APBRmetrics

[Albert Lyu]

Hey all, I've been a lurker in this forum for a few years now, but I'm glad to be posting for the first time here. Hopefully I can contribute to some basketball research.

I wanted to share some of the work I've done on the value of blocks, trying to emulate what John Huizinga and Sandy Weil had presented at last year's Sloan Sports Analytics Conference (bchaikin did revive an old thread in order to share the links). I did not get a chance to attend the conference or see Huizinga and Weil's paper, but I was intrigued about the idea of factoring the preblock situation and the type of shot in order to ascertain the value contributed by shot-blockers.

Using the PbP data provided by Ryan J. Parker, I took my own look at blocks between 2007-2010 from two perspectives: 1) Points saved per block based on shot location, and 2) Points saved per block based on shot type. The premise is the same as that of Huizinga's in that not all blocks are created equal. I attempt to calculate value of the block based on the value of the shot which was blocked.

If you would like to take a look at some of my findings, go ahead to the following links:

http://thinkbluecrew.blogspot.com/2010/08/anatomy-of-block-introduction-part-1.html
http://thinkbluecrew.blogspot.com/2010/08/anatomy-of-block-by-shot-location-part.html
http://thinkbluecrew.blogspot.com/2010/08/anatomy-of-block-by-shot-type-part-3.html

Just a sample of some of my findings, I found that the shots which Andris Biedrins and Brendan Haywood blocked were consistently of lower value based on both location of shot and type of shot, from season to season. I also found that Joel Przybilla, Chris Anderson, and Gerald Wallace were consistently among the leaders in high value blocks.

This is my first time doing a research study like this and presenting it to a high-caliber audience like that of this forum, and I wanted to address some concerns about my methodology and findings and see what you guys think (perhaps Sandy Weil could help me out, if you still hang out here). I am aware that the shot types recorded may include bias in the sense that layups that are made tend to include additional descriptions such as "driving layup" or "reverse layup." Concerning the generic shot types vs. the specific shot types, while it leads to interesting studies, it indicates a reason to be careful/skeptical about generalizing certain shot types, especially the generic shot types.

Secondly, I have tried to think of ways to consolidate points per shot based on shot location with points per shot based on shot type, but realize that it is more difficult than it seems. The sample size either becomes too small as we get more specific (say, a turnaround jump shot in a different X-Y coordinate) or there is a presence of multicollinearity since most shot types are defined precisely by where they are located on the court. I'm not sure if I am understanding this correctly from a statistical standpoint, and feel free to correct any of my statements.

Finally, I do understand there is more to the value of a block than just the average value of the shot that was blocked. I was wondering what other research has also been done out there on blocks concerning the trade-off with shooting fouls, goaltending, "Points Created" and transition baskets, etc.

Anyway, definitely let me know if you have any interesting or critical comments about all this.

Thanks all!
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I am the author of Think Blue Crew. Follow me on Twitter.

[Albert Lyu]

I concluded my series on blocked shots on my blog. Here in Part 5, I started looking at "Points Created" by first calculating "Possessions Gained Per Block" (similar if not the same as the way Sandy Weil did it), then added "Points Saved" with "Points Created" to figure out an overall block value per 36 minutes played. I'm a little bit concerned about the validity of using league PPP with possessions gained to calculate points created, as well as adding points saved with points created.

http://thinkbluecrew.blogspot.com/2010/08/anatomy-of-block-points-created-part-5.html
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I am the author of Think Blue Crew. Follow me on Twitter.

[Mike G]

Albert, have you looked at breaking your samples into home and away blocks? Some players (some years) have gotten twice as many blocks at home as on the road. If half of their home 'blocks' are just due to imaginative scorekeeping, might there be a lower correlation with points prevented?

Players mentioned in your articles have a broad range of home/away block rate differentials. Do Biedrins' blocks not translate to many prevented points? Or does he really not block so many as are reported?: