A lot of great stuff this week online from a baseball stat and sabermetric perspective. I don’t want to take too much time building it up, so I will just get right into the details.

The Great Clutch Project

I mentioned this a few weeks ago, concerning Tom Tango asking fans to join him in a battle in the clutch debate where he will pit his “good” hitters against the fans’ choice for “clutch hitters” to see if there really is a way people can see and perceive clutch. The stats he is using are his Leverage Index scores and wOBA (weighted on base average), so if you are not familiar with those, read up on them. You can find the summary of the project here, and Fangraphs will be running the season tally here for 2008.

Never thought I would see a Ginger/Mary-Anne and clutch/non-clutch analogy used, but I guess nothing should surprise me anymore.

Hardball Times OF Arms

John Walsh of THT reveals his new defensive metric to measure OF arms, something that has always been missing and that is sorely needed in the defense discussion that has escalated in the past few years. You can search by year on their stats page here, and there is a lengthy description of the methodology at this link. The stats for the OF arms goes back to 2004.

Richard Justice’s war with the stat guys

Local sports writer for the Houston Chronicle has the stats world up in arms from his reaction to a post by Mitchel Lichtman on Justice’s blog piece this week about bunting and how it is always a bad idea. Apparently, Justice has long been a target of some bloggers for his inability to look past emotion and personal feelings and look at the numbers. And the blogosphere just can’t get enough of all of this. And all of this from a couple of sentences about how bunting is always bad in the situation with which the Astros were faced.

For the record, I fall somewhere in the middle of what Lichtman and what Keith Law propose (you need to read all the threads to understand where that is). A manager has to make a yes/no decision in that moment, but his job should be to be as prepared as he possibly can with all the available data that will help him make an educated decision. The ones that are too close to call? Well, that’s why a managers are paid the way they are.

Lineup Analysis

This is not a new tool by any means, but something I have been messing around with this week that I recommend. Baseball Musings hosts a page that has a Lineup Analyzer put together by Morong, Arneson, and Armburst that allows you to put in any nine players with their OBP and SLG and it will construct the ideal lineup based on those numbers, and their calculated comparison and analysis of the two.

Here is the page, use it on your favorite team for this year or any year.

Using a relatively new tool on BaseballReference.com known as the Batting Order Outcomes, I thought it might be fun to go back and look at last season and construct the ultimate lineup, spots 1-8, using each team’s production in each of those spots as our data.

The way this page works is you can put in any team and any spot in the lineup (1-9) and BR will pull up a page with stats on how that team performed in that season at that spot in the lineup, with all PA included throughout the season.

So, I can quickly go back and see that in 1972, The Boston Red Sox had an OPS of .625 in the 7th spot, with the famous Doug Griffin getting the majority of the plate appearances that year.

Using OPS as our gauge, I will lay out the ultimate 2007 batting order from across the Majors. While the batting order page has incredible splits and breakouts of stats per month, player, inning, relative score, and more, the stats used are pretty basic, so OPS is probably our best bet for this exercise.

Starting with the leadoff position, here is the best from each spot in 2007, with a couple of my random comments associated with each:

1. Florida Marlins - .897 OPS

This one makes sense especially when you consider that Hanley Ramirez was given 706 of the 780 plate appearances for the Marlins in the leadoff spot in ‘07. May and June were actually not kind to Ramirez and the Marlins’ leadoff spot; the OPS totals for those two months in that spot were .738 and .694, respectively. But the next three months had totals of 1.094, .875 and .944 - so he certainly finished strong. In comparison, Ramirez’s two counterparts, Rollins in Philly and Reyes in NY, both contributed to .869 and .772 totals for their teams. Ramirez is expected to move to third in the order in 2008, so don’t look for the Fish to repeat in this spot.

2. St Louis Cardinals - .870 OPS

This one mildly surprised me. No Derek Jeter, Kevin Youkilis, Placido Polanco, or even Hunter Pence took this spot. Rather, the combination of Chris Duncan and Rick Ankiel give the Cardinals the top spot. Certainly helping the cause, Ankiel slugged .603 batting second. Also contributing to the solid .870 number were the OPS numbers by Scott Speizio and Skip Schmaker, who both had an OPS over 1.000 in 131 total plate appearances.

