In lieu of BPM to give an idea of the competitive level of each series, I'm just taking the regular season SRS and the avg of the 2 teams.
I seem to recall that in most SPM, a team's SRS will be 4.2 times the avg player (or position) SPM; so an average Lynx player should be (8.72/4.2=) 2.08 BPM better than an avg WNBA player.
Just ranking the NBA players by PER, WS/48, and BPM, I get conversion rates. For each 1.0 of BPM , PER differs by 1.47, WS/40 by .020, e400 by .20:
Code: Select all
rd1 SRS SRS tm srsT /4.2 PER+ ws40+ e400+
Min 8.72 1.47 GSV 5.10 1.21 1.78 .024 .24
Atl 6.49 2.53 Ind 4.51 1.07 1.58 .021 .21
NYL 3.79 2.55 Phx 3.17 .75 1.11 .015 .15
LVA 2.59 2.02 Sea 2.31 .55 0.81 .011 .11
rd2 SRS SRS tm srsT /4.2 PER+ ws40+ e400+
Min 8.72 2.55 Phx 5.64 1.34 1.97 .027 .27
LVA 2.59 2.53 Ind 2.56 .61 0.90 .012 .12
The last 3 columns are the adjustments we can make to these 3 player stats, specific to these series.
After normalizing a series total PER to 15.0, and WS/40 to .100, then adding the
strength of series adjustment, the Min-Phx players look like this:
Code: Select all
. Phx min PER WS/40 e400 . Min min PER WS/40 e400
Thomas 80 25.1 .225 2.04 McBride 81 21.9 .227 1.43
Sabally 70 17.3 .129 1.36 Collier 72 23.8 .196 1.87
Copper 69 11.0 .024 .70 Carleton 71 6.6 .059 .36
Whitcomb 58 15.6 .076 1.13 Williams 69 29.2 .227 2.81
Bonner 51 -2.1 -.125 .14 Smith 56 17.6 .157 1.45
A. Makani 41 10.5 .026 .64 Hiedeman 33 - .3 -.142 -.17
Mack 31 25.9 .307 1.45 Shepard 27 11.9 .094 .71
Westbeld 25 29.7 .319 1.68 Kliundikova 15 28.1 .291 1.47
totals 425 15.9 .106 1.16 totals 425 18.1 .149 1.38
Player wins now sum to more than # of games, but the inferred point differentials should be unchanged.