Marcus, thanks for your thoughtful response. I disagree with you on most points, but I don't mean any disrespect ... and for all I know, I'm wrong. Below, I've quoted your points only enough so that someone can refer to your full statements in the above post; I don't mean to misrepresent them.
1- 700 PA seems a bit high ...
RESPONSE: A previous poster on this board gave the following data for each position in the batting order:
1 775 full-season PAs
2 756
3 737
4 725
5 706
6 687
7 668
8 649
9 599
I don't know the source of this info, but if it's accurate it gives an average of 700 PAs for a DH league (1-9) and 712 PAs for a non-DH league (1-8).
However, as mentioned, with a slight margin of error (bigger for high injury ratings), my figures can be pro-rated to 700. For example, an injury-1 player when the number "775 PAs" is used in the formula (full-season uninjured lead-off hitter) would be just 0.1 "games missed" different by pro-rating than by the exact formula. (An injury-6 would be off by about 2 games missed if pro-rated rather than plugging in 775 for 700 in the formula.) So my figures can be reduced by 5%, say, if someone thinks 665 full-season uninjured PAs is more accurate than 700 PAs, and the results will be close to what the full formula would produce.
2- ... players start the season all healthy. So injury-risk is truncated ....
RESPONSE: I don't understand this point. All it means is that everybody gets "one free PA." That's negligible.
3- ... At one extreme, a player may be injured right off the first at-bat. And at the other extreme, a player may never be injured at all ...... The risk of NOT being injured after 432 PAs is: (215/216)^432, or 13.47%.
RESPONSE: This is mathematically irrelevant over a large sample. For example, a coin flipped four times has a 6.25% chance of never coming up tails. However, that fact does not alter the 50/50 distribution that would be found in a large sample of four flips. For an SOM injury-1 player, there's a 91% chance of not getting injured in 20 PAs, a 63% chance in 100 PAs, and a 1% chance in 1000 PAs. How does this possibly affect the average number of injuries (1 in 216) in a very large sample? Meanwhile, at the other end of the bell curve, a player could get injured two times as often as chance, or five times as often as chance, in 432 PAs; in both cases (or all other rare cases, including no injury), the odds are very low. However, both sides of the bell curve cancel each other out. Yes, in 432 PAs, there's a 13% chance of no injury; but there's also a chance of 1, 2, 3, 4, 5 or 432 injuries, and the aggregate of all these (and all others) will inevitably equal 1/216 in the long run.
4- On average, players have more impact than half-a-game before they get injured, because they complete the at-bat during which they get injured ...
RESPONSE: I don't understand this. For an unsubstituted starter, distributed over the batting order and over home/away games in a big sample, half of all injuries will occur in the first half of a game, and half will occur in the second half of a game (meaning the average is "one-half game per injury"); a tenth will occur in the first tenth, and a tenth will occur in the last tenth. If this were not true, it would mean that "more" (unsubstituted) starters play in the second half of games (or last tenth) than in the first half (or first tenth).
In any case, this affects only "games missed" but does not affect "starts missed." The difference between those two is small, and only that difference would be affected (specifically, reduced by about one-fourth, or e.g. 0.3 games for an injury-1 599 PA player) if you're right.
5- In Strat, injuries don't happen during bunts, squeeze, and hit-and-runs.
RESPONSE: This is mentioned in my post above ("bunts, H&Rs, etc."). By "PA," I mean an SOM injury-possible PA. So the 700 figure would reflect that, and, if wrong, could be pro-rated with a slight error.