Talk:Sabermetrics/Archive 1

Tommy Lasorda Quote
The whole passage "a truly outstanding player, for example, might be described as being worth 54 runs more than an average player at the same position over the course of a full season. Oddly enough, this matches the unscientific quote by former Dodger manager Tommy Lasorda who said almost every team will win 1/3 of their games (which is 54 in a 162 schedule), and lose 1/3 of their games - it's the other 54 that determine your season" is uneeded. There is no specific significance to a player being 54 runs above average being an outstanding player. That would be an outstanding player-but there is no specific meaning attached to that number. It is not a significant benchmark that separates distinctions in any way, and the LaSorda quote thus has no relation because there is no real reason why 54 is used there. -BBonds —Preceding unsigned comment added by 68.116.160.191 (talk) 01:56, 8 January 2008 (UTC)

Quote
I don't really like David Grabiner's quote to open the article. Specifically, the Ken Griffey Jr. idea should be more along the lines of "how many home runs is Ken Griffey Jr. likely to hit next year" since of course it is impossible to know his future production. I feel like this may give false ideas to the article readers as to what sabermetrics entails. Is there a better quote that could be used that would better protray sabermetrics?

That's the thing about sabermetrics...it actually CAN predict how many Griffey is LIKELY to hit. Since we cannot predict the future, we cannot know how many home runs he will actually hit, but we can estimate what he is likely to do. Not to overly simplify things, but if you roll a die a million times, although one cannot predict with certainty the actual number of 6s rolled, one can predict with a very high degree of certainty that the number will be very close to 1/6 of one million. Oh, and sign your posts. Mickeyg13 21:18, 3 October 2007 (UTC)


 * The quotation may not be the best lead or second lead but I agree with Mickeyg13, sabermetrics does ask and answer such predictive questions.
 * The Manifesto is 15(?) years old, so it uses Ken Griffey home runs or example. The update to Ryan Howard is inappropriate in quotation and I have reverted it, along with completing the quoted paragraph (six more words at the end) and dating it uncertainly (1994?). --P64 (talk) 00:25, 26 February 2010 (UTC)
 * Someone recently revised the quotation again, reverted today by User: Seancasey00. This time the culprit is an evident fan of the Chicago Cubs and Ernie Banks, a 1950s/60s contemporary of one player named by Grabiner, Mickey Mantle. Jointly the two revisions by Oliveralbq did not even "bring examples up to date" as his only edit summary reports.--P64 (talk) 15:19, 26 May 2011 (UTC)

Anon vanity posts
It appears that a long series of anon edits added a number of new names that are vanity posts to this article in April and May. I have reverted the article back to where it was before the anon edits, but in doing so I may have eliminated legitimate edits as well as clearly self-promotional ones. This article needs to be reviewed by someone who really knows the history of sabermetrics to sort the "buy my computer game" or "subscribe to my service" people who are vanity posts from the real sabermetrics proponents. OverInsured 06:28, 9 June 2006 (UTC)
 * Well, then DON'T revert it if you're going to delete legitimate content. Delete the spam instead. If you're not knowledgeable enough to do this in the first place, then why are you reverting the article?  You should leave it alone and simply bring to other people's attention that there's spam that needs to be edited. Hayford Peirce 18:04, 9 June 2006 (UTC)


 * I wrote too concisely and was unclear. I should have reverted only the prominent contributors section, because it looked like all the edits were there but I did not double check. The edits were anons and looked self-promotional, but I requested review by others to make sure that what I felt comfortable about was STILL double checked by others. I feel comfortable identifying anon vanity posts when I see them, but I believe the entire principle of wikipedia is that we decide these thinghs as a group and invite the opinions of others. I asked for help on the chance that I cut encyclopedic content, but I actually believe that what I cut was self promotional. You're right that my initial post was unclear and sounded too sweeping. I'll correct.  OverInsured 19:19, 9 June 2006 (UTC)