3. Boston Red Sox - 1.034 OPS

No surprises here. David Ortiz ate up 89% of the 751 total plate appearances in the third spot. I have heard some people say that Ortiz had a down year last year because his homeruns and RBI were down from the previous two seasons, but that argument is truly ridiculous. His batting average, OBP, OPS+, Runs Created, and Runs Above Replacement were all the best of his career. His 52 doubles made up for “only” 35 HRs - a number which will likely trend upward in 2008. And in September, during the playoff push, Ortiz’s OPS was a mere 1.355.

4. New York Yankees - 1.069 OPS

Again, no surprises at this spot. Of 744 2007 plate appearances in the #4 spot, A-Rod had 700 of them, with OPS of 1.081. In the few times someone else actually hit in this spot, Jorge Posada, Miguel Cairo and Hideki Matsui all had an OPS of at least 1.000 as well. And quite possibly even more impressive, the Yankees who had the number four spot come up with RISP 243 times, totaled an OPS of 1.127.

5. Toronto Blue Jays - .939 OPS

I probably could have given you a dozen guesses to this one, and you wouldn’t have said the Blue Jays. But there they are - with big Frank Thomas leading the way with his .935 OPS. Actually, while Thomas had the most PAs in that spot, he only accounted for about a third of the total plate appearances. Some of the other notable names hitting in that spot: Aaron Hill, Troy Glaus and Matt Stairs totaled OPS scores of .946, 1.145 and 1.003, respectively. All of these numbers represent significant increases over their seasonal totals.

6. Colorado Rockies - .908 OPS

This spot makes sense as well, with Brad Hawpe demanding 73% of the PAs for the Rockies in 2007. And while Hawpe’s OPS in 2007 in that spot was an incredible .918, it is severely overshadowed by Ryan Spilborghs who had an OPS of 1.212 over 74 PAs in the six hole. In another interesting note, the Rockies only had one month all season (April) where they did not slug at least .500 from the 6th spot in the lineup. Perhaps not surprisingly, that was the month they had a losing record.

7. Philadelphia Phillies - .850 OPS

This spot in the Phillies’ lineup was distributed pretty evenly amongst Abraham Nunez, Jayson Werth, Wes Helms, Greg Dobbs, and Aaron Rowand. Except for Nunez, all other batters had an OPS of at least .847 in the seven spot, with Rowand leading the way a 1.070 over 87 plate appearances. One entertaining and interesting note here looks at when throughout the course of the game the Phillies really produced in the 7th spot. In the 1st-6th innings, the Phillies had an OPS of .885 in the seventh spot, but that number drops to .783 from the 7th-9th innings.

8. Pittsburgh Pirates - .800 OPS

I could probably give you 25 guesses and you would not have picked the Pirates in this spot. I certainly thought it would be Robinson Cano or some other powerhouse offense, not the team that was 12th in the National League in runs scored. But with Jack Wilson and his .825 OPS getting exactly half of the plate appearances, the Cesar Izturis’s, Jose Castillos and Jose Bautistas of the world could not drag down the total number below .800. The second half of 2007 is what tells the story for the Pirates earning this spot - as a team the OPS in the 8th spot after the All-Star Break was an amazing .899.

In an exercise like this, the Magglio Ordonezes, Matt Hollidays and Miguel Cabreras unfortunately get stuck on the outside. But I certainly think that a team composed of this lineup would score an astonishing amount of runs. But just how many? Well, using the basic Runs Created formula, we can come up with a good guess as to just how many.

Formula: ((H+BB)*(1B+(2*2B)+(3*3B)+(4*HR)))/(AB+BB)

Total estimated Runs Created: 1024

In context, the team with the most runs in 2007 were the Yankees with 968 and the average across MLB was 777.

So in other words, we have quite an offensive machine on our hands, even including batters from the Pirates, Cardinals and Blue Jays.

I have written a short piece for the Spring Training 2008 website hosted by Blogs by Fans about the Astros. You can check it out here, and also click on any of the team logos for a preview of rosters, rotations, and key spring training battles. Spend a few minutes there if you have a chance.

