PaKii94 wrote:madvillian wrote:ZOMG wrote:
That's a super weird take. You can bet none of the people making personnel decisions in the NBA think like that. If they do, they deserve to get fired. Hell, there’s a whole number crunching industry of advanced analytics that leans on the fact that basketball isn’t played in a vacuum. Everything affects everything.
What would be the point of pretending that streaks, injuries, coaching or intra-team dynamics don’t mean anything when looking at the performance of an individual player? How could that ever be true?
It’s easy to say that a player should "handle the adversity”, but if your boss tells you that your new job is to blitz the ballhandler on defense and space the floor on offense, and your rebounding numbers drop as a consequence, what do you do? How to handle the ”adversity”? After all, according to you this player has now regressed as a rebounder.
Yea I'm done. Nobody in analytics uses smaller samples when they have bigger ones available. He's played to a 14.4 PER this year. You are what the back of your baseball card says you are. Players get hot and cold. Players play in bad schemes with **** coaches and poor team mates. Somehow the stars manage to elevate themselves above all that -- like Lavine and countless other players stuck on **** teams.
Sorry friend but that's not how analytics work. Obviously a bigger sample set is preferable but that's so you can dissect it more. A simple example:
Sample set #1 of 1,3,2
Sample set #2 of 1,2,3,1,2,3,1,2,3
Sample set #3 of 1,1,1,2,2,2,3,3,3
Sample set #4 of 1,1,1,1,1,3,3,3,3,3
Sample set #5 of 1,3,2,2,3,1,3,2,1
These all have an overall average of "2" but they all tell a vastly different picture:
#1 - a too small sample set, you really can't tell anything
#2 - a cyclic/seasonal trend
#3 - a gradual improvement as time passes
#4 - a sharp change from 1 to 3.
#5 - random order, probably normal variance
The distinction you are making of the normal ups and downs of a season is usually a mix of #2 & #5.
#3 is how we would expect/want young players to gradually improve in performance and you can see numbers slowly improving
#4 is what Lauri experiences when hit with injury. It's damning that any injury and Lauri becomes a limp noodle but there is a distinction in how he plays.
as far as what analytic departments do - They for sure do a much deeper dive compared to "what the back of your baseball card says you are". The overall season numbers are a good starting point but the next step is "How were these numbers achieved?" and you break it down piece by piece.
I can understand the frustration though.