I’m in love with the new Baseball-Reference WAR data. WAR, or Wins Above Replacement, is the uber-stat that attempts to encompass the total value of what makes a player, erm, valuable. With the development of FanGraphs and other saber-slanted websites, WAR has become a pretty well known statistic. If you’re new to the game, check out the glossary section of the site for a definition.

One of the components of WAR is fielding. Now that BB-Ref is providing WAR data, I’ve been having a good time running various queries. Best WAR seasons, best baserunning seasons, best fielding seasons — and today’s post, the worst fielding seasons in Giants’ history. A few words before we jump in and have fun. Baseball-Reference’s fielding component for WAR comes in the form of Total Zone. It’s expressed in runs above (or below) average. Also, when considering defense at a position we must realize that a -10 run first baseman isn’t the same as a -10 run shortstop. The shortstop is a much more athletic group when compared to your average group of first basemen. So, we can assume that if we moved a SS to 1B he would be very good, if we moved a 1B to SS, he wouldn’t do so hot.

Now, let’s check out the 10 worst fielding seasons — as measured by the Total Zone component of BB-Ref WAR — in Giants’ history.

A graph plus the data table. Click the graph to enlarge. It looks much better at full resolution.

A good mix of Giants past and present. A few words on some of the names on our list.

• #1 on our list is Bobby Murcer’s 1975 season which clocks in at -22 runs below average just on defense. Bobby Murcer is known for a few things in his baseball career. First and foremost, from a Giants’ perspective, is that he’s the player the Giants traded for when Bobby Bonds was sent to New York in the offseason of 1974. Bonds went on to have maybe his finest season that year when he hit .270/.375/.512 (151 OPS+). For the Giants Murcer had a fine year on offense batting .298/.396/.432 (127 OPS+) but, as our graph and data table show, his defensive numbers in the outfield were terrible. Oddly enough, Murcer — a gold glove winner in 1972 — scores poorly by Total Zone throughout his career. He owns a career mark of -97 runs below average in the outfield. It’s almost as if the Gold Glove Award doesn’t do a good job of assessing good defense. Hmmm.
• Ron Hunt was never considered a strong fielder and his 1970 season and the -20 runs (nearly negative 2 wins) he accumulated on defense was a career worst. Hunt, a career 2B, played primarily 2B in ’70 but he also saw some time at 3B. Hunt — the master of getting hit by pitches– has maybe one of my favorite baseball quotes of all time, “Some people give their bodies to science; I give mine to baseball,” And to back that statement up he ended his career with an astounding 243 HBPs. To this day, he owns the record for most HBP in a single season with 50(!) in ’71 with the Expos. The HBP magnet only played 3 seasons with the Giants from 1968-70.
• Maybe my favorite player on the list, Dick ‘The Mule’ Dietz, shows up for his 1970 season and the -20 runs on defense that accompanied it. Dietz’s season is really a tale of two different skill-sets. On offense Dietz was incredible — batting .300/.426/.515 (152 OPS+). It’s probably the best offensive year ever for a Giants’ catcher. However, on defense, Dietz was another story. His -20 runs is damaging, but also consider some of the traditional stats that, I think, tell a story. Dietz made 14 errors, 25 passed balls, and caught only 19% of base-stealers. Dietz gave up 92 stolen bases that year while only throwing out 21 runners. Even more amazing is he was still worth +4.5 wins that year — even docking him nearly 2 wins by defense — he was an All-Star and still remains one of my favorite Giants of all-time. You have to wonder if Dietz would have been moved over to first base if he hadn’t played with McCovey.
• Hey look, a Marvin Benard sighting. His -19 runs below average on defense in ’99 is our most recent Giant to make the Butcher List. I have to admit, I’ve got a soft spot for Benard. He was generally acceptable on defense — a carer +2 runs by TZ — and he had a couple of average to above-average years (’98, ’99, and ’01) on offense. He was most likely stretched as a CF and the Giants didn’t help themselves by primarily playing him there. He would have most likely done much better in a corner spot.
• You’ve got to feel for Johnnie LeMaster. He was futile on offense — career OPS+ of 60 — and his defensive numbers don’t stack up. Since he was a SS, we should note that he was playing in a more athletic peer group than the OF/1B group, but LeMaster scored poorly across the board over his career on defense. In fact, by BB-Ref’s WAR, he’s -7 wins below replacement level for his career. His -15 run defensive season in ’82 was paired with an OPS+ of 51. And yet he still appeared in 130 games and collected 436 at-bats.

