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Alright, so here is where we are.
We started with a look at the most crazy direction for modeling an Ohtani-friendly 6-man rotation, using a flex plan. That was Part 1. Sure, there are doubters. Why shouldn’t there be? Forecasting a model is not the same as casting things in stone and it’s easy to lose the distinction. But I think that I demonstrated that using some form of a flex plan holds the greatest promise for our main objectives of allowing Ohtani to get as much MLB game time as possible while still protecting the pitching regimen with which he is most familiar. And the odds are that Ohtani will be a more valuable pitcher than batter, so protecting his strength is important.
Then we went and looked at a straight 6-man model. This is for the sake of comparison. We should learn two things: (1) whether a straight 6-man is seriously meaningful or not, and (2) whether it is close enough in value to a flex plan as to negate all the effort in figuring out a flex? I think we learned that those answers are definitely NO and NO. A straight 6-man is clearly inferior to maintaining some form of flex in your rotation, simply at the modeling level. But there are probably even more benefits of a flex plan in managing a pitching staff, because it does not lock you in to one specific guy as your 6th starter. You have options. You could leverage your AAA depth better, or you could work some guy who is good at starting but also handy in emergency long relief in those long stretches between starts. Flex plan beats a straight 6-man.
Today we use the same modeling perspective to put the usual and customary 5-man rotation into view. From this we can compare just how radical we are being, and in which direction.
Ok, so here we are. To review, this was what I believe to be the optimal model for a 6-man flex plan:
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And here is how the straight 6-man worked out:
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What we found was that the straight 6-man heavily favors the 6-day rest cycle which is well beyond the MLB norm and even beyond what Ohtani is used to, yet doesn’t grant a meaningful benefit in more DH opportunities for Ohtani.
Now that we are up to date, here is the straight 5-man:
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Just as with the straight 6-man, there is no need to present all 5 tables. They are all identical except for which slot Ohtani occupies and how many DH chances he gets. When working the #1 slot in the rotation, Ohtani gets 44 potential DH chances in the first half of the 2018 season. Those numbers for slots #2-#5 are 40, 43, 43 and 47. So Ohtani in the #5 slot in a straight 5-man would seem optimal.
I expected to see a table heavily weighted towards 4 days rest. So I find it surprising that although the 4-days rest value is high, the 5 days of rest still is dominant. 5 days of rest is the target for calendars days between starts for Ohtani. So, to me, this reinforces the notion that a straight 6-man is the worst idea. Using a traditional 5-man rotation as the base, and adding a flex plan to add a 6th starter as needed when off days in the calendar are of no help to extend Ohtani still seems the better direction to take. The flex plan gives the same number of starts with 5 days rest as a straight 5-man, with the difference being more 6 and +6 days (for that spot starter only) of rest rather than 4 days in a straight 5-man. We get about 28 starts with a flex plan where the staff has an extra 3 days rest. That is either a healthy benefit or a fatal flaw. I’ll let the LA Front Office and coaching staff own that one.
But what I still see is an advantage for some form of 6-man flex, working off the base 5-man model. What will be fun is to watch exactly how the Angels deploy their staff and compare that to the models we are creating here.
There will be one more article in this series. I find it important to now go back and look at a past season and track the actual starting rotation through at least the first half of a season (as these modeling exercises have been), and see just how much hash happens to a real schedule and how the Angels have moved their staff around injuries, off days and makeup doubleheaders and such. I have no prediction there, but I feel that there might be the potential for good information should I put a real life series of events into this modeling perspective. My hope is that I find the real world actions can then be overlayed into a flex model but I don’t know. And I need to know.
So the floor is open for comments again. And, as always, anybody who wants to have my source Excel workbooks need only DM me.