Archive for Giants

Following a disastrous 0-6 start that saw him allow 56 baserunners in 28.2 innings, the Giants demoted Barry Zito to the bullpen. How bad was his start to the season? His average game score, which measures the in-depth quality of a start, comes in at 34; with game scores, 50 is the starting point for quality. He struck out just 11 batters while walking 15 and surrendering four home runs. Though his FIP of 5.81 suggested a 7.53 ERA may have been too harsh, 5.81 is not going to help a manager sleep at night.

Prior to a game against the Phillies, cameras spotted Zito getting advice from the venerable Jamie Moyer. I guess since Zito is already pitching like a 70-year old lefty he might as well learn how to be effective as one. Or maybe they were talking about Moyer’s favorite episode of Dharma and Greg.

Either way, Zito’s demotion did not last long as he made no relief appearances and was given the ball to start last night. Perhaps the demotion served its purpose as a wakeup call or one of those trips to the disabled list with a phantom injury.

As the title of this post suggests, though, Zito actually pitched pretty well. Generally a fastball, curveball, changeup pitcher, Zito had been struggling with velocity; if his fastball lacked speed there would not be enough of a separation between that and the changeup. Additionally, if hitters knew he had a weak fastball, he could not utilize it to keep them off guard; therefore, his curveball would look like hanging junk instead of the devastating out pitch it used to be.

In his previous start, April 27th against the Reds, Zito got clocked with a fastball ranging from 80-82 mph. In fact, some of his fastballs were so slow that the classification algorithm mistook them for changeups. Last night, however, against the Pirates, the Pitch F/X data says that the vast majority of Zito’s heaters came in the 84-86 mph range.

He threw a first pitch strike to just 7 of the 18 batters that did not put it in play on the first pitch. Despite this, he only walked two batters, and recorded a season high five strikeouts. Of these strikeouts, he did not follow a pattern in using a specific out-pitch but he did use his curveball as a major device. If he didn’t strike a batter out with the curve he would use it to set up the following pitch. All five of these strikeouts came from either a curveball or a sequence set up by the curveball.

His changeup was quite effective last night, however two poor ones resulted in the only two runs he surrendered; essentially, these hanging changeups handed him a seventh loss. Throwing it exclusively to righties, here is a location chart:

The circled pitches are the two hits that cost him: a single and a home run in the fourth inning given up to Jason Bay and Xavier Nady respectively. The home run came on the pitch with the larger circle.

Here is a look at Zito’s movement last night:

Though a few of his curveballs lacked efficient movement the larger majority moved quite a bit. Very interesting is his fastball movement. Last night it averaged around five horizontal inches and twelve vertical inches. Here is his movement from the 4/27 start:

Here his fastball averaged about three horizontal inches and eleven vertical inches. Not only has his fastball lacked velocity but apparently it has also lacked sufficient movement to garner some positive results. His changeup was much more consistent last night as well.

Hopefully, for the sake of Giants fans, Zito can build on this in his next start. While he is still on pace to at least tie the all-time losses record (29), this particular loss must have been pretty uplifting for his confidence.

This is the fourth installment in a series of articles detailing Matt Cain’s starts. Based on the quality of his games pitched and his decisions or no-decisions earned, Cain’s 2007 was the unluckiest season of at least this decade. Seeing as the Giants have a bleak outlook this trend should continue.

His first three starts followed an extremely simple pattern of: good, bad, good. In pure Cain fashion, he did not receive a decision in either good game but earned the loss in his poorly pitched game. To get caught up on his season visit any of the following links:

• Cain Watch #1
• WPA, 4/1/08
• Cain Watch #2
• WPA, 4/7/08
• Cain Watch #3
• WPA, 4/12/08

He made his fourth start on April 18th, a game in which bad luck never had a chance to interfere due to Cain’s poor performance. His line of 3.2 IP, 8 H, 9 ER, 3 BB, 4 K led to the following lopsided game graph:

For the season, Cain is averaging the following rounded numbers per start: 5 IP, 4 H, 4 ER, 4 BB, 5 K. There has been quality as he has had two very good starts; however, his bad starts have had much more of an effect on his season to date. Let’s compare this to last April, when, through four starts, Cain had the following averages: 7.1 IP, 2.8 H, 1 ER, 3 BB, 5 K. The only stagnant number is the strikeouts; everything else is worse now than a year ago. So what’s the difference?

