Pitching on an Imbalanced Schedule

By John Coleman

2002

One of the by-products of repeated expansion, uneven league sizes and random inter-league play is the Imbalanced Schedule. The schedule-maker now allots 76 intra-division contests for most teams in baseball.

An NL Central team will face its NL Central foes 84 times, and the smaller AL West will spend 58 contests facing its three divisional rivals.

Since we are all here to play a game of stats, (or in fact, live a life of stats) the question is not whether this imbalanced approach skews our stats, but by how much? And more importantly, can we somehow take a strategic advantage?

Do Yankee pitchers benefit from facing weak Baltimore and Tampa Bay offenses twice as often as Oakland pitchers? Obviously they do, but to what degree, and what measurable effect does it have on their value?

I’ve assembled a chart of Opposing pitcher ERA’s for each ML team, listed for the last 4 years.

Then, by grouping them according to division, we can see what kind of trouble each division has been cooking up for its opponent pitchers. The ERA figure is a measure of that team’s offense when facing other teams from its own league.

Then I averaged each division and subtracted the overall league figure from each total, which yields a positive or negative Divisional ERA Factor.

This factor behaves much as a Park Effect does. You only notice it when someone moves in or out of the context.

Here’s the AL Central:

AL	1998	1999	2000	2001
vs.Chi	4.82	4.41	5.57	4.59
vs.Cle	4.95	5.85	5.57	5.23
vs.Det	4.10	4.27	4.78	3.95
vs.KC	4.09	4.82	4.87	4.18
vs.Min	4.19	3.55	4.32	4.22
AL Central	4.43	4.57	5.02	4.44
	-0.23	-0.24	0.08	-0.04

Remember, these ERA’s belong to each team’s Offense, not pitching staff. Each figure is an aggregate of all AL pitchers facing that offense. The bottom line is the Divisional ERA Factor.

AL totals

4.66

4.82

4.93

4.48

The league totals are subtracted from the divisional totals to come up with the Divisional ERA Factor. This figure means, essentially, that a pitcher facing the AL Central in 2001 would expect to lower his ERA by .04.

Here are Divisional ERA factors for all 6 divisions:

	1998	1999	2000	2001	3 year avg.	adjusted
AL Central	-0.23	-0.24	0.08	-0.04	-0.07	-0.03	76/162	47%
AL East	0.03	0.09	-0.32	-0.25	-0.16	-0.08	76/162	47%
AL West	0.25	0.19	0.30	0.38	0.29	0.10	58/162	36%
NL Central	0.19	-0.06	0.15	-0.02	0.02	0.01	84/162	52%
NL East	-0.23	-0.17	-0.40	-0.41	-0.33	-0.15	76/162	47%
NL West	-0.00	0.24	0.22	0.42	0.29	0.14	76/162	47%

For the sake of simplicity, I’ve taken a 3-year average and applied a factor of the percent of divisional contests. The “adjusted” column suggests a recent historical norm for ERA effects between the divisions.

What is the meaning of all this?

I’m saying that a pitcher changing divisions from NL East to NL West can expect to have his ERA jump by an average of 29 points (before park effects) simply based on the increased level of offense he’ll be facing.

For example, Rick Reed left Shea Stadium for the Metrodome last year. His new stats were projected by removing Shea’s park effects, adding the NL to AL run increase, then accounting for The Metrodome’s park effects.

By using divisional effects, you’ll see that he also left the weakest offensive division for a nearly neutral context, which helped further ruin his numbers for the Twins.

SO ANYWAY…

The big question is this: What does this have to do with fantasy baseball?

1) When a pitcher moves to a new division, expect him to feel the effects of the offensive context. If El Duque moves to Texas, the new division alone will pop his ERA by a likely 18 points. The change in parks won’t help him at all either!

2) Overall rotisserie value is unlikely to change by more than $3 in even the most extreme cases, based on divisional factors. Park and team factors can be far more influential.

3) The “Draft starting pitchers in the weak divisions” strategy will not gain you any advantage, unless the starting pitcher is recently acquired. This is because a pitcher’s record and projections will always be based on his performance within that weak division.

I’ll finish up by presenting my complete charts. In order to use this information effectively for projection, I advise modifying the Adjusted Divisional Effect from a 3-year average to a projected figure. I’ll leave that job up to you! I’ll look forward to answering any of your questions or abuse, presuming you’ve gotten this far!

AL	1998	1999	2000	2001
vs.Chi	4.82	4.41	5.57	4.59
vs.Cle	4.95	5.85	5.57	5.23
vs.Det	4.10	4.27	4.78	3.95
vs.KC	4.09	4.82	4.87	4.18
vs.Min	4.19	3.55	4.32	4.22
AL Central	4.43	4.57	5.02	4.44
	-0.23	-0.24	0.08	-0.04
Adjusted Divisional Effect Factor:					-0.03
AL	1998	1999	2000	2001
vs.Bal	4.82	4.68	4.50	3.91
vs.Bos	5.05	5.01	4.64	4.50
vs.NYA	5.51	5.29	5.01	4.73
vs.TB	3.42	4.41	4.04	3.67
vs.Tor	4.68	5.14	4.87	4.32
AL East	4.69	4.91	4.61	4.23
	0.03	0.09	-0.32	-0.25
Adjusted Divisional Effect Factor:					-0.08
AL	1998	1999	2000	2001
vs.Ana	4.45	4.13	4.96	3.95
vs.Oak	4.55	5.29	5.66	5.23
vs.Sea	5.14	4.96	5.38	5.20
vs.Tex	5.51	5.66	4.96	5.05
AL West	4.91	5.01	5.24	4.86
	0.25	0.19	0.30	0.38
Adjusted Divisional Effect Factor:					0.10
AL totals	4.66	4.82	4.93	4.48
NL	1998	1999	2000	2001
vs.Chi	4.75	4.24	4.19	4.40
vs.Cin	4.50	4.86	4.86	4.09
vs.Hou	4.70	4.55	5.59	4.76
vs.Mil	3.89	4.66	4.15	4.24
vs.Pit	3.64	4.08	4.50	3.62
vs.StL	4.80	4.45	5.13	4.76
NL Central	4.38	4.47	4.73	4.31
	0.19	-0.06	0.15	-0.02
Adjusted Divisional Effect Factor:					0.01
NL	1998	1999	2000	2001
vs.Atl	4.82	4.76	4.39	4.13
vs.Fla	3.78	3.56	3.92	4.02
vs.Mon	3.56	3.87	4.24	3.60
vs.NYN	3.93	4.98	4.45	3.60
vs.Phi	3.78	4.66	3.92	4.29