Phillies Week in Review, 6/19-6/25

With the start of my new full-time job, I am now in a position where I will need to regiment my lifestyle effectively in order to make sure I get the things done that I want to.  Since this blog is included in that collection of tasks, I will try to make sure to write at least once per week.  How better to ensure that than by having a weekly piece about the only thing that is consistently going on during the summer, the baseball season?  As a Philly guy, I have unique interest in the Phillies, so y'all are just going to live with me blabbering on about a sub-.500 team that many people are ignoring out of disappointment.

Let's see where this goes.

Team Performance

Record: 4-3 (35-40 overall)
Streak: W1
Division: Gained 1 game, 8 GB
Avg Opponents' Record*: 35-38
* Weighted average of current records of opponents during the week

As an average team, it's not altogether surprising to see the Phillies play about even with average teams.  They were just 5-10 against AL teams during interleague play, which is business as usual for them.  With 9 out of 12 remaining pre-All-Star games against division rivals, they have a real opportunity to make hay and get some momentum for the back end of the schedule.  With Chase Utley set to return quite soon, they might just get that boost.

Most Outstanding Hitters

Jimmy Rollins -- 31 PA, .393 AVG, .452 OBP, .929 SLG, 4 HR, 9 R, 7 RBI, 1 SB

He's on a J-Roll right now (yeah I said it), posting half of his home runs for the season this week and putting together an OPS of almost double his season average.  Everyone always says that he's the catalyst of the lineup, and perhaps that is the case, with the team scoring at least 7 runs 4 times this week.

Carlos Ruiz -- 28 PA, .348 AVG, .464 OBP, .522 SLG, 1 HR, 4 R, 4 RBI, 1 SB

His season averages are .354 AVG, .421 OBP, .561 SLG, and he just keeps on trucking.  The home run rate has slowed down after five jacks in May, but he's on pace for just about 20, which would more than double his career high of 9.  Not to mention that he stole as many bases as Rollins this week.  The man's got wheels.  Kinda.

Michael Martinez -- 20 PA, .050 AVG, .050 OBP, .200 SLG, 1 HR, 1 R, 3 RBI, 0 SB

Not only was he the worst Phillie at the plate this week, but he was the worst Phillie in the field as well (per FanGraphs), which naturally begs the question: why is he on the field?  Ever?  I know Mike Fontenot is boring (he has 20 hits, 18 of which are singles), but he is hitting over .340.

Most Outstanding Pitchers

Cole Hamels -- 15 IP, 1.20 ERA, 1.00 WHIP, 14 K, 6 BB

The price for Hamels' services next year and beyond continues to stay at about $25 million per year as he continues a solid year surrounded by inconsistency and injury in the rotation.  The 6 walks are slightly bothersome by his standards, but they are his standards.

Raul Valdes -- 2 IP, 0.00 ERA, 0.50 WHIP, 4 K, 0 BB

Not exactly a big name or even a guy that pitched a lot, but it's worth acknowledging that he has struck out 17 of 52 batters faced this season while only walking one and allowing a .157 opponents' batting average.

BJ Rosenberg -- 0.2 IP, 27.00 ERA, 6.00 WHIP, 0 K, 4 BB

I'm as much a fan of Rosenbergs as the next guy, but definitely not in the athletic domain.  Mah Jongg, maybe.  There is a  silver lining -- he didn't allow a hit -- but that's simply because it would be imprudent for anyone to even swing at a pitch if he's walking 2/3 of the batters he faces.

Waiting on the Right Side of Your Infield to Change

            I’m not sure if any of you have heard, but the Phillies have been missing two of the cornerstones of their team the past five years, Chase Utley and Ryan Howard, for the entirety of the 2012 season.  While Utley just started a rehab stint that could signal a return early in July, Howard has yet to start running and fielding and could be out until August, if not longer.  Phillies fans know that the past two weeks have been trying for the team, losing 9 of their last 10, and they now sit a hefty 9.5 games out of first place behind the Nationals, who themselves have won 8 of their last 10, and 5.5 games out of both Wild Card spots.  So how much will the returns of Utley and Howard be a boon to the team’s offense, possibly propelling them to a come-from-behind playoff berth?

