MDS Model for the BIG3 Basketball League

I haven't done much with the MDS Model recently, so this summer's BIG3 basketball league seemed like a good test case to break it out again. I applied my standard methodology on the 8 teams in the league, and I'll be using the typical techniques to project win probabilities and margin of victories as well. The nature of scoring in BIG3 does necessitate a deviation on the normal distribution I use to project spreads for other leagues, since in BIG3 teams play to a set score (60, win by 2). Based on my observations with Ultimate Frisbee (which has a similar end of game structure), I tweaked the formula to the log-normal distribution, which gives more weight to the extremes.

With that in mind, here's how the standings currently look (only based on margin of victory right now, since the teams aren't "connected" yet in the graph network):

Rank	Teams	PF	PA	Pyth	Matrix	MDS
1	Trilogy	60	45	0.650	0.5	0.650
2	3s Company	61	51	0.595	0.5	0.595
3	Power	62	59	0.527	0.5	0.527
4	3-Headed Monsters	62	60	0.518	0.5	0.518
5	Ghost Ballers	60	62	0.482	0.5	0.482
6	Tri-State	59	62	0.473	0.5	0.473
7	Ball Hogs	51	61	0.405	0.5	0.405
8	Killer 3s	45	60	0.350	0.5	0.350

I then used this to project the next round of games in Charlotte, NC on July 2:

Team A	Team B	Pick	Win Prob	Pick By
Ball Hogs	Tri-State	Tri-State	56.91%	Tri-State by 2
Trilogy	3-Headed Monsters	Trilogy	63.37%	Trilogy by 4
Power	Killer 3s	Power	67.37%	Power by 5
3s Company	Ghost Ballers	3s Company	61.19%	3s Company by 3