does not exist:

    J.C. Bradbury, in his recent The Baseball Economist, states, “Protection is a myth.”
    In Baseball Prospectus’ Baseball Between the Numbers, James Click concludes, “Batting performance does not change significantly with the quality of the following batter..."


    Considering James’ fog argument, such prior research methods may be flawed. Bradbury’s regression analysis attempts to measure the effect of the on-deck hitter's quality on the current batter's outcome (his regression model has the on-deck hitter’s OPS on the right-hand side and the current batter’s outcome on the left-hand side). This approach is intuitive; in fact, my initial instinct might be to perform similar research. However, at bat outcomes involve many moving parts (where the ball lands, reaction of the defense, and luck, to name a few), and Bradbury is trying to measure the effect of an outcome-based rate (OPS) on another outcome. Thus, if there is some noise or randomness within the data, the problem would be compounded in the findings. When discussing the previous development of a new statistic (platoon differential), James summarizes the challenges:

    “… the result embodies not just all of the randomness in two original statistics, but all of the randomness in four original statistics. Unless you have extremely stable ‘original elements’ – original statistics stabilized by hundreds of thousands of trials – then the result is, for all practical purposes, just random numbers.

    We ran astray because we have been assuming that random data is proof of nothingness, when in reality random data proves nothing.”


    How can we get around these issues?
    Through the lens of a production function, we can analyze this same protection problem as a process involving inputs as well as outputs. For the “protection process,” inputs can describe what is going on within a pitch before the batter reacts to it (my data set tells me the location coordinates, velocity, pitch type, etc. of every pitch thrown in MLB since 2002). If protection exists, a batter’s experience at the plate would be distinctly different – in several advantageous ways – when a great hitter is standing in the on-deck circle. For example, we would expect a batter in front of Barry Bonds to see more pitches within the strike zone (the pitcher will nibble less) and more fastballs (pitcher has more control). Both MLB players and empirical research would agree that these two inputs provide a significant advantage to the batter.

    My regression analysis attempts to measure the effect of a better on-deck hitter in this way, i.e., the effect on the current batter's experience in seeing both more pitches in the strike-zone and more fastballs. Specifically, either “strike-zone location: yes or no” or “fastball: yes or no” is my dependent variable (left-hand side). On the right-hand side, I include the OPS of the next hitter and then control for everything within the situation: the pitcher, the batter, pitch type, count, outs, runners, ballpark, and year.

    Using per pitch data from 2002 through 2006, the results show that better on-deck hitters have a positive and significant effect on both the strike location and fastball inputs, and hence, protection does exist in so far as a pitcher adjusts his approach and a batter enjoys multiple advantages when a good hitter is on-deck.

    Effect on a pitch being located within the strike-zone:




    Coefficient (Std Error)

    OPS of next batter


    .0169




    (.0029)

    Effect on a pitch being a fastball:




    Coefficient (Std Error)

    OPS of next batter


    .0107




    (.0029)


    The protection production function seems to tell us conflicting stories. The "input" findings show that protection exists, but the "output" evidence suggests that protection does not exist. So, which answer is correct? In addition to the potential randomness issue discussed earlier, outputs suffer from one other relative disadvantage – the mere volume of data being studied is different. Analysis at the per-pitch level (inputs) employs about four times the number of instances as per-at bat level analysis (outputs). Thus, while prior research may (or may not) point us in the right direction, I would argue that the production function's inputs push us much closer to the truth.

    Lastly, moving beyond this discussion on protection, I want to be clear about my broader argument. The sabermetric community will benefit as it moves away from its relatively strict reliance on outcomes and outputs. Events on the field of any sport involve a great deal of processes. While outcome data (e.g., much of what you find online at great sites such as retrosheet and baseball-reference) have generally been more widely available, a full picture of economic analysis in the future will rely much more heavily on whole processes and their inputs.
    I was also reading some of this topic from another forum. I'm not going to copy every post, but some can take a look.
    http://forums.rotoworld.com/index.ph...ic=140816&st=0

    maybe it also should be asked..
    what is protection?
    does protection mean the batter being "protected" has to have better production than if he were not being "protected"?
    does protection mean the batter being "protected" has to be pitched to differently than if he were not being "protected"?
    can't a form of protection be the way a lineup is constructed, having multiple good batters all protect one another so the opposing pitcher can not pitch differently based on whether a bad hitter could be on deck?

    where does one find statistics for a player to show how he did with specific players in front or behind?
    Tigers manager Jim Leyland in the past had a habit of when one player gets a day off his replacement would just bat in the same spot in the lineup regardless of who he is. there should be somewhere to find that information yes?

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  12. #447
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    Quote Originally Posted by SpecialFNK View Post
    if there are pitchers that believe protection exists, that's all the evidence I need. how can one come up with evidence of what's going on in a pitchers head? any results that occur could be because of many different factors.
    I posted an article before from ESPN where Rays manager Joe Maddon said protection exists in a pitchers head. any statistical evidence whether it's good or bad could be effected because of other factors, so those results wouldn't mean anything.
    I also mentioned before that to me protection doesn't mean batter A in front of player B HAS TO have better production for it to be considered "protection". but when there are thousands of other variables, they can cause many different results.
    so basically any evidence is going to be able to be picked apart, and when there is evidence to maybe suggest protection it's going to be considered a small sample size.

    when the on deck batter is in the pitchers head and can cause the pitcher to pitch differently to the batter, I can consider that protection. and when a major league manager says protection can be in a pitchers head, I'm going to believe him.

    I don't know if this helps anything.
    if pitcher makes a perfect pitch to the batter exactly where he wants it, the batter can still get a hit.
    if pitcher makes a mistake and hangs a pitch, the batter can still miss it.

    I did find this. what does this mean?
    http://mlbresearch.blogspot.ca


    I was also reading some of this topic from another forum. I'm not going to copy every post, but some can take a look.
    http://forums.rotoworld.com/index.ph...ic=140816&st=0

    maybe it also should be asked..
    what is protection?
    does protection mean the batter being "protected" has to have better production than if he were not being "protected"?
    does protection mean the batter being "protected" has to be pitched to differently than if he were not being "protected"?
    can't a form of protection be the way a lineup is constructed, having multiple good batters all protect one another so the opposing pitcher can not pitch differently based on whether a bad hitter could be on deck?

    where does one find statistics for a player to show how he did with specific players in front or behind?
    Tigers manager Jim Leyland in the past had a habit of when one player gets a day off his replacement would just bat in the same spot in the lineup regardless of who he is. there should be somewhere to find that information yes?

    I am embarrassed for you at this point.

  13. #448
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    Quote Originally Posted by Guppyfighter View Post
    I am embarrassed for you at this point.
    thanks, good to know.

    I feel the same way for those who think everything in baseball can be put into numbers.

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  14. #449
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    Quote Originally Posted by SpecialFNK View Post
    thanks, good to know.

    I feel the same way for those who think everything in baseball can be put into numbers.
    What is wrong with using pitch selection, pitch location, and stats of the batter for this? Where the pitcher puts pitches and what he chooses is not hypothetical. It's what actually happened. We know what these pitchers did to protected batters to attempt getting outs. Nothing different than normal.

  15. #450
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    Not even close to as bad as the crap you are spewing now. Its all nonsense. Just anything you can think of to try to save your point. Just give up dude.
    You have no idea how excited I am right now.


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