Archive for August, 2005
Sorry for the slack posting lately. The school year starts this week, and I’ve been busy preparing and finishing up summer projects. Here’s some thing’s I’d like to write about, but don’t have much time. If you want to leave comments on these things please do.
- All-Baseball has two interviews with economist Andrew Zimbalist: Part 1, Part 2. I disagree with Zimbalist on two issues he discusses. 1) I think MLB’s monopoly status is slight and produces almost no dead-weight loss to society. 2) I think to say that the A’s success with pitching has little to do with sabermetric insights is incorrect. To fully explain my reasoning for this would take some time I don’t have, so I’m just going to have to drop some bombs and run.
- I think Adam LaRoche should consider catching. The bias against left-handers at catcher is there for good reasons: righties are better at keeping runners off of third and lefties with good arms become pitchers. Adam won’t pitch (and it’s probably too late in his career to change) and he’s got a gun. He’s too slow to play outfield, and his bat really isn’t good enough to play first. I think his strong arm could compensate for any deficiencies he has at being left-handed. And he would be a very good hitting catcher. If I were a manager, I’d be tempted to try it. Of course, the last things the Braves need is another catching prospect. Anyway, just a thought.
- Aaron Gleeman has an excellent article on the Braves over at THT.
What we really need, is for the amateurs to clear the floor.
— Bill James
What do you get when people actually listen to Bill James? Michael Schell’s book Baseball’s All-Time Best Sluggers: Adjusted Batting Performance from Strikeouts to Home Runs. Schell is certainly no amateur, he’s a professor of biostatistics at UNC and an example of what can happen when you design your own table-top baseball game as a child. I was nothing short of blown away by Schell’s book. This is serious sabermetrics. It’s complicated, but only because the complications are necessary to find the answers Schell is looking for. He does a magnificent job of making the case for the adjustments he chooses. If you are a bit wary of statistics, you probably won’t want to read about the minutia of the adjustments, but you don’t need to understand the statistical techniques to know why he’s doing what he’s doing. And trust me, if he was doing it wrong Princeton University Press wouldn’t be the publisher.
Schell begins by laying out his plan for the book. The end result is to compile rankings of the 100 greatest career and individual season “sluggers” in baseball history for hits, doubles, triples, doubles-plus-triples (DPT), home runs, runs, rbi, walks, strikeouts, stolen bases, OBP, SLG, and OPS. But, the end result of Schell’s analysis is the development of Event-Specific Batting Runs (ESBR) and Career Batter Rating (CBR), with positional adjustments, to generate the final rankings.
The adjustments that Schell makes are obvious to those familiar with “best ever” debates: seasonal variations, park effects, the talent pool of the leagues, and aging. However, the methods for making these adjustments are not so obvious and are the key to making this book an important contribution to sabermetrics. While the most simple transformations for comparing players across eras is a comparison to the mean, Schell also looks at the variance, skewness, and kurtosis of the events to compare hitters across playing conditions. The most technical tools Schell uses are piecewise linear regression (to evaluate playing eras) and multiple changepoint regression (for park effects). And both methods are clearly explained (just an explanation for interpretation not a technical explanation) in the appendices. One of the best features of the book is the tables of park effects by events for all ball parks in different eras. The park effects are not just for runs or home runs, but Schell breaks them out by offensive category — runs, batting average, DPT, doubles, triples, walks, strikeouts, and home runs by handedness of the batter are all included. The numbers for ever year don’t exist for all parks, but this is the most thorough record of these effects available. These tables alone justify purchasing the book.
The end result of all of this hard work is a group of tables to end the book. These last 80 pages present some answers to the “best ever” questions we’ve all asked. While this certainly won’t end these debates, it’s certainly a huge step in the right direction. In the conclusion, Schell even goes so far as to offer where his analysis could be improved. Schell has done a great service to the baseball analysis community, and those who are interested in sabermetrics ought to read this book. I will add that the book is more of an encyclopedia than a beach reader. It’s something you ought to keep close by while doing research, but it’s not something you want to consume cover to cover. I’ll admit that I haven’t read every word in it yet. Keep it on a bookshelf nearby, and when a question arises pick it up just to see what Schell has to say on the issue.
