First, look at this:
Monta is now 28 years old. He's achieving productivity/efficiency ratings similar to what he put out at age 22, if not better. Why? By all accounts, Ellis already declined as a player and was supposed to continue declining throughout his career. But it appears he's making a comeback.
One-time aberration? Or were we to quick to jump to conclusions?
Grantland can help. Read this:
Here are some salient quotes:
One of two things is happening: Either Ellis is the breakout star of small-sample-size theater this year and a regression is coming, or he is in the process of demonstrating something that seems so obvious I hesitate to even write it: Playing for a good team makes individual players appear better, while playing for a bad team makes them look worse. To this point, even our most advanced stats neglect that most basic notion of basketball ecology.
The main point, that individual stats are a reflection of team success, seems extremely obvious, right? Or is it the other way around? Hmm
There’s no way to accurately characterize an individual basketball player without considering his situational habitat. Yet this is what we all do on a daily basis. We constantly cite individual basketball stats like points, field goal percentage, and assists as if they were home runs. I am as guilty as anyone. Ellis’s shot chart from last season is horrible, there’s no doubt about that — but what does that actually tell us? It tells us he was very active and his shots from the field went in at below-average rates, which is true, but that’s not the whole truth. Part of the problem is that our spreadsheets can’t handle the truth.
I think this is what I hate most about advanced stats in basketball. Basketball is a team game. Baseball, at least on offense, is a 1v1 game. Logically, you shouldn't be able to apply a baseball-approach to statistics to basketball since they're inherently different. But I think that's what we do.
So how does this affect Monta?
Let's leave it as a 'hmm' for now. :)