Right, I know it's a multi-year sample. But, from my understanding, it's a multi-year sample because that's the level of data you need for something close to "real information" (as opposed to sample size artifacts). So, even though the data is not just from this year, it should be your system's best guess as to the players' current "true talent level," right? That's why I recommended checking it against this year's team point differential.
No... it is purely due to sample size. If you look at my first table, the standard errors are still kind of high even using four years of data. If I used one year of data they would be too high. Even as it is, every 10th player rating is expected to be off by 3 or more.
So I have to use 4 years of data and I weight those years equally so it is
not a current year rating. EDIT: In the sense that a vastly improved player will be rated the same as a vastly declined player if the overall performace during those four years were equal.
82games claims you can weight current year very heavily against prior years in order to get a current year rating while at the same time obtaining low standard errors . I don't believe them. It's like polling 10,000 people but weighting that last 1000 people much more than the other 9,000 people combined and thinking you're going to get a MOE similar to polling 10,000 people. Then they wonder why Chris Paul's defensive rating improves by something like 6 points from last year to this year.
So unfortunately I think that is a limitation of +/-. It takes years of data to reduce noise to reasonable levels, but then you are going to miss player improvement because you can't separate one year from the other. And one player's improvement missed is going to skew other player ratings somewhat. For example, Brandon Roy's improvement this year will tend to show up partly in Rudy's rating.
What I do like about this system though, is that it is the one rating system that can sense just about all of the intangibles except for interdependancies - stuff where the whole is greater than the sum of the parts.
Anyhoo... here is what I get for team +/- weighted average ratings. It's really not a predictor though since it cheats by using this year's data.
Code:
Team Rating Actual
BOS 9.3 8.1
CLE 8.0 8.9
LAL 6.8 8.0
SAS 5.9 3.8
HOU 5.6 3.8
ORL 4.6 7.3
POR 3.4 3.9
DAL 3.3 1.6
PHX 2.9 2.1
UTA 2.8 3.6
PHI 2.2 0.7
DEN 2.1 3.1
NOH 2.0 2.5
DET 1.6 -0.7
TOR -0.3 -3.3
MIA -0.4 -0.2
ATL -0.6 2.0
CHA -0.9 -1.1
MIL -1.1 -1.2
NYK -1.3 -2.6
CHI -1.7 -0.7
NJN -2.1 -2.3
GSW -3.3 -3.7
IND -3.5 -1.9
OKC -6.0 -5.5
MIN -7.0 -4.8
LAC -7.7 -8.4
SAC -7.9 -8.4
MEM -8.1 -6.6
WAS -8.5 -7.8