I was curious about how well NBA draft combine metrics & measurements (i.e., vertical, lane agility, 3/4 court sprint, bench press, wingspan ratio, and weight ratio) actually predict success in the NBA (spoiler: not too well). To examine this, I scraped NBA combine data from 2000 to 2023 and ran regression analyses predicting LEBRON, a relatively new all-in-one advanced impact metric (LEBRON is further broken into O-LEBRON and D-LEBRON for offensive and defensive impact, respectively).
Across all positions, select combine metrics were only significantly associated with D-LEBRON. When broken down by position, the largest effect size was found for wingspan ratio and D-LEBRON in centers (b=0.14). This chart visualizes that association (with the manual addition of Wembanyama, Embiid, and Jokic, who weren’t in the original data due to missing combine stats).
The write up is interesting, and I see that you do adjust for multiple comparisons (which adjustment? Bonferroni?) One thing I think might be interesting is to include height in the model. The wingspan ratio accounts for the relationship with height, but raw height probably accounts for some of the defensive success, independent of wingspan (i.e. a tall person with a smaller wingspan ratio might be better off than a shorter person with a larger wingspan ration).
Also, I suspect that the negative relationship between wingspan and offensive metrics for guards might be due to selection bias: guards selected for their defensive ability probably had longer wingspans than the average. It might be interesting to stratify your data beyond position to account for this. I think if you compare similar draft positions you may see stronger/weaker relationships.
generally-mediocre on
who is the huge negative outlier? i cant recognize that face
4 Comments
**Data source:** NBA & Bball Index
**Tool:** R (ggplot2)
I was curious about how well NBA draft combine metrics & measurements (i.e., vertical, lane agility, 3/4 court sprint, bench press, wingspan ratio, and weight ratio) actually predict success in the NBA (spoiler: not too well). To examine this, I scraped NBA combine data from 2000 to 2023 and ran regression analyses predicting LEBRON, a relatively new all-in-one advanced impact metric (LEBRON is further broken into O-LEBRON and D-LEBRON for offensive and defensive impact, respectively).
Across all positions, select combine metrics were only significantly associated with D-LEBRON. When broken down by position, the largest effect size was found for wingspan ratio and D-LEBRON in centers (b=0.14). This chart visualizes that association (with the manual addition of Wembanyama, Embiid, and Jokic, who weren’t in the original data due to missing combine stats).
An in-depth write-up of my findings is available here: [https://www.formulabot.com/blog/do-nba-draft-combine-metrics-predict-nba-success](https://www.formulabot.com/blog/do-nba-draft-combine-metrics-predict-nba-success)
The write up is interesting, and I see that you do adjust for multiple comparisons (which adjustment? Bonferroni?) One thing I think might be interesting is to include height in the model. The wingspan ratio accounts for the relationship with height, but raw height probably accounts for some of the defensive success, independent of wingspan (i.e. a tall person with a smaller wingspan ratio might be better off than a shorter person with a larger wingspan ration).
Also, I suspect that the negative relationship between wingspan and offensive metrics for guards might be due to selection bias: guards selected for their defensive ability probably had longer wingspans than the average. It might be interesting to stratify your data beyond position to account for this. I think if you compare similar draft positions you may see stronger/weaker relationships.
who is the huge negative outlier? i cant recognize that face
Where’s Draymond on here?
Also, crazy to see Bogut so high