Spread of MOV in MLB (Predicting Run Lines)

I undertook the same margin of victory (MOV) analysis I did with Ultimate Frisbee to determine the spread of MLB games, with the intention to then use this to predict run lines. As mentioned in the above post, to predict MOV (lines), I calculate the inverse of the normal distribution for each win percentage and then multiply this by a parameter for each league. I had not yet calculated this parameter for baseball/MLB.

I took all games played in the 2013 season (both regular and postseason) and found that the standard deviation in MOVs is 2.546. To be conservative (as I usually am when predicting lines), I bump this up to 3. Fittingly, 62.91% of games were within 3 runs or less (close to the 68% desired within one standard deviation of normally distributed data). However, as with Ultimate, more exists at the extremes than would be predicted by this normal distribution. However, run lines are always set at +/-1.5, which is where I'm most concerned (within 1 to 2 runs). So I'm sticking with a SD of 3.

SD for MOV:

NBA:      10.5

NCAAB:    10

NFL:      10.5

NCAAF:    13.5

NHL:      2

MLB:      3

Soccer:   1.5

Ultimate: 4

Below are the counts and cumulative percentages for MOV in the 2013 MLB season.

MOV	Count	%	Cumulative %
1	1586	30.85%
2	947	18.42%	Actual	Normal Dist
3	701	13.64%	62.91%	68%
4	583	11.34%
5	436	8.48%	Actual	Normal Dist
6	268	5.21%	87.94%	95%
7	206	4.01%
8	128	2.49%	Actual	Normal Dist
9	95	1.85%	96.28%	99.70%
10	76	1.48%
11	34	0.66%
12	16	0.31%
13	18	0.35%
14	3	0.06%
15	9	0.18%
16	5	0.10%
17	0	0.00%