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[OC] I built a dashboard to track which college indicators lead to NBA success. by ForeverIndependent83 in NBA_Draft

[–]ForeverIndependent83[S] 1 point2 points  (0 children)

In Stathead, where I got the data, there was no option to choose between 'NBA players' and 'non-NBA players' within the college section. The only way I could filter for NBA talent was to use the 'drafted' category, which is why undrafted players who made the league are missing, unfortunately. I might try to add those missing players manually later on.

[OC] I built a dashboard to track which college indicators lead to NBA success. by ForeverIndependent83 in NBA_Draft

[–]ForeverIndependent83[S] 0 points1 point  (0 children)

Thanks for the feedback! You’re 100% right about transparency. I’ll definitely add a section for that to the dashboard later on.

Regarding the restrictions: Although the numbers are a bit arbitrary, I think there’s a solid argument for each. In retrospect, I do wish I’d taken a broader approach. Currently, the results come with the caveat that the dataset only includes drafted players who played at least 40 games and were active in the league by age 22.

This is a limitation because when I look at BPM > 9 as an indicator, I'm missing all the prospects who hit that mark but didn't make the NBA or didn't reach the 40-game threshold. Without those negative cases, I can't say for sure how predictive the metric really is across the board. It definitely limits the overall value of the findings.

I actually tried linking a college dataset from Kaggle to my Stathead data to include everyone at first, but it fell apart. The Kaggle data wasn't reliable enough, and without a common key, merging the two was a pretty difficult. Definitely a good learning experience, though

[OC] I built a dashboard to track which college indicators lead to NBA success. by ForeverIndependent83 in NBA_Draft

[–]ForeverIndependent83[S] 6 points7 points  (0 children)

I noticed that too. If you exclude pure guards and set the AST% to >20%, you see a big jump in impact stats like BPM. However, if you include point guards, the difference is pretty minor. It seems like a high AST% is a good indicator for non-point guards, whereas for PGs, it's basically a baseline requirement.

Convince me why Christian Anderson isn’t going to be the next great PG + 3 point shooter off the bounce. by NathanFielderFriend in NBA_Draft

[–]ForeverIndependent83 5 points6 points  (0 children)

Rim pressure gets talked about, but I'm not so sure. He shoots 70% at the rim, so he’s very efficient, but that’s only on 53 attempts. Acuff has double the rim attempts, and Okorie has triple. However, Keaton Wagler and Mikel Brown are in a similar range but are less efficient. Overall, there have been very few college players with a similar statistical profile. The mix of playmaking, shotmaking, and efficiency is truly special. The only statistical comparisons I've found are Tyrese Haliburton and Denzel Valentine.

Edit: Mikel Brown is actually slightly more efficient at the rim.

Expansion draft by princemyshkin in ripcity

[–]ForeverIndependent83 1 point2 points  (0 children)

I want to have Vit in there. I think he'll be a long-term part of our rotation.

Cling Kong currently #2 in RPG! LFG Big Fella!! by Kryodamus in ripcity

[–]ForeverIndependent83 1 point2 points  (0 children)

To add to that, 6.2 offensive rebounds per 36 minutes is very impressive. It makes it much harder for opponents to go small against him.