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41 sats \ 4 replies \ @Undisciplined OP 13 Oct \ parent \ on: A Model to Find the Most Average NBA Player math Stacker_Sports

Earlier iterations attempted to use the share of time spent at each position. This is probably highly correlated with the physique metrics, which wasn't addressed in the video.

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67 sats \ 3 replies \ @SimpleStacker 13 Oct

I like the idea of share of time spent at each position. Why did he give up on that approach?

Sure, it might be correlated with physique, but from my skimming of the video he had some techniques to deal with heavily correlated variables.

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46 sats \ 2 replies \ @Undisciplined OP 13 Oct

I didn't catch his reason for switching. Maybe it was too noisy.

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67 sats \ 1 reply \ @SimpleStacker 13 Oct

400 data points is a pretty small sample size for this kind of high dimensional analysis

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5 sats \ 0 replies \ @Undisciplined OP 13 Oct

I didn't catch the sample size. Power was my other thought. If those five categorical variables can be closely approximated by one, then collapsing them is pretty valuable.

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