One of the main reasons I got involved with sabermetrics was to show fans intimidated by statistical analysis that not all effective evaluative methods consist of complex mathematical formulas. My favorite statistics are ones like FIP, wOBA, and EqA: better indicators of skill and performance but scaled to look similar to the more commonly accepted barometers. In using similar scales more of a chance exists for widespread acceptance.

Through surveys I found that a major reason fans shy away from better evaluative methods is that they are unfamiliar with the baselines. They don’t necessarily know what a good VORP is, or a good WPA; however, they definitely know what constitutes a good or bad ERA or batting average.

One of these stats not mentioned too much is called “Fan Save Value,” and it was created by analyst Ari Kaplan while working for the Orioles in 1990. Essentially, as described in the book Baseball Hacks by Joseph Adler, FSV measures the difficulty level of each save by taking into account the lead with which the closer enters as well as the number of outs he must record to secure a win for his team. When all of the results are added together we are left with a number similar to the saves total but more indicative of how hard a closer had to work.

The formula for FSV is (X/Y)/2, where X=the amount of outs to record and Y=the lead of his team. For instance, recording a one-inning save with a two-run lead would result in an FSV of 0.75; 3 outs divided by 2 runs ahead, then divided by 2. Using this statistic I decided to look at the current saves leaders and determine how hard each has had to work:

Francisco Rodriguez, LAA: 12 saves, 11.3 FSV
George Sherrill, Bal: 11 saves, 7.6 FSV
Joe Nathan, Min: 10 saves, 10.8 FSV
Jonathan Papelbon, Bos: 8 saves, 10.3 FSV
Mariano Rivera, NYY: 8 saves, 9.8 FSV
Huston Street, Oak: 8 saves, 8.3 FSV

Brian Wilson, SF: 10 saves, 10.5 FSV
Eric Gagne, Mil: 9 saves, 8.0 FSV
Jason Isringhausen, StL: 9 saves, 6.5 FSV
Brandon Lyon, Ari: 9 saves, 9.5 FSV
Brad Lidge, Phi: 7 saves, 7.5 FSV
Jon Rauch, Was: 7 saves, 6.1 FSV

The saves leader in each league remains on top when using FSV but the rest of the leaderboard shifts. The biggest dropoffs come from Isringhausen and Sherrill: Both of these pitchers have entered save situations in which their teams led by large margins and/or recorded a couple of 0.2 IP saves.

Papelbon, on the other hand, has pitched more than one inning in a few of his saves. Since the overall result looks similar to the saves total, and saves are commonly used as an end-all when evaluating closers, the FSV is an easy to use and better evaluative tool because it adds context to a normally context-free statistic.

Following an Alex Rios lineout and an Aaron Hill strikeout, Mark Buehrle induced a grounder to third off the bat of Scott Rolen that should have ended the inning. A throwing error, ground-rule double, and single up the middle later, Buehrle found himself the victim of two unearned runs. He struck out Lyle Overbay to end the inning but the Blue Jays ultimately had all the run support they would need.

Despite posting a complete game line of 8 IP, 5 H, 0 ER, 0 BB, 7 K, Buehrle suffered the loss; the committee of Shaun Marcum, Jeremy Accardo, Jesse Carlson, Shawn Camp, and Scott Downs collaborated on a two-hit shutout.

Buehrle threw exactly 100 pitches and 74 of them were strikes. Ironically, ten of those 26 balls came on the first pitch to batters. Here is his pitch breakdown:

• Fastball: 45, 87.8 mph
• Curve: 7, 72.4 mph
• Slider: 27, 83.5 mph
• Changeup: 21, 79.4 mph

Nobody swung and missed at his fastball though his slider proved difficult to make solid contact with; the White Sox fouled off nine of them and flat out missed six. Here are location charts showing where he threw his slider to righties and lefties:

While he tried to stay inside with the slider when facing lefties, he challenged righties in the zone more often with this offspeed pitch.

Facing a total of 29 batters, Buehrle threw a first pitch strike 16 times; ten of the first pitches were balls and another three were put in play. Unlike Matt Cain, who essentially throws a fastball to start every hitter, Buehrle started the White Sox offense with 18 fastballs and 11 breaking balls. With an 0-1 count Buehrle threw just two fastballs out of his 16 total pitches; with a 1-2 count he primarily threw changeups; on a 3-2 count he did not rely on his fastball, throwing two sliders and a changeup out of five pitches. Normally I would show this data in graphical or chart form but, when dealing with just one start, it would suggest patterns and tendencies that just cannot be determined with such a small sample.