Also, check out any of the previous five posts on offseason MLB transactions from the American League and two of the three NL divisions. The NL West will round out the series later this week.

While I sort through all of the National League transactions since October and also wait for a few pending AL things to be completed, I thought I would quickly throw out a new round of websites that I recommend whether you just have some time to kill, research to do, or random things you want to look up.

Most of these I have found linked on other sites or through perusing other pages, so I will reference those when applicable.

Baseboogle - Google for baseball? Exactly. Baseboogle is a search engine run by Google that uses a special set of selection criteria and filters searches through a vast list of baseball related websites and documents. My search for simply “clutch” yields more than five pages of links to articles ranging from who is the most clutch, to dismissing clutch hitting, to clutch projects, to “is David Ortiz a clutch hitter?” Also helpful is a list on the right side of the page that lists all of the sites that Baseboogle pulls from when it searches. You can recommend sites to be added so that the directory of pages it searches from becomes more extensive. You can find this site at www.baseboogle.com. I found this site from a post on The Book blog by Tom Tango.
Cot’s Baseball Contracts - I can’t tell you how many times I have wanted exactly this type of information at my fingertips. This site has a page for each team and lists all players, the manager and what contracts they have, what their yearly salary is, what their bonuses are, no-trade clause or not, etc. This is also a great resource for arbitration eligible players, 2008 and 2009 free agents, transaction lists, and other interesting baseball links. Just a great site to look up your favorite team, player, or whatever. You can find it at www.mlbcontracts.blogspot.com/. This site is always used in Pizza Cutter’s sabermetric year in review series for each MLB team currently running on MVN’s Statistically Speaking.

Sabermetric Studies - A useful and well-organized archive of all things having to do with sabermetric analysis. There are pages for each area of discussion and research such as fielding, run estimation, DIPS, clutch hitting, and many more. Each page has multiple links to any study or analysis that has been done on the subject, and the most helpful part is that he mentions which of the articles are available only to those who have subscriptions to respective sites. Also available on this site is a very comprehensive list of sabermetric and other baseball reference sites. This can be found at www.sabermetricstudies.com. This link also came from a Tom Tango post on The Book blog.

Beyond the Box Score - A site much like this one, Beyond the Box Score is a comprehensive look at stats, teams, players, and trends going a little bit deeper than the average analysis. The articles and analysis are always concise, easy to understand, and extremely helpful for understanding teams and their trends. RJ Anderson, the author, also blogs for the Devil Rays and was formerly at Deadspin.com. BTBS also has one of the more extensive blogrolls and link lists that you can find anywhere. You can find this site at www.beyondtheboxscore.com.

There you go, just some more filler for you in your free time desperately counting down the days until baseball season starts again.

If I hear one more person talk or write about how clutch-hitting ability or the perception of clutch hitting is the most debated and written about statistical anomaly in baseball, I might start going a little crazy. So much has been written and discussed on this topic over the past 20 years that it is getting somewhat ridiculous these days. There is the side that believes certain hitters, whether they are typically good or not-so-good hitters, can somehow routinely deliver in the most crucial of circumstances, and then there is the side that believes it is just about perception, and the people who are commonly referred to as “clutch hitters” are only defined as such because they have performed well a few times maybe on the biggest of stages and they stick out in our minds as having this unique ability.

But finally, two different sites are asking people to put their money where their mouths are when it comes to clutchiness (only one involves actual money, but still…).

The famous sabermetric blogger Tom Tango, aka Tangotiger, is challenging readers, clutch advocates, and the like to a simple contest to see if clutch hitting really can be predicted or continued after it is recognized. In this post on his website, Tango challenges the following:

He wants fans/readers/critics or whomever to pick one guy from “their team” who they feel is the most clutch, assuming they believe that sort of thing. The one guy they would want to have come up in the most crucial, pressure-filled situations and then nominate them for their side. Tango will then pick who he thinks is the best hitter from that same team to compare at the end of the season.

