From the Desk of the Commish

I have often dreamt of the possibility that in some parallel universe, the Cowtippers are currently six-time BDBL champions, and the '08 'Tippers are locks to make it seven titles in ten seasons. Not only that, but I haven't traded John Danks and Jon Lester, Miguel Cabrera is enjoying an MVP season, Kenji Johjima is hitting his weight, Erik Bedard and Dustin McGowan aren't injured for the season, and the 2009 Cowtippers are looking like surefire locks to win it all again next year.

No doubt, in that alternate universe, I am the only human GM remaining in the league, as all of the other owners have grown so tired of seeing me win year after year, they've all departed, leaving me to manage every one of my games against the MP. But still, I am happy.

The beauty of Diamond Mind baseball is that you can simulate this dream scenario and play out the season several times in order to see what might have happened had a few random bounces gone differently. Since the inception of this league, it has been an unwritten rule that we should not simulate any full seasons using the league disk, as it would "ruin the surprise" of the coming season, and may prompt teams to make premature decisions based on a few random sims. However, I'm going to break that unwritten rule for the simple reason that I have nothing else to write about this month. Don't try this at home.

For the purpose of this exercise, I ran ten full simulated seasons using our current player disk. The downside to this method is that I'm using the rosters as they exist today -- after a ton of trades have been made. It would be more interesting to run these sims using our Opening Day rosters, but that would take too much work, and I'm very lazy. Another big difference is that not all MPs may be set to their optimum usage. And another difference is that the sims don't follow our usage rules, so some SUS's may get more playing time than they are allowed. And the sim seasons also include random injuries that last more than four games. But for the purpose of this exercise, this is all acceptable enough, I think.

One thing I have learned through this exercise is that the regular season is FAR more random than I had ever suspected. Below are the results of my ten sims, along with some projected numbers from our current season. I'll explain what all of this means after I show you the numbers:

Butler	W	L	Pct	Avg RF	Avg RA	pRF	Diff	pRA	Diff	Div	Hi W	Lo W	pW	Diff
Salem	96	65	.597	807	639	838	31	557	-82	8	103	82	105	+10
Corona	93	67	.580	862	743	825	-37	688	-55	2	102	84	97	+4
New Hope	78	82	.489	778	806	781	3	826	20	0	87	72	82	+4
New Milford	63	97	.393	706	884	779	73	784	-100	0	77	55	86	+23
Benes	W	L	Pct	Avg RF	Avg RA	pRF	Diff	pRA	Diff	Div	Hi W	Lo W	pW	Diff
Manchester	82	78	.514	760	762	701	-59	757	-5	4	87	71	75	-7
Ravenswood	82	78	.512	732	711	742	10	685	-26	4	94	73	94	+12
Marlboro	75	85	.470	694	724	683	-11	858	134	2	83	71	62	-13
Las Vegas	68	92	.424	705	790	662	-43	829	39	0	72	56	66	-2
Griffin	W	L	Pct	Avg RF	Avg RA	pRF	Diff	pRA	Diff	Div	Hi W	Lo W	pW	Diff
Los Altos	91	69	.566	758	682	700	-58	690	8	5	101	75	80	-11
Bear Country	90	70	.563	834	733	898	64	762	29	5	100	84	86	-4
San Antonio	83	77	.516	666	646	586	-80	677	31	0	96	76	67	-16
Sylmar	73	87	.458	662	733	674	12	745	12	0	84	62	69	-4
Higuera	W	L	Pct	Avg RF	Avg RA	pRF	Diff	pRA	Diff	Div	Hi W	Lo W	pW	Diff
Allentown	96	65	.597	857	711	915	58	714	3	8	102	90	90	-6
Kansas	88	72	.549	703	653	748	45	671	18	2	103	69	96	+8
Villanova	64	96	.401	685	801	673	-12	769	-32	0	72	58	75	+11
Great Lakes	63	98	.391	673	849	650	-23	846	-3	0	76	53	53	-10
Person	W	L	Pct	Avg RF	Avg RA	pRF	Diff	pRA	Diff	Div	Hi W	Lo W	pW	Diff
Southern Cal	102	58	.636	884	661	987	103	635	-26	10	115	95	114	+12
St. Louis	85	76	.528	724	686	763	39	678	-8	0	91	76	91	+7
Nashville	71	89	.444	762	835	723	-39	698	-137	0	81	61	82	+11
South Carolina	63

What Might Have Been