Buehrle did not have an easily identifiable “out-pitch” last night as, with two strikes, he threw 13 fastballs, 2 curves, 7 sliders, and 8 changeups.

The aspect of pitch data that fascinates me most right now is sequencing: What does a pitcher throw after a certain pitch? Buehrle threw very few pitches to lefties but, against righties it becomes clear that he successfully mixed up his pitches.

When throwing his changeup to righties he definitely relied on additional offspeed pitches to accompany it rather than mixing speeds by throwing a fastball. In fact, there were six different plate appearances in which Buehrle threw three consecutive offspeed pitches. Never one to waste time on the mound, his quick work and mix of pitches and speeds successfully kept the Blue Jays off balance. Though his overall numbers suffer from an atrocious opening day start, Buehrle will have to pitch like this much more often for the White Sox to avoid the label of “pretender” and be in the race all year.

Indians lefty Cliff Lee recently put the finishing touches on an absolutely incredible April. Ironically, the 6 IP, 3 ER, 3K performance on Wednesday night—one many pitchers would love to have—was far and away his worst of the month. He will likely garner AL Pitcher of the Month honors, in unanimous fashion, and rightly so: Anyone who posts a legitimate W-L of 5-0, a 0.96 ERA, 16.0 K/BB, and has surrendered just one home run in 37.2 innings truly deserves any and all recognition.

Oh, and Lee also pitched 28 consecutive scoreless innings.

It began in the fifth inning of his April 13th start and lasted all the way until the seventh inning of Wednesday’s start. Despite this, he did not even get halfway towards Orel Hershiser’s oft-underrated and mind-boggling 59 consecutive scoreless innings record. Seeing as Lee’s effort has come to an end I decided to break everything down and analyze what happened in these innings. Hmm… a summary of Cliff’s streak… wait for it… Cliffsnotes:

Overall Streak Line: 28 IP, 10 H, 0 R, 1 BB, 24 K

Of those 28 innings, 18 were perfect (no baserunners) and 4 more saw Lee face the minimum; in each, singles were erased by double plays.

He allowed 11 runners to reach base and only two found themselves at third base. In the fifth inning on April 24th, Jose Guillen doubled and advanced to third on a wild pitch. With two outs, Lee struck Miguel Olivo out to end the threat. In the fifth inning Wednesday night, Wladimir Balantien reached third before Ichiro Suzuki flied out.

The situation with the highest Leverage Index (1.95) occurred when John Buck led off the ninth inning on April 24th; Buck flied out.

He found himself in eight situations with a Leverage Index of 1.60+ and produced the following results: 4 flyouts, 2 groundouts (1 GIDP), and 2 strikeouts.

His WPA over the course of these four games (31 IP) accounted for 1.72 wins; his WPA during this streak (28 IP) accounted for 1.67 wins.

Using TangoTiger’s Marcel projections I classified those with expected slugging percentages of .445+ as power hitters and under that mark as contact. Against Lee, power hitters went: 5-25, 2B, 4 GIDP, 5 K. Contact hitters went: 5-69, BB, 19 K.

The blog Defensive-Indifference does not think Lee will be able to sustain his current pace and I happen to agree. One of the reasons he is unlikely to continue dominating is that his current BABIP of .195 exceeds expectations based on a line drive frequency of 13.7%; with that frequency it should be closer to .257. Additionally, despite posting a 0.96 ERA, his FIP implies it is closer to the 2.01 mark; still great, but not superhuman. Regardless of what happens from May until September, though, Lee had an absolutely phenomenal opening month.

It’s no secret that Micah Owings is a great hitting pitcher, often causing analysts to refer to him as a hitter that happens to pitch rather than the aforementioned moniker. Reports even circulated prior to the season starting that Owings might get some playing time at first base due to the departure of Tony Clark. Last year, Owings produced one of the best hitting-seasons-for-a-pitcher of all time, thanks to a slash line of .333/.349/.683; he also hit eight doubles, one triple, and four home runs.

In the sixth inning of last night’s Diamondbacks-Astros game, Owings hit a pinch hit, two-run homer to tie the game. The Astros even made a pitching change prior to the at-bat in order to bring in righty Dave Borkowski and Brad Ausmus commented that Owings is the only pitcher over which he has ever discussed sequencing strategies. ESPN had a field day showing highlights and questioning whether or not Owings belongs in the lineup everyday, but the following video segment made me cringe:

They specially selected the ridiculously small sample size of 75 plate appearances in order to further a point that did not necessarily need to be made. Everyone knows he is a tremendous hitter and this comparison did nothing but show a complete ignorance towards the usage of statistics. The hard part about criticizing the video is that the anchors actually used and explained OPS! Granted, OPS is not the end-all, be-all, but for a mainstream show such as Sportscenter to discuss a sabermetric statistic is a pretty big step. Unfortunately, they lost points with the small sample size comparison.