 * You're right. When I looked at the detail I cut too much good stuff with the self-promo. Please check this version. In general, what was in before all the anon edits I left in place, since most of it had stood for some time. The people who seemed to be trying to sell things and did not have high Google hit counts and who were added by anons I cut out. If someone had over 10,000 Google hit counts I left them in. Please review what I did and look for ways to make it better. OverInsured 19:36, 9 June 2006 (UTC)

listing of the heavy hitters
Now that I've edited the caption to say that the list is arranged alphabetically, I wonder if this is actually the way it should be? I myself would start it off with Bill James, then, I suppose Pete Palmer and John Thorn. Then what? Billy Beane? Then who? It's a can of worms, I agree. Any suggestions? Hayford Peirce 21:06, 9 June 2006 (UTC)


 * I 110% agree that James, Thorn and Palmer stand above all the rest for those who researched the game. You can argue that Beane led the way on deep implementation of the principles within baseball, although as noted Weaver was capturing sabermetric stats even before James published his first book and other managers followed suit. I don't have a great idea on how to turn all that into a merit based sequence to replace alphabetical order. OverInsured 21:32, 9 June 2006 (UTC)


 * I agree, alphabetical neutrality is not best here, and I can't improve it easily. --P64 (talk) 22:14, 28 February 2010 (UTC)

Math needed
I think an article realted math should to some math. We need a math needed templete.--Scott3 21:33, 15 July 2006 (UTC)

Quality of Article
This article is off to a good start but try to write it in a more neutral tone and cite sources. It's pretty obvious to the casual reader that this article was written by a huge fan of Sabremetrics. Quadzilla99 15:48, 23 December 2006 (UTC)


 * I don't think there is the slightest problem of neutrality here. I think there's a much more serious issue of lack of meaningful content. A WP reader would learn practically nothing from the current article about what it is that sabermetricians do.  Lists of a few key concepts and researchers in the field are given priority here, but this should follow a good solid essay on the field of sabermetrics.  The entire history of the quantitative analysis of baseball is omitted. Although it was before my time, not only were the canonical books (which are mentioned in bare outline here) an exciting time of rapid development but also the informal and less visible community that grew up on the Usenet brought a fantastic array of minds into discussion and analysis. What were the substantive research problems? What were the main issues?  What were/are the controversies?  Where does sabermetrics fit in (the scouting vs. analysis controversy)? How did baseball researchers go about measuring offensive production, defense, baserunning, batting order, valuation of players, pitcher usage, and game strategy?  None of these topics are mentioned.
 * The harm is that tags are big, fat, ugly, disfiguring warnings, and they should only be used when we have serious need to warn our readers. Otherwise we're just making it harder for them to read the article.  I do think statements such as you point out should be removed or altered to make them NPOV, but I'm not seeing that there is a major enough issue to warrant the big box at the top. I'll take a closer look at the article with your comments in mind and see what I can do. Beyond My Ken (talk) 23:10, 25 September 2011 (UTC)


 * These need to be laid out in a master essays with links to smaller essays (some of which are already on Wikipedia). A lot of this research has been cumulative in the best way that science is cumulative; it is rigorous and subject to peer review; and it has much more fundamental structure (in terms of areas of research -- what are all those little terms that are in that list a part of, how do they fit into a field of study?) than this article even hints at. Nor does the article talk about the revolutions in technology, the availability of game and microdata -- and the internet itself -- that has made the rise of sabermetrics possible.  Somebody who is familiar with all of this, and who is also perhaps steeped in the cross-currents of past debates, needs to take hold of this article.  And let the critics have at it, too.--Mack2 01:10, 17 January 2007 (UTC)


 * I think a good essay would have a different structure as well, tentatively with the following topics:


 * I. Definition and Origins of Sabermetrics (including analysis of bb stats historically)


 * II. Development of the Field: a. Main Areas of Research (with links to WP and external literatures), with issues and advances in these areas: game strategy, pitching, batting, defense, baserunning, forecasting, business, etc. What have we learned about expected payoffs in wins from SH, baserunning, batting order, marginal run values, etc. b. Types and Sources of Data, including historical game data, player stats, etc. Other topics . . . such as "measurement" of pitch type, location, speed; measuring vectors and speed of batted balls.


