DenButsu

04-12-2012, 11:28 AM

I found this pretty interesting. I'm only posting the beginning bit so you can get a sense of where he's going with it, but proceed to the original post here (http://thecity2.com/2012/04/08/using-the-usage-efficiency-distance-metric-to-create-aging-curves-for-the-nba/) to see his methodology and the charts.

Using The Usage-Efficiency Distance Metric to Create Aging Curves for the NBA

Posted on April 8, 2012 | Leave a comment

An age-old question — see what I did there? — among APBRmetricians is trying to understand how aging affects players. Consider this post my first contribution to the discussion.

I calculated the distance metric that I introduced in a recent post for the 10,000 or so player seasons since the 3-pt shot was instituted. I then divided these seasons into four groups by age, as follows:

“very young” (18-21)

“young” (22-25)

“prime” (26-29)

“old” (30+)

For each group, I used the lme4 package to create a mixed-effects model. Here is an example for the first group:

Using The Usage-Efficiency Distance Metric to Create Aging Curves for the NBA

Posted on April 8, 2012 | Leave a comment

An age-old question — see what I did there? — among APBRmetricians is trying to understand how aging affects players. Consider this post my first contribution to the discussion.

I calculated the distance metric that I introduced in a recent post for the 10,000 or so player seasons since the 3-pt shot was instituted. I then divided these seasons into four groups by age, as follows:

“very young” (18-21)

“young” (22-25)

“prime” (26-29)

“old” (30+)

For each group, I used the lme4 package to create a mixed-effects model. Here is an example for the first group: