(The thread title should probably read "How do you reproduce Linear Weights?")

I have a pedagogical question.

I understand that Linear Weights have been around for years and their values are pretty much agreed upon. I am writing an example for some Linear Regression software and thought it would be cool if I could reproduce the coefficients.

I plugged in team data from both leagues 1946-89 into a Least Squares Zero-Intercept Linear Regression model with R as the dependent variable and ABminusH,1B,2B,3B,HR,BB,SO,SB,CS as the independent variable and trained. I got the following coefficients:

0.51 : 1B

0.68 : 2B

1.21 : 3B

1.48 : HR

0.37 : BB

0.17 : SB

-0.22 : CS

0.0007 : SO

-0.10 : Outs

One one hand, I was pleased that this sort of looks like the right answer. I did no special massaging of the data, just using the software as a black box. The near-zero value of strikeout was fun to see. On the other hand, I notice some sizeable discrepancies in the values for 2B & 3B (I'm not so worried about SB/CS as I understand those are sometimes fudged for leverage reasons).

Does anyone know what else in done in training the Linear Weights model to obtain the known coefficients? For my software example, I think this is good enough, but now I'm curious.

Let me restate that in no way am I claiming the known values are not correct. I did almost no work in training the above model and I'm simply interested to know if there is a way I can come closer to the published coefficiencts.

Thanks.

I have a pedagogical question.

I understand that Linear Weights have been around for years and their values are pretty much agreed upon. I am writing an example for some Linear Regression software and thought it would be cool if I could reproduce the coefficients.

I plugged in team data from both leagues 1946-89 into a Least Squares Zero-Intercept Linear Regression model with R as the dependent variable and ABminusH,1B,2B,3B,HR,BB,SO,SB,CS as the independent variable and trained. I got the following coefficients:

0.51 : 1B

0.68 : 2B

1.21 : 3B

1.48 : HR

0.37 : BB

0.17 : SB

-0.22 : CS

0.0007 : SO

-0.10 : Outs

One one hand, I was pleased that this sort of looks like the right answer. I did no special massaging of the data, just using the software as a black box. The near-zero value of strikeout was fun to see. On the other hand, I notice some sizeable discrepancies in the values for 2B & 3B (I'm not so worried about SB/CS as I understand those are sometimes fudged for leverage reasons).

Does anyone know what else in done in training the Linear Weights model to obtain the known coefficients? For my software example, I think this is good enough, but now I'm curious.

Let me restate that in no way am I claiming the known values are not correct. I did almost no work in training the above model and I'm simply interested to know if there is a way I can come closer to the published coefficiencts.

Thanks.

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