An interesting list. Dick Dietz’s season in 1970 in particular is notorious for it’s defensive problems. Total Zone is really handy when we’re trying to examine historical players that fall past the scope of current defensive metrics like UZR.

Comment Starter: Anyone on the list surprise you? Anyone you think should be added to our Top 10?

All of that on-based goodness stems from Torres’ approach at the dish — he rarely swings at pitches outside of the strike zone. You’ll often hear announcers state that a certain player has a good idea of the strike zone, Torres fits that phrase almost perfectly.

This week’s graph shows Torres swings vs. non-swings on pitches outside of the standard PFX strike zone.

I posted similar graphs back in last September for Fred Lewis and Pablo Sandoval. But, as you can see, Torres isn’t very likely to swing outside of the zone. They say that players tend to walk more as they age to compensate for the loss of skills, but Torres has seemingly developed both power and an eye at the dish as he’s aged. One has to wonder how much time the 32-year-old Torres has left? Even if you think that his hitting ability could slip — or revert back to his late days in AAA — his defense should keep him valuable. And until the wheels come off, I’ll be enjoying Torres’ turn-around as a player. It’s probably one of the more remarkable transformations that I’ve seen in baseball.

While reading McCovey Chronicles, user oldjacket posted the following which got me thinking:

High fastball. Can’t hit it. Can’t not swing at it.

How has Sandoval been handling the high fastball this year? We know that strikeout pitchers tend to pitch up in the zone with their fastball. This has a couple of related outcomes, they tend to give up more flyballs — and generally home runs — but they also balance that out with the strikeout. Pablo, a free-swinger, seems like the type of guy that’s going to swing at a lot of pitches, regardless of where they are in the zone. How is he handling the high heat? Is he swinging at them? Is he making contact? Is he missing them entirely?

I decided to look at Pablo’s 2009 and 2010 season along with the league average whiff, contact, and swing rate for what I’m calling “high fastballs”. It’s incredibly basic, but I’m defining any fastball with a height of 2.5 feet, or greater, a high fastball. That’s halfway up the normalized strike zone as defined by most PFX analysis.

A graph, and then some data:

(Click to enlarge)

This is a graph depicting Sandoval vs. pitchers by handedness and fastballs. For the visual side of things, I’m including just whiffs and not contact or swings. The graph became really busy when I added those things in. The dashed-line across the standard strike zone indicates the cutoff for what I’m terming a “high fastball”. Here’s the data for Pablo Sandoval on high fastballs compared to the league average.

Pablo Sandoval

2010
Total	Whiff	Contact	Swing
214	30	81	111
	14.0%	37.9%	51.9%

2009
Total	Whiff	Contact	Swing
758	94	328	422
	12.4%	43.3%	55.7%

------------------------------

2010 League Average
Total 	Whiff	Contact	Swing
4666	323	1889	2218
	6.9%	40.5%	47.5%

2009 League Average
Total	Whiff	Contact	Swing
5005	355	2107	2462
	7.1%	42.1%	49.2%

Remember, that this data is just for fastballs that are 2.5 feet or higher. I didn’t consider any other aspect such as horizontal location. Over the past 2 years, the league average hitter has whiffed about 7% of the time on fastballs that are 2.5 feet or higher. Sandoval has posted a 14% whiff rate this year on high fastballs — up from 12.4% in ’09. The league average hitter has made contact 40-42% of the time against high fastballs. Sandoval’s contact rate is down this year at 37.9% after posting a league average rate of 43.3% in ’09. One thing I found interesting, is that batters swung nearly half the time against high fastballs — Sandoval is above that rate in each year, especially in ’09 when he swung at the pitch 55.7% of the time. Sandoval was one of the swingingest (is that a word?) hitters in the majors last year. So, we shouldn’t be too shocked that he’s swinging at a lot of pitches. However, his swing rate is lower this year on fastballs at 2.5 feet or greater.