            Phillies first basemen this season have produced a .257 / .316 / .401 BA/OBP/SLG this season, creating 0.112 runs per plate appearance (by FanGraphs’ Runs Created formula) and have a fielding Ultimate Zone Rating of 4.8 runs prevented when scaled per 150 games.  Last season, Ryan Howard posted a .253 / .346 / .488 line, created 0.143 runs per plate appearance, and had an UZR of -4.5 runs prevented on the same scale.  Howard would produce about 11 more runs combined batting and fielding than the John Mayberry/Ty Wigginton/Laynce Nix/Jim Thome combination over 2+ months, which would be about the amount of time Howard should be back for.

           

            Phillies second basemen this season have produced a .260 / .292 / .386 line, creating 0.092 runs per plate appearance, and having a UZR of -1.5 per 150 games (which is surprisingly low given how Freddy Galvis has performed).  Last season, Chase Utley had a .259 / .344 / .425 line while creating 0.134 runs per plate appearance, with a UZR of 14.5 per 150 games.  Giving Utley just about half a season of production, he would produce about 54 runs, compared to 31 for the Galvis/Fontenot/Martinez collection.

            With Utley and Howard back in the lineup, therefore, we could expect the Phillies to improve by 25 runs over the second half of the season, which is good for only a couple more wins.  Taking into account the improvement in the depth of the team by having Wigginton, Galvis, Fontenot, and Mayberry as bench players instead of starters, they’re likely to net at most a 4 win improvement over the second half.  Getting Utley and Howard back will not cure what ails the Phillies all by themselves -- their bullpen ERA of 4.44 is third-worst in the league and 0.59 worse than last year – but it’s a start in the right direction, and could give players an emotional boost that powers them to a second-half surge.

            

Throwing Water on the Johan Santana No-Hitter

First, a brief statement directed only to Mets fans: 7.5 games back with 17 to play.  Go Phils.

            Now, about the chronologically relevant topic of Johan Santana’s no-hitter two nights ago, in which he posted the following pitching line:

9 IP, 0 H, 0 R, 5 BB, 8 K, 134 Pitches (77/57 Strike/Ball), 3/16 GB/FB ratio

            Obviously, a no-hitter is an impressive achievement, but one should revel in the fortune of it just as much as the skill, and also realize that it is mostly the fact that we have always counted no-hitters that we feel that they are impressive.  The no-hitter is fairly common; they have occurred 275 times since 1876 (or about twice per year), and 20 times since 2007 (almost 4 times per season), so they are not nearly as impressive as perfect games, which have occurred just 27 times. 

            A pitcher does not necessarily need to be at the top of his game to achieve this feat, as shown by Edwin Jackson in 2010, who threw a no-hitter while allowing 8 walks and throwing 149 pitches.  Much of this phenomenon has to do with luck.  In a previous post, I discussed how fly balls have a great deal of random variance in their trajectory that can seriously impact game results.  Santana’s absurdly high fly-ball percentage in this game (his season average is just 66% compared to this game’s 84%) illustrates that he was incredibly lucky to escape this game without getting blown out, let alone allowing a hit.  Santana did not have incredible control in this outing, throwing 56% strikes compared to his prior season average of 64%, and walking five, none of which were intentional, and all of which included three consecutive balls at some point in the at-bat.