Yesterday, I went to the Mississippi Braves vs. Chattanooga Lookouts game. I’d never been to see the Lookouts in my 4 years in the area, but I finally decided it was time. It was more of a family trip than a baseball trip, and it was fun. The park is easy to get to in downtown Chattanooga. The park is small so there are no bad seats. In fact, the worst seats in the park might be the ones closest to the field that have no shade. It was very hot, which forced us to take our two-year-old home a little early. The park has a beautiful view from the stands as you can look out over the rolling landscape. Though there are lots of between-inning games for fans, the game was devoid of many things fans have come to expect at the ballpark. Was there even and announcer? I rarely heard anyone over the loudspeaker. Who is the new pitcher? Could someone tell me? And there was no video or audio piped in to the concession areas. Eh, but what do you expect? It is minor league baseball. However, it’s a nice venue, very kid-friendly, and I will go back again soon. The mascot, Looie, was very nice to my daughter even though she was a little frightened. She said, “Thanks, big Elmo,” because that’s kind of what he looks like.
Oh yeah, the game… I almost forgot. It was pretty bad as the Lookouts jumped out to a big lead. The M-Braves look awful. Of the Braves who played Wes Timmons is really the only player showing anything indicating he might play in the big leagues one day (Prado and Devine did not play). Blanco is supposed to be good, but he’ll need another season in AA — he had one of the worst throws to the plate I have ever seen, which I thought was going to go into the crowd halfway between third and home. Why is Onil Joseph on the 40-man? Can someone tell me? With the call-up of most of it’s good players (to AAA and Atlanta) the AA Braves are a little pathetic to watch.
With John Thomson and Mike Hampton set to come back this weekend, the Braves are going to have to make a few moves. Already, the Braves have announced that HoRam will be moving to the bullpen, which sends a strong message about his future. With so many good arms in the Atlanta system, and Ramirez not making the proper offerings to the DIPS gods, I don’t see him spending much more time with the team. A spot on the playoff roster is at stake here. If he can’t get it done out of the pen, I don’t think he will make the cut if everyone stays healthy.
Speaking of the pen, whose spot is HoRam going to take? There has been a lot of speculation regarding Davies and McBride being sent down. It could happen, especially if they want to give Davies starts, but I’m not so sure. The last time they sent Davies down they gave him a start or two off to get him some rest. The word from the broadcast booth has been that he’s been available out of the pen for the past two games. Sounds to me like he might be staying. And McBride has pitched well in his few appearances.
So, who will the odd man out be? I think it could be Jim Brower. He hasn’t been very good. He’s given up four homers for the Braves, three of them after the break. His FIP is 5.84. Though Brower is not awful, he’s just so easily replaceable and not really all that dependable. I think there is a better chance that McBride or Davies can offer solid relief down the stretch. If not, the Braves have time to find some other options within the organization. And even if he stays with the team, I don’t think he’ll make the playoff roster. So, I hope the Braves will give these guys a chance to get some major league work. I doubt they will do worse, and they have the potential to be much better.
Alright, let’s play a game. Jeff Francoeur is having what might be the greatest start for a rookie in the history of baseball. And though other players have started off hot, I think few have done as well with minor league stats as mediocre as Francoeur’s. Now, I’m not trying to knock him at all. The guy put up .275/.322/.487 in AA Mississippi, and those are very good numbers for a 21 year-old prospect. But, those are not numbers you would expect to translate to .419/.425/.802 as he approaches 100 plate appearances.
I’d like to see an over/under betting market on how he will end up on Tradesports, which Steven Levitt discusses here. However, this is just too minor a thing to start a market for. So, let’s have a contest, where our reputations will be the reward or punishment. It’s not perfect, but I think my former professor Tyler Cowen, who’s written quite a bit on the subject of approbation, would approve.
Here’s the contest. Predict whether Jeff Francoeur hits over/under .300 in his batting average for the 2005 regular season. Simply write in the comments over or under. Anonymous comments will be deleted, remember you have to put your reputation on the line.
Why .300? Well, I figure if Jeff hits .250 for the rest of the season, over which he’ll get about 150 more at-bats that would put him right about .300.
Here’s some information on Francoeur’s 2005 minor and major league performances.
I’ll start: Under.
I’m back from my vacation. I took a trip to the beach earlier in the summer, but that one didn’t take. I guess I knew I had too much work waiting for me when I got back. This trip was much more relaxing, and “I feel reborn, like a phoenix rising from Arizona,” as Frank Costanza would say. Kyle and John did some fantastic work while I was gone. I’m sure they’ll be willing to pop back in from time to time to share their ideas. I enjoyed reading my own blog for a change and wondering what would be posted. Good work guys. Here are a few random thoughts for the day.