 * III. Sabermetric Theory and Practice. a. Use of stats in the game itself, by field managers and general managers), b. Scouting vs. stats. c. Use in sportswriting/broadcasting. d. Changing language of the game.


 * IV. Emerging and Problem Areas: a. measuring defense, b. forecasting, c. the player marketplace. d. Microdata (pitches, batted balls, fielding etc.)


 * V. Main contributors of data, analysis, innovations in the main fields of research (links to WP articles).


 * VI. The Future: new vistas in data collection and analysis.


 * The above are just off the top of my head, but I aim to suggest some of what's missing as this article is currently structured. I'm sure somebody else will have a better way to go at it. But I think what's in this article now is very inadequate. The main focus should be on the SUBJECT (research field) of sabermetrics, and only a secondary focus on the people who have advanced it, though both are important.--Mack2 17:29, 18 January 2007 (UTC)
 * I agree that the article could use some (or some more if I missed where it is now) information on the people who disagree with sabermetrics and some of the arguments against it. I hear people arguing about it on sports talk radio nearly every day of the baseball season, yet reading this you'd think it's been accepted by all in baseball that it is the best way to do it now. For instance, Harold Reynolds of the MLB Network fights against sabermetrics' importance every time he's on. Dancindazed (talk) 22:58, 24 September 2011 (UTC)
 * Criticism of sabermetrics can and should be included in the article, but there are two types of it, and they need to be dealt with differently. The first is the resistance from people, many of them in the game itself, who don't want baseball to change, who want the game to be the way it always was, and see sabermetics as an unwanted disturbance of the game they know and love.  Reynolds falls in this category. This kind of criticism needs to be handled in a way that makes clear that these people, while they may have credibility as holders of traditional baseball knowledge, have no basis from which to criticize sabermetrics from a statistical point of view.  They should not be presented as reliable sources as to whether sabermetric stats accurately measure what they intend to measure, but can be used a reliable sources as to their own opinions. On the other hand, anyone who criticizes sabermetrics from a statistical standpoint, and has the right credentials to do so, can have their views presented as legitimate criticisms.  It surely cannot be the case that all sabermetrical stats (some of which are complex constructions) do the best possible job of measuring what they intend to measure, and it's possible there are better ways of accomplishing the task.  I assume that sabermetricians, like academics in every discipline have disagreements and disputes, and these can be reported on, as long as we don't stray into WP:FRINGE territory, but the article should not become a repository for the views of people who are not knowlegable about sabermetrics, and don't like it just because it's new and strange. Beyond My Ken (talk) 23:19, 24 September 2011 (UTC)
 * It seems inconsistent that there are concerns of lack of criticisms in the article, but a neutrality tag is removed from the article with the rationale that a lack of criticism is not a neutrality issue.—Bagumba (talk) 21:57, 25 September 2011 (UTC)
 * There is a distinct difference between saying "The article can be made better by including the views of those who criticize sabermetrics" and saying "The article is not neutral." The article is neutral, because it does not make significant claims for sabermetrics, but is primarily descriptive, without presenting a point of view.  I agree that adding more neutral description is a good thing, but that is not the same thing as tagging an article as being non-neutral. There is no consensus for that. Beyond My Ken (talk) 22:17, 25 September 2011 (UTC)
 * I'll agree that the article is mostly void of POV (not necessarily a good thing either), but there are occasional statements that are pro-sabermetrics, e.g. "yielded a number of interesting insights into the game of baseball and in the area of performance measurement." Typically, there isnt a consensus needed to tag an article—it's only a concern—but a consensus is needed to remove it. I honestly dont see the harm in tagging the article and encouraging readers to help improve/resolve the concern, but will leave it to someone else to restore it if it is needed. —Bagumba (talk) 22:47, 25 September 2011 (UTC)
 * I'm doing a history project on sabermetrics and have not learned much at all from this article. All of the history is discussed in the links on the Notable proponents section.  However, these links only provide history on either one person's contributions or a group's contributions.  We should take some of the information provided in those articles and incorporate it into this page.  For people trying to learn about sabermetrics, this article only gives an extremely broad overview of what sabermetrics does and then provides links to a hundred other articles involving specific things within sabermetrics. FIRECAKE (talk) 12:53, 15 March 2012 (UTC)

