Six Sigma and Baseball?

[Beast Light]

After coming to grips with a better understanding of six sigma and statistical process control, I am wondering if it could be applied to baseball.

 

Perhaps it could be used to detect processes that "out of control" and signal the early stages of slumps before they are actually deemed "slumps".

 

I also think that by gathering random samples from a players history of perhaps 14 consecutive at bats, a person could compute a range and confidence level that a player will perform in that range.

 

I know that applying six sigma to baseball would not help players hit, unless it could help them to detect slumps in their early stages and work out kinks faster, but it could definately be of value in determining what players are the most consistent and what players have wider ranges of performance according to their samples. If a team is looking to sign a FA, and is looking for someone who is beneficially consistent, they could use some of the philosphies of six sigma to find them. These FA may also be flying under the radar and come at lower costs.

 

The other question to be determined would have to be whether or not a consistent player is better than an inconsistant, within reason of course. Would you rather have a player on your team who will hit 1 homerun every week, or would you have a player that can hit 4 in a week every 4 or so weeks and carry a team for a period of time.

 

I have plenty of details that I could go into and I plan on trying this out over my winter break. If anyone is actually interested in this topic, I will elaborate, however it would be senseless for me to ramble on if no one cares. So, does anyone care? Has anyone ever tried this before?

[rluzinski]

Perhaps it could be used to detect processes that "out of control" and signal the early stages of slumps before they are actually deemed "slumps".

 

The whole notion of slumps and consistancy is largely a function of the random distribution of probabilistic events.

 

To study this matter, statisticians model ABs as a Bernoulli Trial:

 

Quote:

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The Bernoulli trials process, named after James Bernoulli, is one of the simplest yet most important random processes in probability. Essentially, the process is the mathematical abstraction of coin tossing, but because of its wide applicability, it is usually stated in terms of a sequence of generic trials that satisfy the following assumptions:

 

1. Each trial has two possible outcomes, generically called success and failure.

 

2. The trials are independent. Intuitively, the outcome of one trial has no influence over the outcome of another trial.

 

3. On each trial, the probability of success is p and the probability of failure is 1 - p

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Bernoulli Trials

 

It's essentially a coin flipping model. So, we say that a .300 hitter has a 30% chance of getting a hit during every AB (While this is an obvious simplification, it still works very well). We know that for every 10 AB the batter "should" get 3 hits. Anyone who's flipped a coin for fun knows it doesn't work that way, however. For every 10 AB, a .300 hitter will only get 3 hits 27% of the time. That's based off a binomial distribution, which a bournoulii trial follows:

 

You can have hours of fun with this link:

 

Binomial Distribution

 

n = # AB

p = batting average

x = number of hits

 

Hot and cold streaks can almost always be explained by the binomial distribution. Using only a handful of AB allows for a huge variance in performance.

 

Check out the article below for a more in depth look on this subject.

 

Tony LaRussa and the Search for Significance

[JeffSackmann]

I just read the chapter on streakiness in "Curve Ball" by Albert & Bennett (both of whom are professional statisticians). They show that some teams / some players can actually be "streaky" -- that is, streakiness isn't entirely a mirage created by small sample size. They show that Todd Zeile (a notoriously streaky guy) performed much more like a hypothetical "streaky player" than a hypothetical "consistently player." Too much to go into here, and I don't know anything about six sigma, just wanted to point out that you can't entirely write off streakiness.

 

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www.BrewCrewBall.com

[rluzinski]

just wanted to point out that you can't entirely write off streakiness.

 

I didn't. My exact words were, "The whole notion of slumps and consistancy is largely a function of the random distribution of probabilistic events."

 

99% of what the media calls a streak or slump is just a flip of the coin.

[Jimbo]

After coming to grips with a better understanding of six sigma and statistical process control, I am wondering if it could be applied to baseball.

 

I would say in Geoff Jenkins' "Red X' early in 2005 would have been hitting while with RISP. >:

[Jimbo]

Perhaps it could be used to detect processes that "out of control" and signal the early stages of slumps before they are actually deemed "slumps".

 

Are you familar with Cu-Sum charts? I think p-charts would be hard to apply.

[Beast Light]

Quote:

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Are you familar with Cu-Sum charts? I think p-charts would be hard to apply.

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No I am not. Please enlighten me! I am an operations management major and quality control/assurance falls under my qualifications. I am always looking to learn new things!