- Strikeouts don’t cause power and power doesn’t necessarily cause strikeouts. We often observe power hitters striking out a lot because to succeed as a major league player with a propensity to whiff, you have to make up for it in other ways. Power is a very valuable asset to have. The correlation between Ks and HRs may just be a product of natural selection. Adam Dunn is good player despite his strikeouts, not because of them. However, if you think Dunn is not a good player because he strikes out you’re ignoring all the good things he does to make up for his deficiency. Does this mean Dunn should try to strike out less? I’m not sure. It may be that changing his approach to avoid strikeouts may harm his on-base and power abilities. Or, it could make him the best hitter in baseball history.
- Shonk over at Selling Waves, which for some reason is not on the blogroll — I’ll be fixing that, has an interesting take on the Larry Krueger/Felipe Alou situation.
- Stupid Rafael Palmeiro. What on earth was this guy thinking? Either someone slipped him something or he’s not very bright. I’m going with the latter. In my capacity as a teacher I have encountered many incidences of cheating. Almost every single one of them involved the party just being not so bright. My favorite incident was a “broken” arm that prevented the student from taking my test on its assigned day. The student apparently forgot about the excuse, because the individual showed up to class without the cast the next day and took notes with the “broken” arm. I’m still not sure what this student was trying to do, possibly hoping for a sympathy D-. Now, I’m sure that there are plenty of smart people who get away with cheating in life, but I suspect that most people who cheat in life are short a few IQ points. These are people who have the most to gain from cheating. So, maybe Palmeiro is just dim.
- Check out the latest addition to Baseball-Reference. Congrats to Sean and Sylvia!
Baseball statistics are usually used in one of two ways: analysis of past performance or predicting future performance. In either case, we often use them to analyze the decisions of the manager, the general manager, the owner, and anyone else related to the team. Along those lines, my motivation for tracking pitcher WPA stats was not only to know more about pitching, but also to know which pitchers should be used in certain situations. To that end, I have come up with a statistic that I call Usage Score. While the stat corresponds to specific players, it is actually a reflection of the manager’s tendencies with regard to those players.
(If you haven’t read my introductory article on WPA, you may want to now. Otherwise, this will be difficult to follow.)
The calculation for Usage Score (USG) is relatively simple, although getting to the right numbers to use can be quite a task. First, I take a player’s average total P and WPA per appearance. Next, I find the team’s averages in those categories (not including the player’s stats) during the time period that the player was on the team. With that data, I also have the player’s and team’s WPTP over that time period.
By taking the differences between the player and team averages in these stats, you can learn a few things. First, you know if a player is being used in higher-leverage situations than his teammates by comparing the P values. You also know if a player is doing a better overall job by comparing WPTP rates. Take a look at the Braves’ leaders in average total P and WPTP vs. team averages:
From this table, we might already be able to tell which players are not used at the right times, and we’re now getting close to the USG. Using the player’s WPTP and difference from team average P (WPTP +/- and P +/-), we can find out what the player’s WPA would be if he had been used in the average situation his team faced. Just multiply the player’s WPTP +/- by the team’s average P to find the player’s theoretical WPA +/-.
Now we have the two building blocks for USG: The player’s theoretical WPA +/- and his average total P +/-. The difference between the two is the usage score (I subtract P +/- from WPA +/- so that underused players are at the top). Here is the Braves’ USG leaderboard:
Theoretically, a manager should use his middle-of-the-pack reliever in situations close to his team’s average P. More crucial situations should go to above-team-average relievers, while garbage time goes to the team’s worst players. In the above leaderboard, you’ll notice that Macay McBride, Blaine Boyer, and John Foster are the top three most “under-used” current relievers, while Kolb and Farnsworth are “over-used.” Sample sizes are a problem with the current staff, since only Reitsma and Kolb have seen more than a handful of appearances, but you get the idea. It appears that Bobby Cox has done a decent job, aside from the anomaly of Dan Kolb, who was clearly not expected to perform so poorly.
I think USG can be very helpful, but there are a few problems with using this as a catch-all manager performance stat, beyond sample size issues. First, I only have data for the Braves, which means that I really have no idea how Cox is doing compared to other managers. All I can say is that he probably should have used John Foster a few times when he actually used Kolb.
