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.