Defense, Pitching

Batting Average on Balls Put in Play

First, I’d like to give an obligatory hat tip to the San Francisco Giants for winning the World Series against the Texas Rangers, 4-1. Despite my inner-feelings to not root for you (due to my allegiance to the A’s), that was one of the best pitching performances of post-season history, probably since the 2001 Arizona Diamondbacks. Despite losing, Texas has a lot to be proud of. They continued to play their type of baseball day in and day out.

The subject for tonight’s post is a metric not many casual baseball fans know of: batting average on balls put in play (or from hereon, BABIP). It essentially answers the question, out of all the balls a player hits that are field-able by the defense, what percentage of balls will fall for a hit? Note, this is different from a regular batting average, which includes strikeouts and home runs.

Baseball statisticians love this metric because, for obvious reasons, pitchers are not always in control of the amount of hits they allow in a game. There’s just too many factors that can affect the outcome of a hit: Hard line drives are caught by diving center fielders, a bloop single can fall between defenders, ground balls can barely get past the glove of an infielder. When these ‘are you serious?’-hits are allowed, we kind of assume tough luck has graced the pitcher. And when we see excellent defensive plays, we think the pitcher is lucky and fortunate to have player X in the outfield. How many times have you seen this happen in baseball games? Too often.

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Stop Praising Brian Sabean

Sorry but I’m a little tired of hearing how Cody Ross was a brilliant move by Brian Sabean, the General Manager of the Giants. I’d like to note the obvious before I ramble: no one expected half of the production that Ross has given the Giants while on his way to win the NLCS MVP award. I’m not doubting his production or anything.

What I am doubting is the good foresight by Sabean in acquiring Ross. If you don’t know, the Giants got Ross by claiming him off waivers from the Florida Marlins. Waivers works in a way that any team can claim the player, but the waiver is awarded to the team with the worst record, who is also in the same league. For example, if a winning-record team from the NL claims Ross and so does a losing-record team from the AL, the waiver is still awarded to the team from the NL. That’s just how the system works. At any rate, I find it hard to believe Sabean claimed Ross on the belief he was going to go on a rip in the playoffs. The Giants didn’t even need an outfielder, as they had a lot of depth at the position. So why do it?

For one Sabean had to know the San Diego Padres were interested in acquiring Ross. The simple fact is Sabean blocked the Padres from getting the guy (since the Padres at the time had a better record than the Giants).

I’ll admit this was a fantastic move if you’re playing chess, or you’re studying game theory. But please don’t praise Sabean for his foresight, as this required none of it. I think any businessman would have done the same thing: block your competitor from receiving the right supplies. Simple as that. Now I have little proof that the same thing occurred with Pat Burrell, but the Giants definitely lucked out with Burrell feeling allegiance to his hometown team (Burrell grew up in San Jose, CA).

This is another reason why I think the Giants are astonishingly lucky this postseason, offensively. While I admit they are on a tear right now pitching wise, and they look pretty good in the World Series, please don’t praise Brian Sabean for the great luck that has blessed the city by the bay.

Note: I covered instances where random role players have given their teams enough offense to win games in the postseason, but none as wild as Ross, who has only been with the Giants for 2 months, while those other random MVP-winners were with clubs the entire season.


Starting Your Best Player, Third

I wanted to get this post out before the start of tonight’s game 6 game consisting of New York trying to force a game 7 against the Texas Rangers. There was an article on Fangraphs (that you can find here) last week discussing the effects of starting Cliff Lee (the Ranger’s best starting pitcher option) in games 3 and 7 (in game 7, if the series goes that far). A lot of writers have been chiming in discussing how starting Cliff in those games puts Texas at a disadvantage, since the game 7 start is not guaranteed. Thus the disadvantage stems from sending the best pitcher in the postseason out only once.

To summarize the article, Dave Cameron points to the idea that, assuming Cliff can win both his starts, the Rangers need to find ways to win at least two non-Cliff Lee games. Winning these games is independent of when Cliff Lee starts. Albeit, pitching match-ups are important, the message is still clear and simple: the Rangers still need to win two non-Cliff Lee games.

This discussion got me thinking more broadly about the psychology behind 7 game series.

The fact is most people view the goal of a 7 game series is to win 4 games first. Through the first 4 games of both championship series, teams were up 3-1. And then in game 5’s, both series went to 3-2. While most fans believe there’s bad history in clinching a series, the fact is the order of games won doesn’t matter. Each game is independent. For example, coming back from a 3-1 deficit to win a series would be the same as teams alternating wins to force a sudden death game 7. Maybe hearts are broken in the former, but the outcome is the same. All I’m trying to say is if New York or Philadelphia end up going to the world series, don’t be too sad, Texas/SF fans that your team couldn’t just win one more game. The order of the games won shouldn’t matter.

I think to prove my point, series would have to be played through 7 games, no matter if a team wins the first four (or any other combination of wins-losses that doesn’t force a game 7).

But the mentality of being one win away from advancing can be pretty heart-breaking when you still don’t advance. But I just don’t see the necessity in calling it ‘bad history’ when games are won independently of each other.

