Author Topic: Introducing the J Rating (or J Points)  (Read 2775 times)

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Re: Introducing the J Rating (or J Points)
« Reply #15 on: April 15, 2019, 01:08:16 PM »

Offline gift

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Interested to see Baynes ranked so low. He's clearly critical to the team's success.

I think a knock on Baynes in terms of his rating here is his only 16.1 minutes per game average. Limits his impact somewhat.

So everything being equal, the more minutes you play per game the higher your J Rating?  What is the correlation?

Well, somewhat. Minutes per game will obviously limit the number of opportunities you have to contribute to positive outcomes. But it's not as simple as MPG=J Rating Number. For instance, look at how high (relatively) Robert Williams is considering his 8.8 minutes per game.

Re: Introducing the J Rating (or J Points)
« Reply #16 on: April 15, 2019, 01:45:54 PM »

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  • Paul Silas
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Sounds interesting, but I need a hint on how these numbers are formulated.

I won't give away the exact formula because my methodology is somewhat outdated (I devised drafts of it maybe 15 years ago, but took me years to get to a point where I could access the data I needed in an efficient way). Also, part of my interest in actually playing this out is judging my ratings vs. general perceptions of nba players' performances.

However, I'm getting everything from traditional box scores and weighing TS% and +/-. I know how flawed this can be, but that's why I say this rating does not tell you how good a player is, but how good their performance was.

I'm working on a new rating system, but I think I'm going to compile seasons 2001-present first to help me see particular areas for improvement.

Sounds like defense is also not going to be captured, which is of course a problem with most stats-based measurements, arguably all of them.

Re: Introducing the J Rating (or J Points)
« Reply #17 on: April 15, 2019, 01:48:45 PM »

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Sounds interesting, but I need a hint on how these numbers are formulated.

I won't give away the exact formula because my methodology is somewhat outdated (I devised drafts of it maybe 15 years ago, but took me years to get to a point where I could access the data I needed in an efficient way). Also, part of my interest in actually playing this out is judging my ratings vs. general perceptions of nba players' performances.

However, I'm getting everything from traditional box scores and weighing TS% and +/-. I know how flawed this can be, but that's why I say this rating does not tell you how good a player is, but how good their performance was.

I'm working on a new rating system, but I think I'm going to compile seasons 2001-present first to help me see particular areas for improvement.

Sounds like defense is also not going to be captured, which is of course a problem with most stats-based measurements, arguably all of them.

Yeah, defense is not explicitly captured. I just tried to account for it where I could.