APBRmetrics

DSMok1 wrote: ↑Thu Oct 03, 2019 3:16 pm

DSMok1 wrote: ↑Tue Oct 01, 2019 11:54 am Coefficients of GmBPM:
https://docs.google.com/spreadsheets/d/ ... d=77600438

I'm interested in input: should any of these stats be in any way context dependent? I.E. relative to league or team averages?

Thanks!

RyanRiot wrote: ↑Thu Oct 03, 2019 4:47 pm I generally like to index everything to the league average, which certainly makes things a little more complicated and ugly, but I generally find it brings some slight improvements to my models.

DSMok1 wrote: ↑Thu Oct 03, 2019 5:20 pm

RyanRiot wrote: ↑Thu Oct 03, 2019 4:47 pm I generally like to index everything to the league average, which certainly makes things a little more complicated and ugly, but I generally find it brings some slight improvements to my models.

I am working with Per-100-Possession data in all cases which is a good start.

Logically, which statistics SHOULD depend on league context? I.E. if context changes (average points/possession, for instance) which of these statistics should, by deduction, have different value? Remember, I'm not working with FG% as an input but rather treating each event in a possession as a variable.

FGA
FTA
3 Pt FG
2 Pt FG
FT
AST
TO
RB
STL
BLK
PF

If league-wide FG% is low, it seems like the value of FG's and FGA's should reflect that somehow, but I'm not sure how at the moment.

DSMok1 wrote: ↑Wed Oct 09, 2019 6:20 pm Thanks, Kevin!

As I have dug into this subject, I realized something: One thing to remember that makes BPM as little different is the team adjustment. Basically, the statistics are only used insofar as they improve the division of credit among the players on the team.

In other words... in effect, all of the linear statistics (this doesn't apply the same for shooting) will be calculated vs. the team average regardless of any pre-processing. If my coefficient is 0.5 on rebounds/100, and the average player on the team has 10 rebounds/100 poss, the team adjustment will in effect add in a -5 to all of the players.

Does that make sense?

So, the only thing that is changed for these linear statistics with an adjustment is the scale of the delta between players. If we apply a linear multiplication to adjust for league context, it will change things somewhat. If we apply a simple constant addition or subtraction, it will not change the end result at all.

DSMok1 wrote: ↑Wed Oct 02, 2019 1:48 pm Position adjustment is mostly just a penalty on PGs. Each player is assigned a position from 1 to 5 (on a continuous scale) and then the position adjustment is calculated. Above the "breakpoint" there is no adjustment. The slope runs down from that break point back towards 1. So a PG gets a penalty of over 2 points. SG a small penalty. Everyone else no penalty.

Basically, it's saying--if you're a small player, you better show impact in the stats, because your non-stat impact (i.e. defense, picks, etc) is not as good.

nbacouchside wrote: ↑Tue Oct 15, 2019 2:54 pm Daniel, where are you getting the continuous player position assignments? Also, can you explain the mechanics of the player position adjustment with a couple of actual player examples? I'm having trouble understanding how it works exactly, based on the above description.

Intercept	0.970
 trb		0.398
 stl		-0.274
 pf		0.054
 ast		-0.153
 blk		0.275
 trb^2		-0.011

DSMok1 wrote: ↑Tue Oct 15, 2019 5:24 pm I did a regression to predict a player's listed position:

Code: Select all

Intercept	0.970
 trb		0.398
 stl		-0.274
 pf		0.054
 ast		-0.153
 blk		0.275
 trb^2		-0.011

That is then capped at 1 and 5.

The biggest discrepancies are 38-year-old Clifford Robinson (listed as a C for the GSW in 2005) and 21-year-old Giannis (listed as a PG by MIL in 2016). The regression puts Robinson as a 2.5 position and Giannis at a 3.5 position.

The position adjustment is a linear adjustment if less than the breakpoint, which is a round position 2.5. Above 2.5, there is no adjustment. Below 2.5, it's linear. So it would be mathematically:
Adjustment = (Slope*min((Position-2.5),0))

Does that clarify? The slope as it currently stands has now been revised down to around 1.0. So a PG gets a -1.5 point/100 penalty.

tarrazu wrote: ↑Tue Nov 12, 2019 4:53 pm Are there new coefficients for BPM 2.0 when splitting in into its offense and defense components? I went through this thread quickly, but didn't see anything?