Recognizing that some teams will have one player represent both sides (i.e. the Cardinals with Albert Pujols), the thought is that if that happens he will use the next most requested clutch hitter and who he perceives to be the next best hitter on the team. And this will go on down the line until there is a difference in who the readers pick and who Tango picks. Once this is done, you will be comparing 30 “clutch” hitters to 30 good hitters and Tango is predicting that his hitters will come out on top in the clutch situations.

How will he measure it? A while back Tango invented a measurement tool for in-game situations called Leverage Index. Essentially, it takes each moment in a game, a batter’s at-bat or a pitcher’s confrontation with that hitter, and places it in the context of the game. As the game gets closer to the end, the LI goes up for the hitter or pitcher because you have less time to put your team ahead, tie the score, hold the lead, etc. At the beginning of a game when there is no score, there may be an LI of 1.0 or lower per situation. A batter coming up in the 9th with a tie score could have an LI of 10.0 or so. So games that are blowouts by the 8th or 9th inning would have low LI scores for each situation, but tied games that progress into the 6th, 7th, 8th, and 9th innings would have increasingly higher LI scores.

Tango proposes that we compare the plate appearances with the 50 highest LI scores for each player that is chosen for the project. So you would end up comparing 1500 plate appearances for the “clutch” side to 1500 plate appearances for the “Tango” side. At the end of the season, he will look at the aggregated lines of the two groups to see which performed better in their most crucial situations.

He believes if the players actually chosen as clutch hitters do perform better in those situations, there will be some sort of statistical significance separating the two groups. Not to spoil the surprise, but he is not expecting that separation to be there.

In a related story inspired by Tango’s challenge, blogger Phil Birnbaum has laid out his own challenge to clutch advocates in this post on his website. His project is a little more risky on his part and actually involves money changing hands. The details look like this:

Birnbaum is not proposing to compare clutch hitters to other good hitters, but rather perceived clutch hitters to proposed choke hitters - those who absolutely fail in pressure situations. He challenges readers to pick any number of clutch and choke hitters; one vs. one, 30 vs. 30, 100 vs. 100, whatever. And he has finally settled on odds for the bet - 2:3. So he is proposing to every bettor whose clutch players out-perform the choke hitters, he will pay them $10, but if your choke hitters out-perform the clutch hitters, you have to pay Birnbaum $15. The reason he does not offer 1:1 odds is because he states that if you accept those odds, you are basically saying whether or not a player is clutch or not is essentially “a coin flip”, and this bet is supposed to attract those who believe clutch hitting exists.

If you accept this bet, you can define the players, you can define the amount of money, you can define the metric used to measure the players (as long as it revolves around batting average, such as BA in close and late, or LIPS), and you can control your sample size. Hitters suggested with obviously different skill levels (someone wanted to use Ortiz vs. Kevin Millar) will be judged on clutch differentials from seasonal numbers and not overall performance in the defined situations.

What he wants to see is if there is anyone out there who believes with a there is at least a 60% probability (hence the 2:3 odds) that you can predict hitters who will perform extraordinarily in the clutch. Some have accepted and some have declined, but there has definitely been some action on this post. You can also make the bet for charity, with the loser paying the amount to the charity of the winner’s choice. Email Phil Birnbaum from his website, http://sabermetricresearch.blogspot.com/, if you want to take part.

As you know, clutch is a very tricky thing. It has been shown to have patterns across seasons but not necessarily across careers, and every new study that comes out seems to contradict or challenge the rest. And you have so many competing ways to measure it, that it all gets lost in the shuffle anyway. Perhaps, at least for 2008, these two projects will use some real-life examples to put some of the issue to rest. Until it all comes up again next year, that is….

As of today, I will also be blogging about the Astros on www.fangraphs.com. I wrote about Fangraphs a few weeks ago as one of my obsessions and favorite places to play around online, and I highly recommend you check it out; not just the Astros page, but the whole site.

The Astros blog (done from the Win Probability Added perspective) can be found at http://www.fangraphs.com/astros/. Bookmark it and read it when you can.

As of now, I plan to try and post an entry after each series to analyze how things shook out for the ‘Stros and how well they performed in the situations that would have either won or lost them the games. My plan is to post the first of those a day or so after the Rockies series is over.