He is throwing 57% first-pitch strikes, which is the same as last year and higher than his previous two years, but his overall percentage of strikes has dipped from 63% to 60%. Batters are swinging at 73% of his pitches, down from the 75% last year, however they are making contact 84% of the time; last year the contact rate was at 81%. Putting this together, Cain is throwing a lower percentage of strikes while maintaining his rate of first-pitch strikes, but batters are swinging less and making more contact. This helps to explain why his baserunners allowed have increased.

I’m currently building my own Pitch FX database and will begin to incorporate his data in that area into future looks at his starts. His next start is scheduled for April 23rd, when he will face-off against Greg Maddux for the second time this season, this time at the spacious Petco Park. His flyball and groundball percentages have lowered this year while his line drive percentage has risen. Though he has not given up a ton of home runs in his career, three in his first four starts shows some susceptibility; limiting his walks will help reduce two-run and three-run home runs to those of the solo variety. If he cannot rebound from this start and get onto some type of consistency track then luck will not be a factor in what will amount to a poorly pitched season.

Taken directly from the FanGraphs Glossary, WPA is the difference in win expectancy (WE) between the start of the play and the end of the play. That difference is then credited/debited to the batter and the pitcher. While venturing to a website like this implies prior knowledge of WPA I always like to err on the unknowing side. Since baseball is zero-sum game, everything positive is cancelled out by something negative; a home run is very positive for the hitter but equally negative for the pitcher. Due to this, the WPA of a winning team in any given game will add up to +.500; that of a losing team will be -.500.

Keeping this in mind, let’s take a look at this afternoon’s Diamondbacks/Giants game:

The matchup of Brandon Webb and Barry Zito ultimately resulted in a 4-1 Diamondbacks victory and, according to WPA, it was pretty much all due to Brandon Webb. The former Cy Young Award winner went for 8 IP, 3 H, 1 ER, 2 BB, 5 K, and a pitching WPA of +.337. On top of that, as evidenced by the graph above, Webb also added a two-run single. His hit put the DBacks ahead 2-0 and turned out to be the biggest play of the game; the WPA for the single play was +.165. Since the hit proved to be so significant Webb ended with a batting WPA of +.210.

Add both of them up and Webb’s WPA comes to +.547. As mentioned at the start, the net sum WPA of a winning team will be +.500.

Webb not only shut the Giants down for eight innings of great pitching but added the biggest offensive play of the game; the LI of his at bat was 2.96. Of course, watching the game or highlights of it would explain that it was not a laser sharp single, but the fact is that the blooper fell in, two runs scored, and that was all Webb needed.

The problem with looking solely at WPA in this case is that Webb’s single came with the bases loaded so he could not have knocked in the runs without his teammates doing their part to get on base. This is where WPA/LI comes in. The stat also goes by the nickname “context neutral wins” and tracks the contributions with the Leverage Index aspect removed. It is not calculated by dividing the overall WPA by the overall LI but rather dividing the WPA and LI of every single play and then adding everything together. With regards to this particular game, and Webb’s single in particular, the WPA and LI were high because the situation existed as a result of others getting on base. Webb had nothing to do with them reaching base and so using WPA to determine whether or not he single-handedly beat the Giants would not necessarily be accurate; the WPA/LI would determine exactly what he individually contributed to the game.

Looking at the WPA and LI of each play in this game, Webb’s WPA/LI from a pitching standpoint adds up to +.328, not much different than the +.337 WPA. His hitting, however, lessens quite a bit due to the context that padded his batting WPA. From a context neutral standpoint, his batting WPA/LI comes to +.067. Though still qualifying as a positive contribution it is much less than the +.210 WPA. Overall, adding them together, Webb’s WPA/LI for this game was +.395. While he did not single-handedly beat the Giants he would definitely win the Game MVP award for contributing much more to his team’s victory than anyone else.

I posed this in the comments thread of the Appreciating Pat Burrell article but feel it is an important enough question to merit its own post. In an NPR interview, author Dan Gordon discusses the psychology of die-hard fans in an effort to promote his new book, Your Brain on Cubs. Towards the 31-minute mark of that interview Gordon says something interesting: He essentially says that Cubs fans are able to stay dedicated because they have come close many times to the World Series and so the fans know how sweet it will be when the team eventually wins a championship.