Pitching, Risk Aversion, Salaries

Lincecum and Arbitration

Tim Lincecum is currently in his first year of arbitration with the Giants (If you don’t know what arbitration is, look at this post). In a short synopsis, it is speculated Lincecum will file for anywhere between $8 and $24 million for his one year contract. How it works is that Lincecum has to file what he believes he should get as salary, and the Giants can either accept the offer, or offer him something else (which is usually  a lower salary). What’s important to note is both numbers will correlate as to what each side believes Timmy is going to be worth for the 2010 season. if both sides can’t agree to a salary, they both go to court and argue their sides for a correct amount.

What’s cool is that Lincecum has a lot of space to work with, as to what will actually be granted to him through this process. If he asks for way too much (like upwards of $24 million), then the Giants could get a huge discount (say $12 million) if the court sides with the Giants. However, if he asks for what is probably his worth (say $18 million), he’s probably leaving a couple million dollars on the table. So it’s an interesting game theory model in which both sides must also think about what the other will do in certain situations, the interdependency of choice. What’s best for both sides is coordination, yet the uncertainty of what the other will do causes conflict and may result in giving Lincecum either more or less of his true worth.

Here’s a good summary of the figures, taken from an article in Baseball Prospectus yesterday:

I think Lincecum will win $18 million, hands down, but that’s a different question as to what he should offer. The arbitration panel picks the offer (the team’s or the player’s) that they believe to be most correct. If the Giants propose $12 million and Lincecum goes $18, Lincecum wins. But, he also could win if he goes as high as $24! To suggest $18 million would be to leave possibly $6 million on the table. Now, I don’t think the Giants will go that low—they will go under $18 though—so, I wouldn’t recommend $24 million, but I think Lincecum will ask for more than $18. How much more has to do with factors that I know nothing about. Have the parties discussed figures for a long-run contract? I suspect they both know something about what the other party might offer.

It’s the same exact negotiations any business goes through in evaluating promotions and raises. What’s more important, the number of years serviced to the firm, or how much the employee has increased revenue in the past, even if it has only been one or two years.


Pitchers & Volatility Levels

In the past two weeks, Brad Penny and John Smoltz, both very experienced veteran pitchers, were released by the Boston Red Sox. Signed during last season’s offseason on incentive based contracts, the Red Sox nation bought low for pitchers with lots of question marks.

Smoltz’s season with the Red Sox can be described as disastrous. Here was his line with the New England-ers:

2 Wins, 5 Losses, 40.0 Innings Pitched, 59 Hits Allowed, 37 Runs Allowed, 8 Home Runs Allowed, 33 Strikeouts, 9 Walks Given, 8.32 ERA, 1.70 WHIP, .343 BAA

Yeah, over 40 innings, Smoltz looked like an aged man who could not locate his pitches where he wanted them. His velocity was there, but location was the key flaw that many saw in his pitching for the Red Sox. But the key question is, has Smoltz digressed to become a bad pitcher? A good article to look over (if you have time) compares Smoltz’s past 40 innings to Jered Weaver’s (a 26 year old pitcher who, many believe, has a bright career ahead of him) past 40 innings. The article bases its argument on the fact that a sample size of 40 innings is very small; too small to judge whether a pitcher is performing at his true talent level. Why is this important?

A pitcher’s volatility level is rather high, even for above average pitchers. Meaning a pitcher’s performance fluctuates a lot from game to game. Let’s look at Penny’s and Smoltz’s debuts with their new teams:

Penny for the Giants: 1-0, 8.0 IP, 5 H, 0 R, 2 K, 1 BB, 0.00 ERA, 0.75 WHIP

Smoltz for the Cardinals: 1-0, 11.0 IP, 7 H, 1 R, 15 K, 1 BB, 0.82 ERA, 0.73 WHIP

Now those are stellar numbers. See the fluctuation? I wouldn’t be surprised if either is able to ride this stretch for another 3 or 4 starts. If they did, it would help bring them back to numbers that coincide more with their career averages.

To further my case, let’s look at two pitchers: Tim Lincecum and Joe Blanton. One is the reigning Cy Young winner (an award for best pitcher in the league), the other is known as a number 3 starter, an average pitcher. Their ERA’s differ by more than a 1.50 (2.33 vs. 3.88 respectively). By finding the standard deviation of runs given up by the pitcher by game, we can see how volatile their performances are. Lincecum stands at a 2.86 while Joe Blanton is at a 3.86. What does this tell us?

Despite Lincecum’s status as the best pitcher in baseball, there’s a substantial chance he could give up 2.86 runs more than average, while Blanton could give up 3.86 runs less than his average. This assumes some sort of standard distribution, but you get the point. The probability of Lincecum allowing +2.86 extra runs and Blanton allowing -3.86 less runs is equal to the flipside. So much can happen in a game, a so-so pitcher can outright dominate the game while the stellar workhorse can have an off day. It’s amazing how teams will pay premiums for above average pitchers, even below average ones! Why spend +$10 million for a pitcher who will equally give up either  1 run or 5 runs in one game when you have a minor league spot starter who can guarantee the same performance?

EDIT: Another great example of the volatility we see in pitchers.