Runs against average
I'm not gonna delete this entry again, I'll leave that to someone more knowledgeable than I. But -- I'm a member of SABR and for the last 4 or 5 years I've been receiving a daily email message from the SABR group in which various members send comments, queries, etc., to a central List (so they call it) about research matters. Then every day the moderator posts the 10-40 messages that have come in that day in a single email to the subscribers to the service. It's sorta like a chat room or newsgroup discussion area, except it's done by email and it's exclusively about research matters, NOT general baseball discussion, such as "who's gonna win the Series". I've just checked my SABR mailbox on Eudora -- there are 3443 separate emails! That means there are probably at least 35,000 to 50,000 individual emails within that group. I've just done a Search for "runs created" -- that returned 265 entries. I Searched for "total player rating" -- that returned 45 entries. I then Searched for "runs against average" -- and got zero entries. "RAA"? -- zero entries. A Google search for "runs against average" only brings in 65 hits -- many of them on blogs. Surely an extraordinarily low total for a generally accepted research tool. So it looks to me that, whatever the merits of the method, it's almost certainly Original Research under the Wiki definition and shouldn't be here. Nor should it have a separate article in Wiki about it. Hayford Peirce 02:24, 6 February 2007 (UTC)
 * I know the above comment is 4 years old now: I just searched the both and one got 25,600 results and the other over 50,000.. (and that was with quotations for exact results). Dancindazed (talk) 00:22, 25 September 2011 (UTC)

Proposed deletion of Runs Against Average article
I've just proposed that the above article be deleted from Wikipedia because, in my opinion it is both non-notable and Original Research, at least as Wikipedia defines both terms. If you want to join the discussion about whether this article should be deleted or not, go here:http://en.wikipedia.org/wiki/Wikipedia:Articles_for_deletion/Runs_Against_Average Hayford Peirce 04:37, 8 February 2007 (UTC
 * I tried to tag the article as Original Research but its author deleted the tag. I agree with your recommendation.--Mack2 05:32, 8 February 2007 (UTC)
 * Result was delete. MaxEnt (talk) 19:12, 17 December 2007 (UTC)

Hoax
This is surely a Hoax site, i will pin it up in notice if no citation will be bothered 144.138.85.30 12:32, 20 May 2007 (UTC)

Close this page?
I suggest we close this page until someone can write this article in a neutral way that doesn't promote sabremtrics so much. The public does not embrace sabermetrics as a true science, since there is no control group to prove the theories of sabr people. Also, most of the stats claim to be 'total evaluators' - when in reality they are flawed. It should be pointed out that sabermetrics is nowhere close to a science at this point in time. 66.227.169.69 (talk) 05:03, 27 November 2007 (UTC)


 * What? The word science doesn't appear once in the article as I find it today.  Not only is Sabermetrics widely discussed (whatever merit it might or might not have) it has also spawned similar activities among die-hard fans in other major sports leagues, such as the NHL, which has lately become more interesting prospect as the NHL now publishes official shift charts.  When you find a strong statistical correlation on an existing data set your main obligation is to prove it wasn't a post hoc by testing it against new data you haven't seen before to see whether the correlation holds up.  Control groups need not apply.  MaxEnt (talk) 19:25, 17 December 2007 (UTC)


 * Yeah, nobody is interested in sabermetrics. Only 627,000 hits on Google (12/29/07).  Only about 150 Wikipedia pages link to the Sabermetrics article.  To be sure, this article needs to be improved. But to say that it should be deleted, not to mention for the reasons given above, is absurd.--Mack2 (talk) 03:31, 30 December 2007 (UTC)


 * Fix it instead of deciding to close it. "POINT IT OUT" if you have a problem with the article! Freeth (talk) 03:44, 7 February 2008 (UTC)

