A fun little summer project to predict how good NBA players can become based on their rookie stats. 🏀
NBAPredict.io is now longer operational. Feel free to peruse through the code and check out some of my more recent NBA related work.
Player Name | Prediction |
---|---|
Ben Simmons |
5.00 |
Lauri Markkanen |
3.75 |
Donovan Mitchell |
5.0 |
Jayson Tatum |
3.75 |
De'Aaron Fox |
2.5 |
Malik Monk |
1.25 |
Metric | Purpose |
---|---|
per |
overall efficiency |
bpm |
box plus/minus |
vorp |
value over replacement |
usage |
usage %! |
tov% |
mistake rate |
ts% |
scoring skill |
war |
record orientation |
WS |
win shares (!) |
We look at a broad sample set of (current and former) NBA players and their rookie statlines. Once we've done that we begin to track certain "between-the-lines" metrics that can give the best insight as to what rookie tendencies and on-court habits resulted in the development of stars. We then apply that model on n number of players' rookie statlines and then can see whether or not they may become stars. A good example of this would be Jimmy Butler. As a rookie, Jimmy Butler averaged 2.6 points and other absymal on-the-surface numbers, but our model was able to indicate that he had a solid chance at stardom.