Second, as JF said in his comment on Kyle’s article, you just can’t predict the leverage of future situations. You have to make decisions based on the current situation of your staff (things such as fatigue and perhaps hot and cold players) and only the current state of the game. If Cox brings in Chris Reitsma for a 3-2 game in the eighth, who’s to say that he won’t need someone to get Kyle Farnsworth out of a bases-loaded jam in a 3-3 ninth? Of course, the reverse could be true, with the Braves scoring 4 runs to put the game out of reach after Reitsma’s appearance. I don’t know if those scenarios average out, so we’d likely need a guinea pig manager to start bringing in the closer in these early-but-tight situations to see what ends up happening.
All of the stats I’m tracking are still in the early stages of their development. WPA analysis is not widespread, by any means, so it’s very difficult to say anything conclusively when looking from a broad perspective. Any and all comments and suggestions about my work are always welcome. You can visit my site by following JC’s link to “Advanced Pitching Stats for Relievers” on the left.
Just popping in from my vacation, where I’m typing while looking out over a South Carolina marsh. The SC coast is one of my favorite places on earth. The salty air is probably not great for my laptop, but the benefits are quite high.
For all you who gave Steven Levitt such a hard time, you will be happy to know that he’s put some money down on the A’s. You see, Levitt is interested in getting things right, not “being right” as any good social scientist should be.
On Saturday, I had the chance to see the Braves take on the Pirates in the second game of a four-game series at Turner Field. I only get to go about once a year because of the prices and the drive, so it’s always an exciting experience. What I’ll try to do in this review of the game is a WPA analysis of the flow of the game, similar to what Dave Studeman has done on occasion at THT.
The Teams and Starters
The Braves entered the game at 59-44, out in front of the rest of the NL East by four games after a mid-week sweep of the Nationals. The Braves have suffered through a slew of injuries and poor performances, playing in a division in which every team is over .500. They have started an entire minor league team at the major league level, and yet they are still the front-runners for an unprecedented fourteenth consecutive division title. They were riding a four-game win streak going into Saturday’s game, but they had to call up Kyle Davies from Richmond to start the game, thanks to Mike Hampton’s back injury. Davies was adequate at best in his earlier starting stint, with a very high 28% line drive rate, but he had only a 4.32 ERA. He still has a promising future, but he doesn’t appear to be quite ready.
The Pirates were 44-59 and headed in the opposite direction as the Braves. They were perceived to be sellers at the trade deadline, and that was the case, as they moved Matt Lawton to the Cubs for Jody Gerut on Sunday. Lawton was still the starting right fielder for Saturday’s game, though, and fellow trade-bait pieces Mark Redman and Jose Mesa were still his teammates. As it turned out, of course, the latter players would not be moved. Redman, in fact, was the Pirates’ starter for Saturday’s game. With a 3.99 ERA entering the game, he had been adequate, but that ERA has steadily increased as the season has progressed: 2.78 in April, 3.43 in May, 4.01 in June, and 6.00 going into his last July start. He likely played himself out of a trade to a contender with his poor performance, although I doubt that was intentional.
Davies started the game with a four-pitch walk to Chris Duffy, one of many Pirates prospects now on the major-league roster (which is sort of like the Braves, except that their regulars haven’t been as good). He then proceeded to pitch around the following batters, striking out Rob Mackowiak, but walking Matt Lawton with Jason Bay on deck. Entering the game, Bay’s .931 OPS made him the best hitter on either team not named Andruw Jones, and naturally, he homered after working a full count. Before they even had a chance to bat, the Braves’ win probability had been reduced to under 25% (.246). Davies entered damage-control mode and finished the inning without allowing more runs, although he did throw 36 pitches in doing so.
Both teams went quietly over the next inning, aside from a Chipper Jones double in the first, but there was an exciting moment in the bottom of the second inning when Julio Franco (a.k.a. Father Time) picked up his 2,500th career hit on a single up the middle. I’ve seen a few interesting things at Braves games, including a homer hit by John Smoltz, but that was one of the greatest moments I’ve been a part of. Franco has been such an unheralded player the past few years with the Braves, aside from the novelty of his age, so it was nice to see him recognized for his excellent career.
The Pirates went quietly again in the third, but the Braves made some noise in their half of the inning. Kelly Johnson walked to lead it off, but Kyle Davies failed to get down a good bunt, and Johnson was thrown out at second on the play. Davies ended up advancing around to third, but the inning ended on a Chipper Jones fly out, lowering the Braves’ win probability to .181.