Earlier today on PTI, Michael Wilbon mentioned that putting Owings in the lineup should be done sparingly at first until a large enough sample could be gathered to determine his true ability. Suffice it to say, I was shocked: One ESPN show discussed OPS and another discussed how small sample sizes should not be used to make quick judgments. While discussing sabermetric statistics and explaining how small sample sizes fail to explain anything truly tangible are both important, which do you feel would be best served exploring deeper on mainstream analysis-driven shows?

This offseason the Diamondbacks struck gold in winning the Dan Haren sweepstakes. The young, 27-year old ace looked mighty fine when placed right next to Brandon Webb. Billy Beane decided it was time to rebuild and sent Haren to the desert for six prospects: Dana Eveland, Carlos Gonzalez, Brett Anderson, Gregory Smith, Aaron Cunningham, and Chris Carter. Many had only heard of Eveland and Gonzalez but, as usual, concluded that the other four must have solid value because they attracted the attention of Beane.

Haren has pitched quite well in the early going, legitimately posting a 4-1 record with an FIP of 3.26. Further west, though, Gregory Smith and Dana Eveland have been flying under the mainstream radar and paying dividends to a surprising Athletics team. Of course the season is still young, but these youngsters deserve some credit.

Smith has pitched at least six innings in four of his five starts, and is yet to surrender more than three earned runs in any of them. He currently sports a 1.06 WHIP and an LOB of 75.5%. His line drive percentage of 17.2% expects a BABIP of around .292, yet it currently sits at .226. Additionally, his ERA of 2.73 translates to a 4.20 FIP. He has not been as steady with the luck-based indicators as Eveland but ranks 9th among AL starters with a 0.73 WPA/LI.

Eveland’s ERA of 3.13 translates to a still quite good 3.46 FIP. Allowing 16.8% line drives we would expect his BABIP to be around the .288 mark; it is currently .291, so he has not been unlucky in that regard. He currently ranks 16th among AL starters with a 0.52 WPA/LI, just slightly ahead of teammates Chad Gaudin and Joe Blanton. Yes, four-fifths of the Athletics rotation ranks in the top twenty. His K/BB of 1.86 is nothing to write home about but he has pitched quite well for a 24-year old with just six major league starts entering the season.

Though Eveland pitched poorly last night. based solely on April performance, this trade has definitely benefited both teams, and the Athletics still have four more prospects yet to scratch the surface.

Blue Jays righty Roy Halladay has earned his reputation as being a top-tier pitcher, one of the best this decade. Predominantly utilizing a combo of fastballs, cutters, and curveballs, Halladay keeps the ball on the ground, generating grounders just about 60% of the time. Though he has suffered some injuries in the last few years, when healthy, going late into games is not an issue; he has pitched 220+ innings in four of the last six years. This durability has led to 32 complete games since 2002, seven more than closest competitor Livan Hernandez. The entire AL had 64 complete games last year and Halladay accounted for seven of them.

There have been 16 complete games this year and Halladay currently has four of them. Additionally, his other two starts have seen him go for seven and eight innings respectively. Oddly enough, despite pitching a complete in each of his last four starts, his W-L in that span is 1-3. His three consecutive complete game losses ties a Blue Jays record set in 1980 by Jim Clancy. The last pitcher to lose consecutive complete games is another Roy: Roy Oswalt, who did so in 2006.

The last major league pitcher to throw four consecutive complete games? Well, that would be Halladay back in 2003. The all time record for consecutive complete games belongs to Jack Lynch, with 198; his record was compiled between 1881 and 1887. Halladay would need an average of 33 starts in each of his next seasons just to make 198 starts, let alone go the distance.

Very interesting about his complete games is that he is not overextending himself by throwing a ton of pitches. Through 49.2 innings he has thrown 648 pitches, which amounts to an average of 13 per inning. His complete games have consisted of the following pitch counts: 110, 117, 107, 112. The Blue Jays have scored 115 runs this year, just 17 of which have come in Halladay’s six starts. The team has provided an average of 4.67 runs/gm in non-Halladay games and just 2.83 runs/gm for their ace. Hopefully the team can start scoring runs or else this former Cy Young Award winner may find himself qualifying for next month’s edition of unluckiest pitchers.

