Defense, Pitching, Risk Aversion

Project/Research Ideas

In my final semester, I’m obligated to complete two projects, so I thought, why not center one of them around baseball data? So far, my inclination is to use regression analysis to hone in on some baseball questions that I’ve been pondering about lately. Here are some of my ideas, with problems/conflicts arising from further thought included:

Assessing Starting Pitcher’s Risk to Injury

This is a clear issue in baseball. With guys like Stephen Strasburg going into Tommy John surgery (a serious surgery that take 12-18 months to recover from), it’s in the best interest of team executives, players and fans alike to find reasons behind why many young pitchers are blowing out their arms. With this in mind, I believe there are two ways to use regression to learn how to keep these players healthy.

  • We could use past injury data as our explanatory variables. This seems intuitive, as past-injuries would seem a good indicator of how likely you will be injured in the future. Thus, it seems a bit redundant analysis, and the only real conclusion that I see likely occurring is ‘once injuring your throwing arm’s elbow, you’re screwed.’ There’s gotta be some more in depth conclusion we can come up with.
  • Pitching mechanics. There’s a ton of debate as to how much pitching mechanics really determine injury risk. Some argue good mechanics will help a pitcher last 20 years (the Greg Maddux or Jamie Moyer fans), but some also say if you change a young pitcher’s delivery (like King Felix), he may not have the success on batters. The issue with this is, where’s the data? How can I quantify pitching mechanics? So far researching this, I could probably make a bunch of parameters for pitching styles, like average speed on pitch types, pitching angle, right-handers vs left-handers, ball movement from pitcher’s release to home plate. Things like that may give us useful knowledge in what differentiates Mark Prior from Justin Verlander (two highly regarded young pitchers, but with Prior known for his past injuries). But in general, this data doesn’t exist (to my best knowledge).

Game Theory: Batter vs. Pitcher over the course of one game, or a career

A starting pitcher will generally face a batter at least 3 times before being pulled from the game. Thus I would argue at-bats are correlated with one another, since past at-bats give a pitcher or batter a better understanding what their foe will do in the next at-bat. Say if a batter strikes out his first time up, will he know what to do next time in his approach? Or if a pitcher gives up a home run to a batter, will he understand not to make the same mistake again? These questions scream game theory, and it’d be interesting to look at data for several pitchers vs batters to see which players learn more from their mistakes or failures.

Probability of a successful defensive play

It’d be cool to simulate defense, and be able to compare players’ defense skills. Assessing defensive skills is a huge problem in baseball, as there are a lot of variables and circumstances that make one ball put in play different from another. Currently, defense statistics are out there, but are very limited and still don’t say a lot when comparing players. Variables to regress on the outcome of a play would include type of ball hit (this includes ground balls, line drives, fly balls), angle of ball hit, ball speed/ drop rate, defensive ability of player, type of pitcher on the mound, etc.

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    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.

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    Risk Aversion

    Risk Aversion in Baseball?

    People are risk averse. For example, we buy insurance plans so we’re not stressed too much about paying for car accidents or breaking a laptop. It’s a pretty big human characteristic; people like decreasing risks even though the probability of bad events occurring is relatively low. The high costs of paying for medical bills or paying for fire damage on a house is just too much for people to fathom, and thus that’s essentially how insurance companies make their money off us.

    In baseball you see the exact opposite behavior from General Managers (GM’s). Instead of a consumer’s tendency to pay for insurance coverage, managers generously give to players in return for something never guaranteed: production on the field. I’ve listed and summarized below three main components of risk in the development, and signing of baseball players.

    Signing free agents.

    All teams need to sign free agents every off season to keep competitive, yet there are always contract agreements that baffle the typical fan. In many ways, you can’t fault the team for giving a player too much money; it’s the bidding war market and the suave talk of agents that inflate a player’s worth to a team. Many players find an incentive to increase their productivity in seasons heading into free agency, attempting to legitimize a hefty raise. This leads to an over-dramatization by  sports agents to paint a picture of exponential increases in production in all stat categories. What teams fail to see is that not even last year’s production numbers are insured. Barry Zito was given the insurance of making on average $18 million for the next 8 years, while the true ace of the Giants, Tim Lincecum, is making $650,000 this year. Obviously, Lincecum will get his payday in due time, but in pure production numbers, it’s evident Zito is not even worth half his salary. Last year, Zito won his first game two months into the season.

    Addition of prospects to a ballclub.

    Prospects signing through the MLB draft are often given huge bonuses (especially those drafted in the first round) despite never playing a single professional game. Sound familiar to the likes of free agents? Once again managers are willing to take risks on high school, college players who might not even get a chance to play in the majors for at least another year.  More interesting, is when managers are willing to trade their elite players for a batch of young prospects. It’s essentially trading in your money for a bond that will become liquid in four or five years. Except that it might or might not be there in most cases. Prospects are always desirable. Except that they have never proven themselves in the highest levels.

    Baseball players are injury prone.

    You never know what will happen. A lot of players have made fortunes while going through injuries for years. These players are paid millions while frustrating both management and themselves for chronic back spasms or elbow surgeries. Carl Pavano signed a 4 year $40 million contract with the Yankees while in return, gave them back 21 starts, less than two-thirds of a season.

    All in all, it’s obvious managers must take these risks in order to keep their business running. Fans love to see their newest acquisition. Big names bring out the richest of fans, go to lavish yankee stadium and see their $200 million payroll play against the likes of $50 million Cleveland ballclub. In fact, it could be argued that these risks show how players are risk averse. They won’t play a game until they are guaranteed a salary they deem as the market price for their services.

    What would it look like if businesses ran by the likes of baseball teams? Every worker would be given guaranteed money while never having to worry about getting the next expense report out, or the next project.

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