Sandoval’s K% is very similar this year as compared to last. He’s making contact at the same rate. But, it does appear that he’s missing the high fastball a little more this year. As compared to the league average hitter, he’s swinging and missing almost twice as much. What does it all mean? I’m not sure I can take anything away from this data just yet — that’s why I like to call it labwork. Hopefully, it’ll lead to bigger and better things. I think the numbers could be improved by better defining what is a high fastball.

So, I turn to you dear reader, when you’re trying to operationalize a term like “high fastball” what does it mean to you? I get the feeling that my current cutoff is a little too crude. Maybe use bins? Increase the height by something like 6″ or so, vertically, for each bin? And should I take into account the horizontal location of the pitch? I’m still trying to figure that out.

Hopefully Pablo can get himself figured out, too.

This one speaks for itself. A graph of fastball velocity by appearance from our favorite flame-throwing closer.

For now, Lincecum’s career high for K’s in a game came against the Pittsburgh Pirates in 2009. In that game, Lincecum pitched 9 innings while striking out 15, walking 3, and allowing 0 runs. If you’re wondering where that 15K games places Lincecum on the all-time list for most strikeouts in a single game by a SF/NY Giant starter (data goes from 1920 onward), well then, BB-Ref has your answer.

Gaylord Perry makes our list 3 separate times along with some other classic pitchers. If you’re a Giants fan, the names of Montefusco, Marichal, and Hubbell should perk your ears. The Schimdt game was compelling because of the way it ended. The Marlins, down by just 1 run, put two men on to start the 9th inning and Schmidt proceeds to throw a wild pitch that moves up both runners a base, now standing on 3B and 2B. Schmidt then struck out Miguel Cabrera, Josh Willingham, and Jeremy Hermida in order to end the game. It’s easy to forget sometimes just how dominate vintage Jason Schmidt was, but this game summed him up perfectly when he was pitching healthy.

If I was a betting man, I’d place a wager on Lincecum eventually breaking the 16 strikeout mark that Schmidt set in 2006.

Take a gander:

Yes, that’s what a 14.4 K/9 looks like. Romo struck out 106 in 66.1 innings while only walking 15 hitters. Funky motion, or not, you won’t see a better season from a pitcher’s standpoint anywhere. Romo was simply un-hittable for that year. Romo eventually made his MLB debut in 2008 at 25-years-old and, has since, been solid reliever for the Giants. In 79.2 career innings pitched at the major league level, Romo owns a 2.61 FIP that he’s paired with a 9.83 K/9 and a 2.15 BB/9. What’s been so vital to Romo’s success as a pitcher?

It’s an easy question for anyone to answer that’s seen Romo pitch: it’s his slider. By FanGraph’s pitch-type values, Romo’s slider has been worth 12.6 runs above average since 2008 — if you go by the 10 runs to 1 win rule, that’s a 1.2 win pitch for Romo. Romo possesses a frisbee slider that he throws from a few different arm angles and batters haven’t been able to touch the pitch since Romo entered the league.

The above graph indicates Romo’s slider usage this year split by batter handedness. Whiffs are represented by black circles and contact is represented by X marks. In 2010, Romo has thrown a total of 165 pitches — 67 of which have been the slider. Romo has thrown the slider 40% of the time this season, he’ll pair the pitch with a 2-seam fastball and the occasional changeup. Looking at Romo vs. right-handed batters, we can see a pretty typical usage for the slider. It’s generally in the lower half of the zone with most whiffs coming down and away from the batter. Against lefties, Romo has tended to work them away — or the “back door” slider — or down in the zone. I think from our graphs you can see the above-average control Romo has with his slider, he controls the pitch well and has tended to spot it in the right places.