No criticism?
There's a huge gap in this article. It doesn't list any of the shortcomings of sabermetrics or list any oppositions of this approach to baseball. I think that because of that, this article deserves a neutrality tag. Phattonez (talk) 05:23, 16 September 2008 (UTC)
 * Again as in another talk topic, I agree there needs to be more information on the criticism. Maybe the problem is that all the opponents of sabermetrics are generally too unfamiliar with computers to edit it in, and the rest have no enthusiasm to. I understand and agree with the use of sabermetrics, but I also know of people, some of them respected in the baseball world, who do not. I would agree with the neutrality tag being needed. Dancindazed (talk) 23:04, 24 September 2011 (UTC)
 * See my response under above. Beyond My Ken (talk) 23:20, 24 September 2011 (UTC)

Sabermetrics Becomes Mainstream
The article makes several unreferenced and contradictory statements about when/where/how sabermetrics has become "mainstream" or pervasive. In particular, it credits at least three different people with being the first to employ Sabermetrics in an MLB front office. They can't all be the first. Further, all of these claims about Sabermetrics having suddenly become pervasive in the wake of "Moneyball" being published, and that before Moneyball "rigorous statistical analysis was rare" -- they just seem absurd, and dramatically overstate the impact of the book. They also seem to be implying that the adoption of new methodologies is a sudden recent development, rather than a more gradual evolution that has been going on for decades. Furthermore, if the article is going to assert that Sabermetrics has become mainstream, then isn't it ridiculous to include people like Max Kellerman as "proponents?" If he simply agrees with the use of the science and hasn't made major contributions (like Palmer, James, et al), then why not add every writer/commentator who covers baseball? Sportswriter (talk) 14:38, 19 April 2009 (UTC)

Major Proponents
It pains me to see my name--Eric Walker--not included in the "major proponents" list, because it was I, at the request of Sandy Alderson, with whom I had been working for some years, who taught Billy Beane what is today called Moneyball. But we are not supposed to add our own names to things, so I leave it to anyone interested to read Moneyball and (better) Alan Schwarz's book The Numbers Game, and decide if my name merits mention--not owing to vanity (or not alone), but because my role with the A's under Alderson and Beane was pivotal (if as much by being in the right place at the right time as anything else) in the adoption of statistical-analysis methods by major-league clubs. 63.174.56.82 (talk) 22:36, 17 May 2009 (UTC)
 * Still no takers, eh? Nothing on Eddie Epstein, either.  Has the much-discussed "total rewrite" idea gained any traction?

63.174.56.82 (talk) 22:51, 26 September 2009 (UTC)
 * A convincing argument could be made for Walker's inclusion. He's mentioned on several early pages of Moneyball in a pivotal moment of Billy Beane's acceptance of sabremetrics as a useful tool. I'll try to work something in. PrBeacon (talk) 23:16, 2 May 2010 (UTC)

plagiarism (delete section Controversy)
Most of section "Controversy" is direct quotation of the second half of Wainwright fires at sabermetric voters. In the first half, author Brian Walton primarily quotes Wainwright. Then he speaks for himself which was nearly copied here. WP:PLAG

That specific controversy about one award to a player for work during the 2009 season does not warrant much attention here. Maybe one line in a section or paragraph that covers other such controversies. --P64 (talk) 23:21, 25 February 2010 (UTC)

needs wholesale rewrite
This article needs a thorough rewrite. (I would grade it start quality, bottom importance, but that isn't my place.) Three years ago ("Quality of Article") Mack suggested one organization for a fresh start.

I have replaced section "Controversy" (just above) with section "SABRmetrics in the classroom", where I have named two college courses. I don't suggest that it belongs at the top in a fresh start and I don't know that the courses are current. Albert's site at BGSU includes includes his essay, An Introduction to Sabermetrics. It dates from the 1990s, as does Dave Grabiner's Manifesto quoted in the lead. Andres at Tufts provides a 2007 course syllabus. Probably a list of major "proponents" should include Eric Walker or it should be much shorter. The longtime editor of SABR newsletter "By the Numbers", Phil Birnbaum belongs on any short list of proponents. But should major proponents or contributors or both be listed? What about opponents? --P64 (talk) 23:56, 25 February 2010 (UTC)