Kyle Davies had settled down by this point, and he retired the Pirates in order in the fourth. In the bottom half, the Braves came roaring back on a two-run moon shot by Jeff Francoeur that increased the team’s win probability to .394. (Francoeur is a unique talent, but he has to learn how to take a walk if he wants pitchers to keep throwing him hittable pitches. I won’t be sold on him unless he keeps hitting .400 or starts showing some patience, at least for the immediate future. There’s no doubt he’s a star in the making, though.)
Davies pitched around a hit in the fifth, while Redman pitched around two. The Braves’ promising inning ended yet again at the hands of Chipper Jones, whose DP cost the Braves 17.4% in win probability. Their WP was actually .510 before the play, thanks to the run expectancy of the first and third, one out situation. The Pirates then went 1-2-3 in the sixth, but Davies’ time was limited because of his early-inning pitch count struggles.
The bottom of the sixth was the Braves biggest inning of the year, a seven-run outburst in which the first nine batters batted 1.000 because they had not one, but two sacrifice flies in the process. Francoeur doubled with Andruw Jones and Franco aboard, driving in them both. That hit was the largest single swing in win probability for the game, raising the Braves from .550 to .801. The next three batters all got hits, and Giles tripled in between the sacrifice flies by Furcal and Chipper Jones. Andruw Jones, who started off the inning with a single, flew out to Matt Lawton (who made all three outs in the inning) to finish it.
The Braves had the game all but locked up after that huge inning (WP of .983), so they brought in Blaine Boyer to pitch. After Davies had struck out eight in six innings of work, Boyer sought to add insult to injury by striking out the side in the seventh. Jeff Francoeur lined into a hard-luck double play with Franco at third, ending another threat in the Braves’ half of the inning.
Boyer hurt himself in the middle of Rob Mackowiak’s at-bat in the eighth, and Dan Kolb had to come out cold to relieve him. Kolb finished off a walk of Mackowiak and then gave up RBI singles to Lawton and Bay. Freddy Sanchez drove in another run on a ground ball before Jose Castillo ended the inning. At 9-6, the Braves were still likely to win (.974 WP), but Boyer and Kolb made it interesting, reducing the win probability to .933 after Bay’s single.
The Braves failed to score in the eighth, but it didn’t matter, because Bobby Cox brought in Reitsma for the ninth. In that situation, the win probability was .967, which raises the question of why Reitsma is coming in, especially since he worked three of the previous four games. We all know the answer (to get the save), but that doesn’t make it a good one. Before I dive too far into that argument, I’ll save it for my next article, which will be on reliever usage patterns. Anyhow, Reitsma sat down the Pirates 1-2-3 in the ninth for the cheap save.
Win Probability Graph and Summary
|Pirates Total||0.020||-0.505||-0.014||-0.500|||||Braves Total||0.520||-0.008||-0.012||0.500|
As you can see, there was one offensive star for each team. Bay’s 3-run blast was very important in the early going, and Francoeur’s huge and timely hits far outweighed the two double plays he hit into. The bottom 5 spots in the Pirates order went 0-for-21, which shows in the numbers above. On the other side, Chipper Jones was the only Brave who had a rough game at the plate. On the mound, Redman was clearly far worse than Davies, almost to the point that he lost the entire game by himself (that would be a WPA of -.500).
There were a few plays where I assigned credit to fielders, aside from errors by Furcal and Castillo. I gave Furcal a bit of extra credit for a terrific play he made in throwing out Mark Redman on a very hard hit grounder, and I gave Mackowiak some credit for turning two on the liner Francoeur hit at him. Other than that, the WPA allocation was straightforward.
I had a great time at the game, and if I had the time to do it, I’d love to do this sort of analysis on a regular basis. It would be interesting, at least, to see who the best WPA performers are on a larger scope. For now, we’ll have to leave that to the guys who get paid for it.