If you are not familiar with Win Probablity or Leverage Index, don’t worry! Click on this link to the representative Cardinals blog on Fangraphs and scroll down until you see “What is WPA?” on the right side. Erik, the blogger, has linked to a number of great articles and references you can review for more information on WPA and LI.

So check it out whenever you can. I will still be posting on this site at the same pace (hopefully), but will make this one more about baseball in general and the Fangraphs blog about the Astros.

Ryan

In my never-ending attempt to fill all of your free time by suggesting more and more unusual baseball stat sites, I have found one that is sure to suck you in for an extended period of time.

If you love homeruns, then www.hittrackeronline.com is the site for you. Never before has so much information about current and past homeruns existed in one place.

This site keeps numbers on every homerun hit this season and each season since 2005. Some of the more interesting things you can find here are the longest and shortest homeruns of the season, who has the longest average distance of their homeruns this year (a surprise to me, by the way - it’s a Dodger as of today), who leads the league in No Doubt homeruns, Just Enough homeruns, and Lucky homeruns. And all of this can be sorted by each team or each league.

You can also get into more detailed information such as the bat speed of all homeruns, the elevated angle of each homerun, and the apex of each homerun. So all of you physics nerds/baseball fans, this is definitely the site for you.

And then, once you are done sorting through all of that, you can switch from Hitters to Pitchers to see who has done all of the same things, given up the most HR, given up the most No Doubt HR, who has given up the longest HRs this year, etc.

Truly, this site is a time-waster to the power of 10. But one that I love.

_____________

Coming in a couple of days: Looking at the debate concerning Adam Everett. Is he currently worth leaving in the lineup, or should he be benched?

If you are interested in knowing the down and dirty details of your favorite team’s performance this year, I suggest you take a look at a new website, www.madstatter.com. If stats such as scoring distribution, runs for and against, scoring margins, and the like are your thing, then this is the site for you.

For example, in just a few clicks, I can tell you the Astros averaged 4.13 runs per game in April and are only scoring 3.50 runs so far in May. At least that’s better than the Dodgers or White Sox, who are both under 2 runs a game.  Also, the Astros average 6 runs per game on Thursday and Saturday, but no more than 4.25 on any other day of the week. Hmmm, and today they scored 13. Interesting.

Also, check out the scoring distribution page where you can see what scores have come up the most often this season. I wonder why the most runs scored in one game (one team scored 16, another team scored 15) so far this season have both been by visiting teams.

All of this data is sortable and easy to read. You can also capture the html for a graphic of your favorite team for your own website that automatically updates stats like record, winning percentage, runs for, and runs against.

I have also linked it to the blogroll, so check it out when you get a chance. You’ll enjoy it.

You can go online here anytime thru June 28 and vote for who YOU (the expert) think should start the All-Star game at AT&T Park in San Francisco on July 10. But, this link being up after two weeks of the season is completed bugged me a little. Some teams have missed four or five games due to weather, some players haven’t come off the DL yet to start the year, some have just gone on the DL (sorry fantasy owners who have Kendrick, Glaus, Ryan, and possibly Howard), some perennial all-stars have yet to get going (wherefore art thou Sir Lance Berkman?).

But, MLB says we have to start voting now, so why not take a look at players after two weeks? Here are (in my opinion) the starting lineups for the AL and NL  if you voted for the best players on April 19:

American League:

1B - Ty Wigginton
2B - Ian Kinsler
SS - Carlos Guillen
3B - Alex Rodriguez
C - Jorge Posada or Pudge Rodriguez
OF - David DeJesus
OF - Curtis Granderson
OF - Grady Sizemore
SP - Josh Beckett, Ramon Ortiz
RP -  Huston Street, Todd Jones

General thoughts about this lineup: The AL team probably has about half of the spots filled with players who will actually be there in July. A-Rod, Kinsler (what other AL 2B do you want right now?), the catchers, and Sizemore are all legitimate. But do you really expect to see Wigginton, DeJesus, Granderson, Ortiz or Jones in San Francisco? Beckett and Street are wild cards, and could definitley make it there. Beckett has been solid, but his past has been a bit blistery (to steal a phrase from Rob Neyer), and Street is definitley Streeky. I guess if you loaded the top of the lineup with Sizemore, Kinsler, A-Rod and Pudge, you might just do alright.