More numbers on Romo’s slider:

* Of the 67 sliders Romo’s thrown this year, batters have whiffed on 18 of them. That’s a Whiff% of 26.8%.
* The league average Whiff% for all sliders (starters + relievers) thrown in the majors this year is 13.4%
* Romo posted a slider Whiff% of 14.2% in 2009
* The velocity range on Romo’s slider is between 77-79 mph

We’re looking at some pretty small sample sizes when it comes to pitches thrown and results, but Romo’s slider has been a fantastic pitch for him this year. It’s unlikely that he’ll continue to post a 26%+ Whiff% on his slider, but it’s seems likely that his slider will continue to be an above-average pitch for him. Whether or not he’ll have to add another wrinkle to his pitch selection as he progress through his career is another question that’s up in the air. Traditionally, Romo has thrown his slider almost half the time — 46% in ’09 and right around 40% this season — and batters have to know that when they are facing Romo, they’ll get a steady diet of sliders. And yet, they still have had trouble with the pitch. That makes the quality of his slider even more impressive, in my opinion.

As long as he’s healthy (my biggest concern with Romo) the Giants should have an above-average reliever on their hands. If Brian Wilson’s groin is still bothering him, you might even see Romo get a few save opportunities. For the pitcher with the funky motion and filthy slider, it’s well deserved.

What you’re looking at is Tim Lincecum’s fastball velocity by inning. The game data is from his first start — and victory — of the year against the Houston Astros.

Each red dashed-line indicates the end of an inning. So, you’ve got 7 dashed-lines indicating 7 different innings. At the start of the game, Lincecum was working 93-94, even touching 95 mph with his heat. His fastball velocity dipped between the 5th and 7th innings to 91-92 mph. He threw a couple of sub-90 mph fastballs in the 5th.

Note: Tim’s fastest heater on the night was clocked at 95.2 mph in the 2nd inning. His slowest fastball was 89.3 mph in the 5th.

There was some talk in the spring about Tim’s velocity, but it looked pretty good for most of the night. I really can’t see anything to complain about. With the development of his changeup, he’s not going to need to pump 95+ mph fastballs for 7 innings at time. Just enough to keep hitters honest.

Thanks to the magic (and nerdery) of PitchF/X we can answer that question. In 2009, Rowand swung at, and missed, the slider 63 separate times. Seems more than that, doesn’t it? For most of the season, the slider seemed to give Rowand a good bit of trouble. According to FanGraphs’ linear-weights pitch values, among qualified hitters in the majors, Rowand was worth -7.6 runs when hitting against the slider as compared to the average major league hitter against the same pitch. That placed Rowand as the 11th worst hitter in the majors last season against the pitch. Not an awful ranking, but one that indicates that Rowand could never get going against the pitch. If you’re wondering if Rowand has always struggled against the slider, it’s a mixed bag. The -7.6 runs in ’09 was a career worst ranking. It beat his previous low mark of -4 runs in ’08.

From 2002-2008 he has produced the following numbers against sliders: -3.2, 2.8, -1.7, -2.8, -1.4, 6.3, and -4.

Some highs (his 2007 with the Phillies) and lows (his recent struggles) but for the most part he’s been within a few runs of average. Further messing around with PFX tonight, I decided to plot all of the swings-and-misses that Rowand took in ’09 against the slider just to see what it looked like. Here’s the results.

I assume for a right-handed hitter, this is a pretty standard distribution. The slider that’s low and away seems to be the classic swing-and-miss pitch for RHB’s. Though, Rowand did miss a few sliders in the strike zone. To lay off the low and away slider it’s all based on split second pitch recognition. They say that you can identify a slider because of the “red dot” on the baseball caused by the spin of the seams. See dot, hit dot.

I also plotted sliders by called strikes and swinging strikes.

Green dots are called strikes, red dots are swings and misses.

If you’re wondering which hitter in baseball had the hardest time against the slider in ’09, using FanGraphs’ pitch-type values, it was Kevin Kouzmanoff of the San Diego Padres. His -16.3 runs against the slider was the worst for qualified hitters. By PFX data, he swung at the slider 82 times without making any contact. That’s nearly +20 swings and misses over what Rowand did.