            ESPN tracks a statistic called the Game Score, which attempts to gauge a pitcher’s performance in a particular game using outs recorded, innings pitched, strikeouts, walks, hits, and runs, and is on a scale from 0 to 100 (theoretically).  It has been referred to in the past on ESPN in reference to the comparison of the consecutive 2010 postseason games in which Roy Halladay pitched a no-hitter and Tim Lincecum allowed 2 hits while striking out 14.  Halladay’s game was given a 94, while Lincecum’s was given a 96, and Santana’s no-hitter received a 90.  This may seem shocking to long-time baseball fans (“how could you beat a no-hitter?”), but it makes sense from the perspective that control and command (which are much more effectively measured by strikeouts and walks than by hits allowed) are a superior method of judging a pitcher’s performance.  In fact, three non-no-hitters this season alone have surpassed Santana’s game score, and they all have similar qualifications: 11+ strikeouts and 2 or fewer walks without allowing any runs.  In case you’re wondering what would constitute a 100, the following games performances have achieved that score since 2000:

9 IP, 1 H, 0 R, 2 BB, 17 K, 137 Pitches (Brandon Morrow vs. TB, 2010)

9 IP, 0 H, 0 R, 0 BB, 13 K, 117 Pitches (Randy Johnson perfect game vs. Atl, 2004)

9 IP, 1 H, 0 R, 2 BB, 17 K, 127 Pitches (Curt Schilling vs. Mil, 2002)

            The moral of the story is that just because you have a title for an achievement does not mean that it is the pinnacle of achievement in that arena.  Would you rather hit for the cycle or hit 4 home runs?  Or even four triples?  And don’t get me started on the Save.

Roy Halladay Finally Breaks Down

            Given the information currently at our disposal, it appears that Roy Halladay is out with a lat strain for the next 6-8 weeks, leaving the Phillies in quite a precarious position.  While the team has won 5 of its last 6 and sits 2 games above .500 for the season, they are still in last place in the NL East, and the one loss was the game in which Halladay left early with the injury.  However, Phillies fans should realize how spoiled they’ve been for the past few seasons, and understand that the Halladay of 2011 is not likely to return, even after 8 weeks.

            First of all, let’s take into account that Halladay is 35 years old.  Last year, just 5 pitchers age 35 or older threw at least 200 innings, and 5 had an ERA of under 4.00 – Chris Carpenter, Tim Hudson, R.A. Dickey, and Hiroki Kuroda fit both bills.  From 2008 to 2011 (ages 31-34), Halladay averaged over 240 innings per season and had his four highest strikeout rate seasons, four of his seven lowest walk rate seasons, and four of his five lowest ERA seasons, so it’s safe to assume that without an injury, he would have done just fine.  But how good could we really expect him to be?

            Halladay has been nothing short of amazing since 2006, leading many to believe that he would be dominant for quite some time beyond this year.  From ages 29 to 34, no one except Greg Maddux accrued more Wins Above Replacement than Halladay in the modern era.  Names like Bob Gibson, Gaylord Perry, Jim Palmer, and Tom Seaver are the only ones above Halladay in both innings pitched and ERA over that age range.  He is sixth in wins by 29-34 year old pitchers, and his winning percentage is comparable only with Maddux, Randy Johnson, Pedro Martinez, and Whitey Ford (minimum 1000 IP).

            However, time takes its toll eventually.  Most pitchers begin to decline around age 35, and certainly injury becomes a concern before that.  Halladay has started between 31 and 33 games each of the past six years, an incredible run of health that seemed destined to end at some point.  And even if you grant him the benefit of the doubt that injury kept his statistics as “bad” as they were thus far this season, it really should be expected that he decline right about now.

 From the above graph of four (soon to be Hall of Fame) pitchers’ ERA trends over their careers, you can see that their prime years (with the exception of Blyleven’s early career) lie right between ages 28 and 34.  However, after age 35, Blyleven, Mussina, and Schiling all declined and/or became quite inconsistent ERA-wise, and it appears likely that Halladay will do similarly.  While it is unreasonable to expect that his ERA will stay as high as it is (especially given that his K, BB, and HR statistics are quite similar to previous years in which he was just fine), I think that upon his return, Roy Halladay will not be the same pitcher Phillies fans have seen dominate the National League since 2010.  At 35, we really shouldn’t expect that of him.  