National League:

1B - Derrek Lee
2B - Orlando Hudson
SS - Jimmy Rollins
3B - Miguel Cabrera
C - Russell Martin
OF - Carlos Lee
OF - Carlos Beltran
OF - Eric Byrnes
SP - Roy Oswalt, Rich Hill
RP - Bob Wickman, Jose Valverde

General thoughts about this lineup: Also some good players here as well. Cabrera, Rollins, Lee, Beltran and Oswalt are studs and will be there in three months. Wild cards here include Lee (who has no homers but wins by default due to Pujols, Howard and Berkman stinking - would you rather have Dmitri Young or Nomar?), Martin, and Rich Hill, who looks dominant early on. The Diamondback Duo will surely slow down off their paces, and I have no interest in having Wickman or Valverde close out a game for me that decides whether I get home-field advantage in the World Series.

Listen, I love the All-Star game, it is a lot of fun. I have been to one and it is just intense enough with all of the great plays and players to make it more entertaining than your normal game. Take last year for example. That epic matchup between Troy Glaus and Derrick Turnbow was amazing.

Honestly, I don’t care who is voted in to start the All-Star Game. It is a game for the fans and always has been. But if you are going to stake home-field to a game where Mark Redman and David Eckstein are picked to participate, something needs to be changed. World Series home-field is something that would have affected six players in last year’s All-Star game if the Yankees and Mets would have made it (a real possibility), so you can’t take it lightly.

If you are going to involve the fans, keep it for the fans. That way, everyone picked can play, there is no intrinsic value, and it can return to the spectacle it once was for kids and adults alike. What can we do? What needs to be changed?

One of my favorite places to kill some time when the wife lets me is a site that has been around for a while called Fan Graphs. Fan Graphs is stocked full with stats and projections and blog entries and searchable tools, but the best part about the site is the statistic they utilize called Win Probability. They use Win Probability to track every MLB game live, so you can go see at any point of a given game what the two team’s win and loss probabilities are in real time.

As I type this on April 12, there is one game going on between the Indians and Angels, and it is scoreless in the 4th inning. The Angels have two men on, so their Win Probability, being the away team, is roughly 60%. If they score, their probability will increase and continue to increase as the game goes on if they are in the lead. If they fail to score, the probability will go back down to about 50%.

Another feature shows the players with the highest Win Probability contribution and the players with the lowest for any given game. So basically, you have a statistical list of who helped most and who helped least in the team’s pursuit of a win that day.

Here is an example. Think back to that fateful night on April 2 when the Astros faced the Pirates. The Astros had a 2-1 lead with two outs in the ninth; needless to say, the Astros’ Win Probability was very high. How high? Here is the graph:

As you can see, the Nate McClouth homerun in the 8th only improved the Pirates’ chances of winning to about 20%. When Xavier Nady came up in the 9th inning with two outs, the Astros’ Win Probability stood at about 95%. Interestingly, after the homerun, Houston’s WP still stood at 60% - this statistic factors in game situations like inning, home team, lineup, etc. Of course, when Jason Bay homered, it dropped to about 10%.

Another interesting caveat to all graphs is the Leverage Index at the bottom where they have graphed higher bars on the bar charts for more critical situations in the game.

Here are the highs a lows for Astros’ player’s WPA for that same game:

PLAYER WPA
Roy Oswalt .373
Luke Scott .137
Dan Wheeler .059

Chad Qualls -.403
Carlos Lee -.212
Brad Lidge -.188

So, actually two players contributed more to the loss than Lidge. Qualls, obviously, for giving up the 10th inning homer, and Lee. Remember him going 0-4 and grounding into two double plays?

Again, I urge you to proceed with caution, because this site is highly addictive. As always, if there are any graphs you would like to me to look up for certain games (back through 2002), I would be happy to do it. Just leave me a comment.