For fun, I plotted his swings and misses to compare with Rowand.

Click to enlarge

Overall, looks pretty similar. There’s a tighter grouping of sliders in the bottom-right of the zone, but other than that, they look almost the same in terms of location. Kouz seems to go after the slider that’s away from him more than Rowand. Food for thought, I wonder how much variance hitters can have season-to-season against pitch-types? For example, Ryan Howard was the best in baseball against the slider this year with a score of +16.3 runs but that was after posting back-to-back seasons of -8.6 and -6.6 runs.

How has it happened? We don’t hit HR’s. We don’t walk. We’re as hacky as a team can get.

The answer lies in run prevention. Or, to put it another way, the Giants have been very good about not giving up runs to their opponents. As a team, the Giants have only given up 425 runs on the season. That’s the best in the majors. On offense, they’ve only scored 455 runs. That’s 2nd worst in the majors behind the Padres. If you want to park adjust things, the Giants should be the worst team in the majors at scoring runs. And while the Giants have played over their heads some — our Pythagorean record pegs us closer to a 60 win team than a 62 win team — the power of run prevention has made the Giants a poster team for why these things matter. And can matter a lot.

Let’s move on towards the graph. I’ve plotted each team in baseball by their UZR and FIP. This should let us see which teams are the best at run prevention (those who pitch well, and play good defense) and those who are the worst at run prevention (those who pitch and play defense poorly) and the teams that are in-between.

The bold lines indicate league averages. For UZR, this would be ’0′ runs. For team FIP, it worked out around 4.34 runs. Remember that the league average FIP will be higher in the AL because of the DH and slightly lower in the NL.

(Update: I’ve added a new version with team icons for each data marker)

Reading the Graph:

Upper-right Quadrant = Teams with above average defense and pitching. This is the most desirable quadrant to be in.
Upper-left Quadrant = Teams with above average defense, but below average pitching.
Lower-right Quadrant = Teams with below average defense, but above average pitching.
Lower-left Quadrant = Teams with below average defense and pitching. This is the least desirable quadrant to be in.

I’ve marked a few of the teams in each quadrant so that you can get a feel for how certain teams were placed.

Amazingly this season the Giants have posted the best defense of any team in baseball. That’s quite a boost from their ranking last year. In 2008, the Giants ranked as the 9th best defensive team in baseball. That’s above average, but they’ve climbed to the very top this year. Not only has the defense been great, our pitching has been very good, too. Only the Braves have posted a better team FIP (3.63 to our 3.73) this season. Defensively, the Giants have been on par with an excellent M’s squad. The Giants OF defense has been superb this year. Aaron Rowand has had a bounce-back season. Randy Winn, despite his struggles at the plate, is still a top OF defender in all of baseball. And the rest of the OF has been played by plus-defenders like Fred Lewis, Nate Schierholtz, and Andres Torres. OF defense is a major, major strength for our current team. This is why any attempt to play Ryan Garko in LF is a foolish idea.

Looking at other teams, the Braves have posted the best FIP in baseball but their defense has played below average. The Cubs are right in the middle as an average team when it comes to defense and pitching. The poor Royals rank as the worst defensive team in baseball by UZR. Their team FIP is better than the league average. The Royals would see some nice gains if they could boot players like Betancourt, Guillen, and Alberto Callapso. None of these players are good hitters, so there’s not much of a reason, on any level of debate, to keep them in the lineup — and in the field. The Orioles have defended and pitched poorly this season. They are one of the unfortunate teams stuck in the lower-left quadrant.

The Giants do need to improve their offense, because it’s hard to bank on Lincecum and Cain being this good every year, but if the team’s defensive abilities remain above average, the offensive improvement might be smaller than most would think.

This morning for Beyond the Boxscore I wrote an article detailing the results of the 2000 NL MVP race along with some observations on the Kent vs. Bonds debate that usually pops up among Giants fans.

I ranked the Top-5 Finishers by total runs, here’s the results in graph format:

(Click to enlarge)

You can read the rest on BTB, but it looks like there is quite the Rockies bias among MVP voters.