We should be expecting that of Cole Hamels.

Three True Outcomes: Clearing the Mechanism?

Bonus points if you get the “For Love of the Game” reference.

            In my previous two posts, I went over two of the more commonly referenced sabermetric statistics (BABIP and HR/FB) when it comes to assessing how lucky (or unlucky) a player has been over a small sample.  This “luck” may just involve the interaction between the ball and the bat or the field, but can also be related to the positioning of the fielders (as with BABIP).  In attempting to judge the “true” value of a pitcher or hitter, however, sabermetricians have tried their hardest to isolate those aspects of the game that involve just the pitcher and the batter, and nothing else (“clearing the mechanism,” if you will).  This leaves us with what most stat guys call the Three True Outcomes: strikeouts, free passes (walks / hit-by-pitches), and home runs.  These outcomes have formed the canon of Defense Independent Pitching Statistics (DIPS).  How well do these few statistics actually measure the “true” ability of a player?

            Obviously, there can be a bit of discussion as to whether or not these three outcomes are really “pure.”  Yes, it is clear that any at-bat that results in the ball being put into play introduces variance from the skill and positioning of the players in the field, and therefore only the set of outcomes {BB, HBP, K, HR} should be considered.  The rest of the outcomes should probably be considered through the lens of BABIP.  While this seems just fine when it comes to judging the skill of pitchers, it really is insufficient to judge the worth of a hitter. 

Take a look at the true-outcome stats, as well as other relevant numbers, of three marquee outfielders in 2011 (note that ISO represents Isolated Power, which is just Slugging Percentage minus Batting Average):

	BB%	K%	HR	SB	AVG	BABIP	ISO
Nick Swisher	15.0	19.7	23	3	.260	.295	.188
Andrew McCutchen	13.1	18.6	23	23	.259	.291	.198
Carlos Beltran	11.9	14.7	22	4	.300	.324	.225

None of these players really separate from each other using the true outcome stats, but it becomes clear upon further inspection that Swisher is an inferior commodity, and it may be a matter of personal preference as to which of the remaining two you would want.  Why? 

            One thing that the True Outcomes ignore is speed.  While this has little to do with pure hitting ability, it certainly can make a player much more desirable and productive.  McCutchen stole 20 more bases than either of the other players.  While his batting average and on-base percentage were almost identical to Swisher’s, it can be assumed that his speed accounted for the slight advantage he held in isolated power, as he could leg out a couple more doubles and triples with that extra speed.

            As for Beltran, it is clear that, to some extent, his high BABIP contributed to a higher batting average than the other two (his career BABIP is right around .300).  However, it appears that he has an advantage over the other two players not in home-run power but in inside-the-park power, allowing him to gain a 20-point advantage in slugging without an advantage in the traditional power category, home runs.  Upon further inspection, Beltran hit the second-highest percentage of line drives in his career in 2011, producing a number of doubles and triples that he hadn’t produced in several years.  It becomes clear that you can still provide extra value by hitting the ball hard inside the park, even if you don’t hit more home runs than other players.

            While the true outcomes can form a pretty comprehensive representation of a pitcher’s performance (and I’ll get into this more later this week), it seems like a few other factors need to be considered with hitters.  A player’s speed contributes to his batting average (through BABIP), stolen base totals, and slugging percentage, and thus should not be taken lightly when considering performance.  Also, there is a good bit of variability of performance that can be found between players that have the same home run total, as players who can add a good amount of doubles and triples are much more valuable and likely to have consistent success over the course of a season or career.

Swing, and a Long Drive!

            My post a couple days ago talked briefly about the major differences in the direction and distance of the ball’s flight that can come from a small change in where on the bat the ball is hit.  No statistic captures this concept more than the percentage of fly balls that become home runs (HR/FB% -- yes it’s an awkward name).  I’m going to help describe this using simple geometry, because I don’t feel like dealing with the physics of it, and I’m sure you don’t feel like reading about it.

