Simulation 2016 … try, try again :-þ

Simulation 2016
First crack at simulating the 2016 MLB season.  Last year’s results weren’t very good.   Actually, they were bad …. since the RMSE was greater than that from guessing that every team would go 81-81. So, there’s room for improvement :-þ

For 2016, I’ve changed how the transition state probabilities are calculated by tweaking the pseudocounts, and added in consideration of how each team plays at home versus on the road.  Right now, that means how they performed in 2015 at home and on the road … which of course doesn’t mean they’ll do the same this season.  I’m working on how to add regression into the equation to make a better estimate of how each team might perform at home and on the road _this_ season.

Lineups and pitching rotations used for the simulation are those posted at rotochamp.

wins rf ra xWins wins rf ra xWins
tor 93 811 686 93 nyn 88 665 596 89
nya 84 701 688 82 was 88 670 608 88
bos 79 679 689 80 mia 80 599 623 78
bal 79 676 699 79 phi 69 560 657 69
tba 79 646 665 79 atl 69 541 640 69
wins rf ra xWins wins rf ra xWins
kca 85 682 661 83 sln 92 714 624 91
cle 85 679 658 83 chn 87 685 634 87
min 80 667 677 80 pit 87 691 635 87
cha 75 624 660 77 mil 75 617 671 75
det 74 622 673 75 cin 72 586 664 72
wins rf ra xWins wins rf ra xWins
hou 89 727 664 88 lan 89 687 626 88
tex 83 679 680 81 sfn 87 679 628 87
oak 80 635 659 78 ari 81 669 670 81
ana 79 638 658 79 sdn 76 597 646 75
sea 75 618 641 78 col 73 665 730 74