I want to combine this thought with something I heard last year on the radio and bring forth a question. Quite simply, would you rather be a fan of a team like the Marlins or the Giants? Not necessarily the specific teams or how they look in 2007 and 2008, but would you rather be a fan of a perennial contender for eight years or a team that would win two world series in that span and be below average the other six years?

The Giants had a winning record every season between 1997 and 2004, finishing in either first or second place; their average record in that span was 92-70. They made the playoffs four times and were within two games of either the division or the wild card in three of the other four seasons. The Giants made the playoffs or fell just short in seven of the eight years in that span. The Marlins, on the other hand, had winning records in just three of those eight years. In 1997 and 2003, when they won the world series, they won 92 and 91 games respectively; in 2004, a year removed from their second championship, they went 83-79, just barely breaking .500. Their average W-L in that span is 77-85.

Now let’s revisit the question posed at the start of the post. Strip away what we currently know about the Giants and Marlins: The actual teams are irrelevant and we need to focus on the type of team each is to answer properly. Would you rather be a fan of a team that would go 92-70 each year and give you a shot at the playoffs and/or world series, but not necessarily win a championship? Or would you rather be a fan of a team that would go 77-85 every year, but would step it up to 90+ wins just twice and win the world series in both of those seasons?

On the one hand you have the idea of winning two championships which, I’ll admit, I’ve never felt as a Phillies fan. Then again, on the other hand, you have the idea of whether or not you would even watch your team if they went 77-85 or worse in several consecutive seasons. For instance, I know that last year, I cared less about what the Phillies did in the playoffs than I did that they simply got into the playoffs. I’m curious to hear thoughts on which team would have a bigger Web-fandom.

This is something I began over at Statistically Speaking but it makes more sense to continue here at Fangraphs. Giants pitcher Matt Cain had an historically unlucky season in 2007, posting statistics similar to, if not better than, most NL starting pitchers. And yet, at the end of the season, all he had was a 7-16 record with no true consolation prize. Via my Net Luck Rating statistic–which measures the quality of decisions and no-decisions by evaluating each start as a separate commodity–it was the unluckiest season of the decade. Based on the quality of his starts and his frequency of well-pitched games Cain would have gone 16-7 in his decisions if pitchers were awarded wins for every well-pitched decision and losses for every poorly pitched decision.

Based on how bleak the outlook appears for the Giants I have every reason to believe the string of bad luck will continue. That being said I have decided to track each of his starts. To read the recaps of his first two starts, click any of the links below:

• Cain Watch #1
• WPA, 4/1/08
• Cain Watch #2
• WPA, 4/7/08

Cain’s third start of the season proved to be the perfect example of his lack of luck. Here is the graph of the game:

To recap, Cain pitched 6.2 innings, surrendering three hits and two earned runs; he also walked three and struck out five. At the time of his departure in the seventh inning Cain had a 5-2 lead. Oh, and do you see that little red dot in the graph above in between the sixth and seventh innings? If so, you read correctly: Matt Cain also hit a home run in this game.

After Cain’s departure, Jumpin’ Jack Taschner (it’s a fun nickname, admit it) hit Rico Washington before Merkin Valdez got Ryan Ludwick to fly out. After seven full innings the Giants led 5-2. Some Tyler Walker, Brad Hennessey, and Erick Threets action later and the Giants found themselves extra-inning losers by a final score of 8-7. Sigh. Poor Matt Cain.

In terms of WPA, Cain contributed .286 in the pitching department and .190 in the hitting department; for the game that adds up to an accumulative WPA of .476. Considering that the winning team will add up to a .500 and that the Giants eventually lost the game, the team had to do a lot wrong to lose. A cursory scan of the bullpen WPA for the game supports that: Threets chimed in with a -.292, Walker with a -.318, and Hennessey with a -.434. The efforts of these three not only erased Cain’s efforts but doubled over in the negative direction.

This was definitely a game Cain should have gone onto win but will go down as a too-familiar great start but no-decision. For the season, Cain is now at: 3 GS, 16.2 IP, 13 H, 6 ER, 12 BB, 15 K, 3.24 ERA. Based on his WPA, Clutch, and WPA/LI Cain is currently very comparable to Johan Santana. Despite pitching well in two games, and poorly in the other, he is 0-1. The saga continues.