            Take a fly ball that reaches a peak of 150 feet and travels 300 feet (this is obviously just a rough number used to make the calculations easier, but go with it).   To save you the time reading (and the time criticizing my calculations), a change in 1/10^th of an inch in the position of the ball on the bat (and thus a reduction in the angle of flight by just 2 degrees) causes the ball to fly 10 feet further.  In short, there can be pretty strong deviations in the way the ball flies resulting from small, possibly uncontrollable changes in the way that the ball hits the bat.

            Therefore, to some extent there is a good bit of variability in the distance a ball will travel (or the height it will fly) that is not so strictly under the control of the hitter.  HR/FB% captures a bit of that randomness.  The average percentage of fly balls that become home runs is just under 10%, with a likely range of 0-30.  Batters with different styles tend to have different career average HR/FB%, just like with BABIP.  For example, Ryan Howard’s career average is 28.7%, while Juan Pierre’s is 1.2%.

            However, variance over the course of a career can produce pretty large shifts in power numbers, which contribute to a player’s RBI, HR, and R totals, as well as his batting average (fly balls are incredibly likely to be outs if they are not home runs).  Since Howard’s first full season in 2006, his best-to-worst HR/FB% per season has ranked like so: 2006, 2008, 2007, 2009, 2011, 2010.  His home-run totals in those seasons rank like so: 2006, 2008, 2007, 2009, 2011, 2010.  Notice a correlation?  In 2009, Joe Mauer hit 28 home runs after hitting 29 in the previous three seasons combined.  One needs to look no further than his HR/FB% of 20.4%, which was a full 10% higher than any other season he has posted before or since. 

            In a similar way to BABIP, HR/FB% is a better estimator of randomness with pitchers than with hitters because the variability in the statistic due to a batter’s skill set should even out over the course of a pitcher’s season.  Roy Halladay shouldn’t face a significant amount more sluggers or slap hitters than other pitchers in the league (or than himself in previous years) over the course of a full season, so large changes from year to year can be at least partially attributed to luck.  Or, you know, throwing beach balls up there.

            Take Ubaldo Jimenez’s breakout 2010, for example.  Without significant changes in his other underlying statistics (strikeout and walk rates, BABIP, etc.), his HR/FB% was extremely low at 5.1%, and he posted an ERA a full run below his career average.  Not only that, but his 9.3% and 10.5% HR/FB% in the next two years represent more average outcomes, and he has posted an ERA above 4.80 since the start of last season. 

With home run rates in mind, here are some players I expect to start to decline:

HITTERS: Matt Kemp (41.4%), Josh Hamilton (40%), Bryan LaHair (33.3%)

PITCHERS: Brandon Beachy (1.7%), Gio Gonzalez (2.6%), Ted Lilly (3.9%)

Here are some players I expect to improve when it comes to home run rates:

HITTERS: Jimmy Rollins (2.0%), Alex Rios (2.2%), Jeff Francoeur (2.6%)

PITCHERS: Ervin Santana (23.1%), Adam Wainwright (21.9%), Jonathan Niese (21.1%)

Hit 'Em Where They Ain't

            My introductory post on the topic of luck/randomness (or stochasticity -- Ivy League education right there) in baseball focused a lot on the degree to which small changes in the positioning of the bat and the ball can produce large differences in result.  Not only that, but slight changes in the positioning or movement of the fielders (like A-Rod giving one too many winks to the blonde in the third row) can also make the difference between an out and a single.  The most basic tool that we can use to assess how these random events have affected a hitter’s performance is Batting Average on Balls in Play (BABIP).

           

            BABIP, unsurprisingly, measures a player’s batting average on those at-bats in which he puts the ball in play (i.e. NOT a walk, strikeout, hit-by-pitch, or home run), putting the outcome of the at-bat up to the positioning of the fielders relative to the ball.  Each player’s skill set contributes to where his BABIP will tend to fall, as faster players beat out more grounders and thus have a higher BABIP, while sluggers tend to be slower and hit more home runs, reducing their average BABIP.  Over the course of a single player’s career, however, there can be pretty strong variability in the stat due to the positioning of fielders when he is at bat, as well as simple luck.