 * Agree with idea of rewrite. There are more issues discussed in at least three other threads above, like Quality of Article -- so refactoring those into one thread may be helpful. I think the article could use a proper section on criticism, skepticism and/or debate. Two notable critics like Joe Morgan and Richard Griffin are mentioned in Lewis' Moneyball (in an afterword of about 15 pages where he answers them and others), although on second thought I dont know if Morgan has much to contribute to the debate other than old school stubbornness. I'm a longtime fan of the game but new to the subject of sabermetrics, and so far it seems like the establishment views this topic as little more than fantasy/computer baseball. PrBeacon (talk) 20:45, 3 May 2010 (UTC)

pop-cultural references
Maby as a start: I was just watching Episode #308 of Numb3rs called Hardball, where sabremetrics are kind of the key to the whole episode. My english isn't that good, so I guessed it to be better to leave a note here so hopefully others may put that info into the article. fyi: List_of_Numb3rs_episodes_(season_3) <- a link back to sabremetrics has already been made there. —Preceding unsigned comment added by 89.182.88.40 (talk) 19:03, 20 April 2010 (UTC)

Vandalism against Carson Cistulli, Sabermetric Aesthetics?
Watch for vandalism against these, user "Bayes37" just removed them writing: a) "removed irrelevant toy stat" b) "carson cistulli is not a major proponent of sabermetrics" I believe both to be untrue. In response to the first claim there is an article here on NERD and as for its place in a section called "Examples of sabermetric measurements" I will say that first while I doubt that it's in the mainstream media neither is LIPS, PERA, or FBV and in season it is updated in FanGraphs game previews, second it is referenced on other web sites in the sabermetric community (off the quickest of googles cf. http://www.ghostrunneronfirst.com/2010/06/getting-nerdy-with-jays-starters.html ; http://www.ussmariner.com/2010/06/04/game-54-angels-at-mariners/) and so the question for me is which active and historical sabermetrics statistics qualify for an examples page? I think that one about the aesthetics of baseball is a good choice for such a list but I'm open to discussion here in the Talk section ... For the second claim I think Cistulli's position as a major proponent of sabermetrics is clear but if it's not we can have that discussion too ... Sean 23:28, 7 January 2011 (UTC)Sean

Sabermetrics in the classroom
Professor James H. Albert teaches "MATH 115B – Introduction to Statistics – Baseball Emphasis" at Bowling Green State University.

Lecturer Andy Andres teaches Sabermetrics 101: The Objective Analysis of Baseball at Tufts University.

Professor Thomas Timmerman teaches Sports Management at Tennessee Technological University based on Moneyball.

Professor Thomas Severini teaches Statistics 101-Sabermetrics at Northwestern University. "

This is interesting but not necessarily encyclopedic. If someone wants to make a case for this section citations would be a good start and perhaps more comprehensive research on the subject, more writing than just a 4 person list.--78.234.204.162 (talk) 08:09, 20 April 2011 (UTC)

Major proponents of sabermetrics (alphabetically arranged)
I shortened the descriptions on the list "Major proponents of sabermetrics (alphabetically arranged)" but kept all individuals listed. For the moment the two pairs have been removed but if someone would like to re-write these as individual listings all four seem like interesting candidates:

Don Daglow and Eddie Dombrower are baseball simulation game designers whose sabermetrics-based games have introduced "new statistics" to expanded audiences. They are best known for Intellivision World Series Baseball (1983) and Earl Weaver Baseball (1987). Daglow also designed Baseball (1971), Tony La Russa Baseball (1991) and Old Time Baseball (1995).


 * John Thorn and Pete Palmer are the authors most often mentioned along with Bill James as having popularized sabermetrics. Thorn is a noted baseball historian, while Palmer is by profession a statistician, although each has deep knowledge in the specialty of the other.  They collaborated on two books that present sabermetric statistics and readable, common-sense explanations for why it's worth thinking about them: The Hidden Game of Baseball and the series of baseball encyclopedias called Total Baseball, with David Pietrusza and Michael Gershman.  They also include the mathematical formulae for the statisticians, but the strength of their books is the accessibility of the statistics for everyday baseball fans.  Thorn is a frequent commentator for ESPN, was advisor to the Ken Burns documentary series "Baseball" (1994), and is an advisor to the Baseball Hall of Fame in Cooperstown, New York. In 2011, Thorn was named the Official Baseball Historian for Major League Baseball. Thorn, Palmer and Gershman provided the statistics and analysis for the Tony La Russa Baseball series of computer games.

