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Articles Tagged Regression 

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September 23, 2004 12:00 am

Playoff Odds Report, Redux

0

Clay Davenport

Using the feedback he received upon his re-launch of the Playoff Odds Report, Clay Davenport had made some changes to the system.

It turns out that I was delving into a feature that was widely read, very popular and taken very seriously. My article on the system's methodology generated more response than anything else I've written in ages.

I received many suggested improvements for the routine, some of which have been incorporated into the current system, some of which should be in there by next season (I can't see any reason NOT to run it from Opening Day next year, for everyone who asked that it start earlier in the season), and some of which I considered, looked into and rejected. Some of the changes I've made were trivial to the calculation--a better algorithm for figuring out who won and tied for division championships and wild cards, for instance, is good to have, but doesn't affect the estimates themselves. Among all the suggestions, though, no one noticed what turned out to be the biggest flaw in my original setup.

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June 29, 2004 12:00 am

You Get What You Pay For

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Ben Murphy and Jared Weiss

Inherent in the desire to develop better baseball statistics--and as a result, improve baseball analysis--is the belief that this information is not only available but also not being used by the men and women who run baseball. As Moneyball and the resulting reaction has showed, some General Managers seem to be using the same methods for performance evaluation that were used 20 or 40 years ago. It therefore stands to reason that GMs are paying players not for actual performance, but rather for perceived performance as viewed through the rusty and decrepit glasses of decades-old beliefs about the statistics of the game. For this study we wanted to find out if General Managers were, in fact, paying players along the lines of their objective "value" (as defined by VORP), or if there were something else in play.

Inherent in the desire to develop better baseball statistics--and as a result, improve baseball analysis--is the belief that this information is not only available but also not being used by the men and women who run baseball. As Moneyball and the resulting reaction has showed, some General Managers seem to be using the same methods for performance evaluation that were used 20 or 40 years ago.

It therefore stands to reason that GMs are paying players not for actual performance, but rather for perceived performance as viewed through the rusty glasses of decades-old beliefs about the statistics of the game. For this study we wanted to find out if General Managers were, in fact, paying players along the lines of their objective "value" (as defined by VORP), or if there was something else in play.

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June 30, 2003 12:00 am

Estimating Pitch Counts

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Ted Kury

Using a database of 30,000 starts from 1994 to 2000, BP corrspondent Ted Kury introduces a new model to estimate pitch counts per start from historical and minor league games.

Using data commonly available in newspaper box scores, e.g., innings pitched, hits, runs allowed, earned runs allowed, walks, and strikeouts, we can derive estimated pitch counts. In addition, we will look at how the designated hitter impacts pitch counts.

The Raw Data

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May 6, 2003 12:00 am

Doctoring The Numbers: Hot Starts, Part III

1

Rany Jazayerli

Welcome to the third and final instalment of my look at the meaningfulness of the first few dozen games of a team season. (Go back and review Parts 1 and 2 here. There will be a test later.) This final article looks to merge a team's starting record with its established performance over the past few years, to come up with a formula that most accurately projects its final record based on the available data. Warning: If you thought Part 2 was laden with too many equations, you're not going to like Part 3 any better. I ended Part 2 with a projection that the Royals, based on their 17-5 start, are projected to finish with about 97 wins. The folly with that logic should be self-evident, but let me share some evidence with you to make the point a little more clear. When the Royals' record reached 13-3, my inner circle of fellow Royals fans finally got serious about questioning whether such a strong start really meant anything in light of the team's 100-loss season in 2002. I decided to look for comparable teams throughout history that had gotten off to a similar start. Using my database of all teams from 1930 to 1999, I found a total of 75 teams that started the season either 12-4, 13-3, or 14-2. Sixty-three of those teams, or 84%, finished above .500. As a group, they finished with a .545 winning percentage. But it's not all roses. Because I then whittled down that group to look only at those teams that had played less than .420 ball the previous season, which corresponds to a 68-94 record or worse.

I ended Part 2 with a projection that the Royals, based on their 17-5 start, are projected to finish with about 97 wins. The folly with that logic should be self-evident, but let me share some evidence with you to make the point a little more clear.

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