           

            Here’s an example of the effect that BABIP can have on performance from year to year.  Take Ichiro Suzuki, a guy who has been around as long as he has because of his ability to get a lot of hits with his speed.  His average BABIP over his career has been .350, which is about 50 points above the league average in that span.  To make this a more appropriate discussion, I’ll disregard the past two seasons, in which his age has caught up to him and his batting average dropped 50 points from his career average.  From his rookie year in 2001 to 2010, Ichiro’s worst BABIP was .316, and his best was .399, representing pretty large deviations from his career numbers.  These seasons also correspond to his worst and best batting-average seasons, at .303 and .372, respectively.  In fact, the r² value between Ichiro’s BABIP and batting average, or the percentage of variance in batting average that can be explained by BABIP, is 97%, meaning that almost all of Ichiro’s year-to-year changes in batting average can be explained by the weird stuff that happens once the ball hits the bat.

            How can we use BABIP to our advantage?  Let’s take my fantasy team, for example.  The only reason I drafted Tigers catcher Alex Avila this season was because he represented a great value, but I wasn’t happy about it.  Why?  He hit .295 with 19 homers and 82 RBI while only playing 140 games because Victor Martinez played some catcher.  This season, Martinez is hurt and they add Prince Fielder – slam dunk, right?  I was skeptical.  Avila’s BABIP in 2011 was .366, 90 points above what he posted in 2010, his only long stay in the majors.  Regression to the mean would probably put Avila’s BABIP at more like .310, cutting his batting average by a solid 50 points, and thus bringing his run and RBI totals down as well.  What has actually happened?  He’s on pace to hit .225, 19 homers, and 56 RBI this season, a significant downgrade from a breakout 2011.

            I would be remiss not to mention that BABIP can be just as useful for pitchers as for hitters.  While skill set doesn’t really come into play with pitcher BABIP (most players’ career rates center around .290 to .310), the concepts of luck and fielder ability still apply, and perhaps more consistently than with hitters.  For example, there was controversy as to whether Rays pitcher Jeremy Hellickson’s 2.95 ERA in 2011 could be maintained given the .223 BABIP against him.  However, if you look deeper, his low BABIP is as much about the Rays’ team fielding prowess as it is about good fortune.  Among Rays pitchers with at least 40 IP, no one had an opponents’ BABIP higher than .284.

           

            Cubs ace Ryan Dempster had a 4.80 ERA last season, but had one of the highest starters’ BABIP in 2011 at .324.  This season, his BABIP is .259, and his ERA is 1.74.  Former A’s starter Trevor Cahill posted a 2.97 ERA and went 18-8 in 2010 with a shockingly low .236 BABIP.  In 2011, his BABIP went back to normal (.302), and he went 12-14 with a 4.16 ERA.  Granted, there are other factors at play here, but absent a dramatic change in the defense behind him or the park in which he plays, a pitcher’s performance is very much dependent on where the ball happens to fall.

Based solely on BABIP, here are some players that are overachieving that I might expect to fall back to earth relatively soon (with their BABIP and batting average or ERA, as of last night):

HITTERS: David Wright (.470, .411), Bryan LaHair (.406, .330), Paul Konerko (.406, .362)

PITCHERS: Ted Lilly (.196, 2.11), Brandon Beachy (.214, 1.33), Lance Lynn (.219, 1.81)

As for players who one might expect to bounce back from a tough start…

HITTERS: Eric Hosmer (.165, .174), Jose Bautista (.178, .207), Russell Martin (.186, .167)

PITCHERS: Max Scherzer (.403, 6.26), Josh Johnson (.385, 5.36), Ivan Nova (.380, 5.44)