The save statistic has come a long way from its humble origins in The Sporting News’ books: over the past several years, it has become a lightning rod of controversy in the analytic baseball community. To hear Michael Lewis tell it, several general managers have been fleeced by Billy Beane because of the importance they assign to pitchers with lots of saves. Many productive work-hours have been lost to internet flame wars between the camp of folks who allege that the “closer mentality” is a fiction and those who point to Arthur Rhodes and Octavio Dotel while shouting, “Behold!” The save itself has come under attack; Joe Morgan even wrote a column assailing the save statistic itself; he notes the hypocrisy in giving equal credit to the pitcher who enters the inning with a three run lead and allows two to score before recording the third out and to the pitcher who saves a win from a bases-loaded, no-out jam. A final criticism, headlined by a series of columns by Steve Treder at the Hardball Times, alleges that ace relief pitchers are being misused by managers who focus on maximizing saves rather than team wins.
To better understand the save, I find it instructive to remember from whence it came. Jerome Holtzman, a Chicago sportswriter, created the statistic in 1960 to solve what he saw as a growing problem: the proper valuation of relief pitching. As he tells in this very instructive article:
I invented the first formula for saves in 1960, in my fourth season as a baseball beat writer. At that time there were only two stats to measure the effectiveness of a reliever: earned run average and the win-loss record. Neither was an appropriate measure of a reliever’s effectiveness.
The ERA wasn’t a good index because many of the runs scored off a reliever are charged to the previous pitcher; the reliever’s ERA should be at least one run less than a starter. The W-L record was equally meaningless; the reliever, particularly the closer, is supposed to protect a lead, not win the game.
Holtzman discusses how Elroy Face was acclaimed as a good relief pitcher for his 18 wins in relief despite the fact that he allowed the other team to tie or lead the game in 10 of those victories. Thus, the save statistic was born out of a desire to attribute credit where credit was due.
So, you might ask, what’s the problem? In two words: Tony LaRussa. Holtzman explains succinctly what happened:
… Instead of bringing in their best reliever when the game was on the line, in the seventh or eighth inning, which had been the practice in the past, [managers] saved him for the ninth. The late Dick Howser and Tony LaRussa were mostly responsible for this change in strategy.
In other words, managers would refuse to use their best reliever before the ninth inning, even when circumstances called for doing so.
In John’s enlightening article about advanced reliever statistics, he introduces the concept of leverage: roughly speaking, the relative importance of any given at-bat to the overall outcome of the game. That is, the outcome of an at-bat in the third inning of a 9-0 game is not nearly as important in terms of altering the probability of victory for either team as is the outcome of a bases-loaded at bat in the bottom of the ninth of a tie game. To think of it another way, leverage is the amount of “pressure” put on a reliever: when he enters the game with a big lead (or facing a big deficit), there is little pressure on him to perform. In a tie game, he faces lots of pressure. New statistics have been invented by smart people like TangoTiger and Dave Studeman to measure in exact terms the amount of pressure each reliever faces (leverage or “p”) and the success he has in those situations (expected wins added or WPA).
Treder and others argue that ace relief pitchers are not used properly because their managers use other inferior pitchers in “pressure” situations, when instead they should ignore the save and send in the closer. In essence, this argument says that closers are not used in enough high leverage situations. Thanks to the good people at Baseball Prospectus, this argument is easy to test. They publish a statistic (aptly titled “Leverage”, or LEV) which measures “the change in the probability of winning the game from scoring (or allowing) one additional run in the current game situation divided by the change in probability from scoring (or allowing) one run at the start of the game.” See their site for further explanation. Below is the 2005 leaderboard in leverage, with 15 IP minimum:
Rank NAME TEAM LG YEAR G IP LEV Closer? 1 F. Rodriguez ANA AL 2005 39 42.7 2.33 Yes 2 Bob Wickman CLE AL 2005 41 40 2.22 Yes 3 Ugueth Urbina DET AL 2005 25 27.3 2.19 Yes 4 Joe Nathan MIN AL 2005 44 43.7 2.18 Yes 5 T. Hoffman SDN NL 2005 38 36 2.09 Yes 6 Scot Shields ANA AL 2005 53 65.3 2.01 No  7 Chad Cordero WAS NL 2005 54 57.7 2.01 Yes 8 Jose Mesa PIT NL 2005 37 39 1.99 Yes 9 D. Hermanson CHA AL 2005 38 40 1.97 Yes 10 Y. Brazoban LAN NL 2005 47 44.3 1.97 Yes 11 Akinori Otsuka SDN NL 2005 44 45 1.92 No 12 Juan Rincon MIN AL 2005 46 47.7 1.88 No 13 Octavio Dotel OAK AL 2005 15 15.3 1.87 Yes 14 J. Isringhausen SLN NL 2005 40 37.3 1.86 Yes 15 Eddie Guardado SEA AL 2005 36 36 1.8 Yes 16 Glendon Rusch CHN NL 2005 24 29 1.79 No 17 Brandon Lyon ARI NL 2005 18 18.3 1.76 Yes 18 Troy Percival DET AL 2005 26 25 1.74 No  19 Latroy Hawkins CHN NL 2005 21 19 1.69 No  20 Luis Ayala WAS NL 2005 56 59 1.66 No
 Urbina was used as Detroit’s closer when Troy Percival was injured; he recorded 9 saves before being traded.
