[This article was first published on More or Less Numbers, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
The draft for the NBA is quickly approaching. Much effort on the part of teams goes into selecting the correct assets in a player to complement what a team needs. Drafts also come in on much cheaper contracts than their more veteran counterparts and are therefore desirable from a value standpoint. It becomes increasingly important then what pick a team gets and even more so how well they select their draft pick (No. 1 or No. 2 picks not always dictating a high level of performance). In a recent interview with Bleacher Report, the head of analytics for the Denver Nuggets spoke a little about how they evaluate draft picks. He made some interesting comments about numbers his franchise evaluates as they consider their draft picks. Specifically, rebounds were an important metric that was actually translated as a “hustle stat”. I looked at the numbers to see if what he was saying was actually true over the last few years. Turns out total rebounds per game is an important metric for increasing a draft’s chance of being chosen as a top five pick.
I pulled draft year stats for the past 4 years for the top 30 picks from the good people at Basketball-Reference to see if their were any metrics that increased a players chances of being a top five pick each year. Only drafts who had college stats were used for this analysis. I wanted to see which per game metrics changed the likelihood of a top 5 selection in the draft class. What I found is in the decision tree below. I divided points per game, field goal attempts per game, minutes per game, and total rebounds per game into quartiles. I lumped the bottom two quartiles together as the “Lower Quartile” and then the “Middle Quartile” and “Upper Quartile”.
As you can see from the tree above rebounds per game not in the “Upper Quartile” have a top five selection probability of .13. The probability of being a top five pick is .33 if the draft’s points per game are in the “Lower Quartile” or in the lower 50% (average or lower) of their draft class and their rebounds per game are in the “Upper Quartile”. Alternatively, if the draft has rebounds per game in the “Lower Quartile, or less than the 50th percentile, and their points per game is in the top 50th or 75th percentile their probability of being a top five pick is only .19. Rebounds it seems are even more important than having someone who can score in the “Upper Quartile” of a draft class on a per game basis.
Alternatively, if a draft pick gets playing time per game in the “Upper Quartile” and has “Middle Quartile” or “Lower Quartile” points per game, this also yields a probability of .33 of a top five pick. I interpret this as, if you don’t have hustle but have had a lot of playing time in college, this increases the top five pick probability. I don’t interpret minutes per game in a college season to be as meaningful as rebounds simply because minutes per game is more of a college coaching decision that may or may not be relative to player performance. Minutes are primarily a function of performance and not a stand alone performance metric.
Rebounds matter for draft picks. Players not showing a strong “hustle stat” have a lower probability of being a top five pick within the respective draft class, unless they have happen to have played a lot of minutes, then this also had a higher top five pick probability. The competition, shooting distances, and rules are obviously different in the NBA from college and some of the college stats may not translate into professional performance. That being said this analysis does indicate that the “hustle stat” or rebounds are meaningful for teams other than just the Nuggets. High performance specifically in this metric increases the probability of being selected as a top five pick in the NBA draft.
Those interested in the R code can find most of it here.
I pulled draft year stats for the past 4 years for the top 30 picks from the good people at Basketball-Reference to see if their were any metrics that increased a players chances of being a top five pick each year. Only drafts who had college stats were used for this analysis. I wanted to see which per game metrics changed the likelihood of a top 5 selection in the draft class. What I found is in the decision tree below. I divided points per game, field goal attempts per game, minutes per game, and total rebounds per game into quartiles. I lumped the bottom two quartiles together as the “Lower Quartile” and then the “Middle Quartile” and “Upper Quartile”.
 |
| Decision Tree for Top Five Draft Pick for 2009-2013 |
As you can see from the tree above rebounds per game not in the “Upper Quartile” have a top five selection probability of .13. The probability of being a top five pick is .33 if the draft’s points per game are in the “Lower Quartile” or in the lower 50% (average or lower) of their draft class and their rebounds per game are in the “Upper Quartile”. Alternatively, if the draft has rebounds per game in the “Lower Quartile, or less than the 50th percentile, and their points per game is in the top 50th or 75th percentile their probability of being a top five pick is only .19. Rebounds it seems are even more important than having someone who can score in the “Upper Quartile” of a draft class on a per game basis.
Alternatively, if a draft pick gets playing time per game in the “Upper Quartile” and has “Middle Quartile” or “Lower Quartile” points per game, this also yields a probability of .33 of a top five pick. I interpret this as, if you don’t have hustle but have had a lot of playing time in college, this increases the top five pick probability. I don’t interpret minutes per game in a college season to be as meaningful as rebounds simply because minutes per game is more of a college coaching decision that may or may not be relative to player performance. Minutes are primarily a function of performance and not a stand alone performance metric.
Rebounds matter for draft picks. Players not showing a strong “hustle stat” have a lower probability of being a top five pick within the respective draft class, unless they have happen to have played a lot of minutes, then this also had a higher top five pick probability. The competition, shooting distances, and rules are obviously different in the NBA from college and some of the college stats may not translate into professional performance. That being said this analysis does indicate that the “hustle stat” or rebounds are meaningful for teams other than just the Nuggets. High performance specifically in this metric increases the probability of being selected as a top five pick in the NBA draft.
Those interested in the R code can find most of it here.
To leave a comment for the author, please follow the link and comment on their blog: More or Less Numbers.
R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.