I might start this but I think it's an open question who deserves inclusion on this list or even how useful this list is on this page.

--78.234.204.162 (talk) 08:49, 20 April 2011 (UTC)

Use of "luck" in measurements
The article says that Sabermetrics is "the analysis of baseball through objective, empirical evidence". It also lists Peripheral ERA as a sabermetric measurement. However, the article on PERA says that the measurement attempts "to account for good (or bad) luck in the combinations of hits, walks, home runs, and strikeouts". I didn't see "luck" defined statistically anywhere, so to me it sounds very nonobjective and nonempirical. Attys (talk) 22:00, 20 August 2011 (UTC)
 * I think you're missing the point of PERA. The article says it accounts for luck but in the sense that a bad defense is bad luck to the pitcher or a big ballpark is good luck, so I think that's a little bit of poor writing on that article's part. The stat can help translate how a pitcher will do with a different team and ballpark. For instance if you have a statistically good pitcher that allows a lot of warning track fly balls in PETCO, his PERA for Coors Field should show how that particular pitcher is not a good fit for the Rockies because he'll be allowing a lot more home runs. Conversely a PERA would show that a ground ball pitcher would have a higher PERA with a bad defensive infield behind him. ERA would make no such reflection. That's a very sabermetric statistic to have in mind when evaluating a pitcher. Dancindazed (talk) 23:16, 24 September 2011 (UTC)

Assessment comment
Substituted at 12:07, 4 October 2016 (UTC)

Sabermetrics in the classroom
Removed the following:

"== ...such as attendance...? =="

...rather than industry activity such as attendance." What is that part doing in the opening sentence? Attendance is generally a result of whether or not the team is doing well, and paying attention to the attendance of a team is not mutually exclusive to sabermetrics. I don't understand why it's mentioned in the opening of the article in the manner it is, unless it's subtle vandalism meant to poke fun at the Athletics' lack of attendance recently(??) Or am I missing something? Dancindazed (talk) 17:15, 26 September 2011 (UTC)
 * Attendance may be an extremely rough gauge of how a team is doing, but it's far from being useful, since so many other factors (market size, geographical location of the stadium, demographics of the potential audience, media coverage, ticket price, etc.) go into determining how many people go to games. True, everythign else being equal, a good team will draw better than bad team, but in the real world, "everything else" is extremely unequal. I doubt a dig at the A's was intended. Sabermetrics isn't about Moneyball, Moneyball is about a team which uses sabermetrics. Beyond My Ken (talk) 17:20, 26 September 2011 (UTC)
 * Hmm your explanation helps me understand why someone worded it that way, but I think the wording could be improved. It's confusing to someone who's trying to actually learn what it is. Essentially that part of the opening is attempting to point out that all sabermetric stats focus on game play, as opposed to other groups of stats you might see in a baseball almanac, such as highest attendance or most consecutive sold out games etc. I think the word "especially" is what detracts from the intended meaning. It's not especially in game stats. Sabermetrics is only in game stats. I'll make an edit. Dancindazed (talk) 19:20, 26 September 2011 (UTC)
 * Good edit, but it also made clear to me that the clause (which you turned into a stand-alone sentence) shouldn't be there at all. I can imagine a number of situations in which sabermetrical research would involve attendance, such as, for instance, to investigate the claim that a team plays better in front of larger home crowds. That would be a legitimate avenue of inquiry which would utilize industry statistics as data. Beyond My Ken (talk) 20:19, 26 September 2011 (UTC)

So tell us already:
Was Willie Mays faster than Mickey Mantle? JHobson3 (talk) 18:45, 30 November 2015 (UTC)

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