 Shields was used as Anaheim’s closer for a few weeks when Francisco Rodriguez was injured.
 Hawkins was briefly used as the Cubs’ closer before being moved to the setup role and eventually being traded.
As you can see, a majority of the names on this list (13) were their team’s primary closer while healthy. However, several teams have two pitchers on this list: Anaheim (K-Rod and Scot Shields), San Diego (Hoffman and Otsuka), Washington (Cordero and Ayala), Minnesota (Nathan and Rincon), and Detroit (Urbina and Percival). In every instance except Detroit (which is an exception because of Percival’s injury problems), the team’s closer was used in higher leverage situations. Let’s look at the 2004 list (minimum 30 IP):
Rank NAME TEAM LG YEAR G IP LEV Closer? 1 Trevor Hoffman SDN NL 2004 55 54.7 2.17 Yes 2 Eric Gagne LAN NL 2004 70 82.3 2.11 Yes 3 Joe Nathan MIN AL 2004 73 72.3 2.06 Yes 4 Danny Kolb MIL NL 2004 64 57.3 1.99 Yes 5 Jose Jimenez CLE AL 2004 31 36.3 1.96 No 6 F. Cordero TEX AL 2004 67 71.7 1.95 Yes 7 Eddie Guardado SEA AL 2004 41 45.3 1.89 Yes 8 Greg Aquino ARI NL 2004 34 35.3 1.86 Yes 9 Octavio Dotel OAK AL 2004 45 50.7 1.84 Yes 10 Mariano Rivera NYA AL 2004 74 78.7 1.83 Yes 11 Todd Jones CIN NL 2004 51 57 1.82 No 12 Arthur Rhodes OAK AL 2004 37 38.7 1.79 No  13 Rodrigo Lopez BAL AL 2004 14 31.7 1.74 No 14 Tim Worrell PHI NL 2004 77 78.3 1.7 No 15 R. Betancourt CLE AL 2004 68 66.7 1.69 No 16 Troy Percival ANA AL 2004 52 49.7 1.69 Yes 17 A. Benitez FLO NL 2004 64 69.7 1.68 Yes 18 John Smoltz ATL NL 2004 73 81.7 1.68 Yes 19 Tom Gordon NYA AL 2004 80 89.7 1.67 No 20 Jorge Julio BAL AL 2004 65 69 1.66 Yes
 Jimenez spent part of the year as a closer as the Indians desperately tried to find someone who didn’t suck in their bullpen.
 Rhodes began the season as closer, but was moved out of the role when Oakland traded for Octavio Dotel.
Again, thirteen players on this list were their team’s primary closer, two others were used in that role for part of the season, and Tom Gordon was used in lower-leverage situations than Mariano Rivera. In general, closers seem to have been used in more high-leverage situations this year than last year: four pitchers on the 2004 list had a higher Leverage value than their team’s closer, while no one on the 2005 list meets that criteria.
There are a few important caveats to take away from this brief look at leverage. First of all, the above lists do not measure success; just because a pitcher was used in high-leverage situations doesn’t mean he was any good (and indeed, Jose Jimenez wasn’t). Second, just because a closer shows up on this list doesn’t mean he was used optimally. Further research can be done into the situations when a closer could have been used and compare his “ideal” leverage with actual leverage. Finally, managers are not always successfully identifying their best relievers, so using the closer in high-leverage situations might be sub-optimal (like Jorge Julio and BJ Ryan last year).
For all the grief the save statistic receives, it still does what it was designed to do: measures an aspect of reliever performance that W/L record and ERA do not capture. And despite what may have happened in the past, managers seem to be successful at deploying who they perceive as their best relievers in crucial situations.
As a closing note, I’d like to thank JC for giving me the opportunity to fill in for him while he’s away. It’s an honor and a privilege. If I can come up with anything a tenth as interesting as what he writes daily, I’ll be lucky.