The Milwaukee Brewers optioned Dave Bush to their AAA Nashville club this week following an 0-3 start with a 6.75 ERA. This irked many in the statistical community, especially MGL, because not only is Bush pitching better than the barometric numbers indicate, he is pitching right on par with normal #3 or #4 starters.

The problem, after looking into it more, is not necessarily that Bush’s optioning stems from his slow start but that it may have to do with his Jekyll-like transformation once runners get on base. In 1649 career PA, batters are posting a .253/.307/.420 clip against Bush while the bases are empty. When occupied, though, this jumps to .314/.355/.546 in 1121 PA. Despite these numbers, if the decision to option Bush stemmed from a kneejerk reaction to a small sample size, this argument does not even hold water.

This year, with 57 PA, opponents are hitting .320/.404/.560 with the bases empty. In 47 PA, they are hitting just .263/.340/.368 with runners on base. In the early going he has allowed a higher percentage of runners to reach base but has actually reduced his slash line once they get to their respective bases.

Ned Yost attributed the move to control issues. In his four 2008 starts, Bush has thrown 57.6% of his pitches for strikes. In 2007 he threw 65.6% strikes out of 2972 pitches. In 2006 he threw 66.4% strikes out of 3021 pitches. He has thrown a lower percentage of strikes, putting himself into more “Hafta’ Counts” and forcing himself to pitch from behind. The Brewers had a pitching surplus entering the season, often fostering rumors of trading Bush and/or Claudio Vargas.

Seemingly happy with the production from Ben Sheets, Yovani Gallardo, Jeff Suppan, Carlos Villanueva, and Manny Parra, the team felt they could handle letting Bush get his control back in a few minor league starts. The decision was definitely based off of a small sample size and, in that regard, makes little sense, but I hope they realize it is way too early to sell their stock on Bush.

When discussing the early season productivity of a player it is important to remember that the barometric statistics analyzed by those on television often have better evaluative indicators beneath the surface. Many of these indicators deal with luck, or a lack of luck, and provide a more telling window into what should be expected from the player in the coming weeks and months. Dave Cameron wrote earlier today about Nick Johnson and how, based on his high percentage of line drives but low BABIP, Johnson has experienced an unlucky streak this month. Using a slightly expanded method to the ones currently used to determine luck (relative to GB/FB/LD and BABIP) I decided to figure out the unluckiest pitchers of the month.

Initially the method consisted solely of BABIP and the difference between FIP and ERA (FIP-ERA) but I then extended it to include their current W-L records. Though anyone at least casually versed in statistical analysis will explain the faults of a W-L record, fans that simply love the game without analyzing anything equate W-L records to quality.

A pre-requisite also found its way into the criteria in that the FIP could not be above 4.30, a cutoff I usually look for when determining the difference between good and average. This way players like CC Sabathia and Barry Zito could be avoided; players who, despite having large FIP and ERA discrepancies, still had very high FIP and ERA counts. In summation, the players I considered to be the unluckiest were those with high FIP and ERA discrepancies, a high BABIP against, and a W-L record that does not do a good job of representing the quality of games pitched. This left me with the following four candidates:

Nate Robertson: 6.91 ERA, 4.18 FIP, -2.73 FIP-ERA, .333 BABIP, 0-3 W-L
Nick Blackburn: 3.45 ERA, 2.72 FIP, -0.73 FIP-ERA, .347 BABIP, 1-1 W-L
Ian Snell: 4.45 ERA, 3.03 FIP, -1.42 FIP-ERA, .358 BABIP, 2-1 W-L
Zach Duke: 5.34 ERA, 3.97 FIP, -1.36 FIP-ERA, .369 BABIP, 0-2 W-L

So, of these guys, whom do you consider to be the unluckiest this month?

Deciding to take a short break from the NBA playoffs I tuned into ESPN last night and took in the Yankees/Indians game. Hoping to see a strong performance from a longtime favorite of mine, Mike Mussina, I was instead treated to a great performance from a young Indians lefty named Aaron Laffey. One of those recently recalled to fill the void left by Jake Westbrook’s DL stint, Laffey, a guy just eight months and one day older than me, pitched admirably through his 5.2 innings of work. His end line of 5.2 IP, 3 H, 4 ER really did not do him any justice as the runs scored primarily as a result of bad luck and a lack of aggressive defense.

For five innings, Laffey had a no-hitter going, throwing just 63 pitches. He mixed his fastball, slider, and changeup well, in turn keeping many of the Yankee hitters off-balance; he also induced four popups/foulouts. Nobody hit the ball hard off of him all night except for Bobby Abreu, who flied out to deep centerfield in his first at-bat, and roped a single to leftfield in the sixth inning. All but two of the balls put on the ground by the Yankee bats were weakly hit. Through the fifth inning these were easy outs, but during the sixth inning they proved to be a major factor in bad luck joining him on the mound.

The sixth inning started off with a weak grounder in between shortstop and third base from Melky Cabrera. Jhonny Peralta got his glove on it but the weakly hit ball, combined with the speed of Melky, ultimately resulted in an infield single. Derek Jeter followed with an even weaker groundball to third base. Casey Blake charged but stumbled while attempting to get the ball of his glove. With first and second, Abreu hit the aforementioned single, loading the bases in the process. Laffey then hit Alex Rodriguez in the ribs causing Cabrera to score. In terms of WPA (-.130) and Leverage Index (3.45), this was the biggest play of the game. Check out the big spike in the game graph below:

Still holding onto a 2-1 lead, Laffey went right after Jason Giambi and Hideki Matsui, inducing two more weak groundballs; this time they went to first baseman Ryan Garko. Garko’s lack of aggressiveness in charging these grounders led to Jeter and Abreu scoring. A fourth charged run to Laffey’s line scored when Morgan Ensberg singled Rodriguez home off of reliever Jensen Lewis.

Overall, Laffey looked extremely sharp and his pitch usage made the Yankees look a bit foolish at the plate. Though his numbers did not necessarily paint a descriptive picture of his performance last night, Indians fans should be very encouraged at what this kid may be capable of.

One of the hot topics during spring training revolved around the Tampa Bay Devil Rays and how this would be the year they experienced significant improvement. Photos surfaced of an interesting shirt Troy Percival donned on which he compared Scott Kazmir, James Shields, and Matt Garza to John Smoltz, Tom Glavine, and Steve Avery. Steve Phillips added fuel to this fire by repeatedly mentioning how the shirt compared the three Rays youngsters to Greg Maddux, Glavine, and Smoltz. With no disrespect towards Avery, he is not Greg Maddux, and any comparison to one of the best pitching trios in the history of the game is going to generate some buzz. As of right now, Kazmir is yet to pitch and Garza has not yet met expectations; Shields, however, has pitched quite well.

Great pitching trios are so valuable for the more obvious reason that, over the course of any given three game series, the team is likely assured of having at least one solid starter on the mound. Seeing as April is about to come to a close I decided to take a look at the WPA totals of starting pitchers from 2002 until now to generate a basic list of the best recent pitching trios. The only real “rule” stipulated that all three of the pitchers needed to have a positive WPA. For instance, last year, the combination of CC Sabathia, Fausto Carmona, and Paul Byrd accounted for a WPA of 7.13. This would normally qualify as second-best across the league, but the numbers broke down as follows: Carmona at 4.25, Sabathia at 3.49, Byrd at -0.61. Clearly the WPA total belonged to CC and Fausto; Byrd actually brought their total down. Here are the top trios from 2002 until now:

2002 – Athletics: Barry Zito (3.85), Tim Hudson (3.28), Mark Mulder (3.15)
2003 – Cubs: Mark Prior (4.37), Kerry Wood (4.05), Carlos Zambrano (2.46)
2004 – Twins: Johan Santana (5.52), Brad Radke (3.61), Carlos Silva (0.61)
2005 – Astros: Roger Clemens (5.77), Andy Pettitte (4.86), Roy Oswalt (3.91)
2006 – Tigers: N. Robertson (2.92), Justin Verlander (2.29), Kenny Rogers (2.21)
2007 – Padres: Jake Peavy (4.61), Chris Young (2.67), Greg Maddux (1.17)

A month into this 2008 season and there are three rotations very close to each other: the Cardinals (2.20), Mariners (2.11), and Angels (2.08). The Cardinals trio in question is Adam Wainwright, Kyle Lohse, and Braden Looper; the Mariners are Felix Hernandez, Carlos Silva, and Jarrod Washburn; the Angels are Joe Saunders, Ervin Santana, and Jered Weaver.

Update: The Indians can also be thrown into the mix, but not with Sabathia. The combo of Lee, Carmona, and Westbrook are currently at 2.35. Add them into your consideration. As I mentioned in the comments, though, for potential Mariners fans reading here, Bedard does not count because he does not qualify for inclusion yet. Clearly he is a better choice than Washburn, but the question pertains to the aforementioned threesomes.

Felix Hernandez is the best of the nine pitchers comprising these three teams but, overall, none of them appear to be on the same level as some of the aforementioned trios. Here’s the question: If you had to win a three-game series, which of these three 2008 trios would you pick, and which of the 2002-2007 trios would you pick?