Damage Formula Thread

[EasymodeX]

So, here's 100 hits of B3, copied from ACT, using the 69-471-295 setup, which had 2.50604 potency last time.

Min 520
Max 575
Value 547.5

also max/min = 1.10577... a bit less than your desired 1.1053

Np, with rounding / truncation, I expect that metric to always be a bit off, especially for smaller damage levels. 1.10577 is prettydamnclean.

I plugged in the stats into my formula and it predicts an average damage of 549.9*, with a range of 522.4-577.4.

* I used a BLM trait multiplier of 1.3, assuming the second trait replaces the first trait.

Not bad but slightly off. I'll plug your data point into my spreadsheet and re-run solver a few dozen times.

Edit: Seems like your data point helps stretch/scale the formula for high WD+DTR combinations.

With that method, you can have X hits that dont change or improve the accuracy of your test, then suddenly one magic hit outside the range will change things.
When using an average, EVERY new hit improves your test, rather than waiting out some magical hit that may come in 50 casts, 100 casts, or 1000 casts.

In terms of debating the method ...

I agree with you for an open-ended test where you're trying to measure something unknown or something with "real"/unknown variation. In this context, that is not the case. We know/assume that the expected results are 95%-105% of the average. Therefore we know what range we are looking for -- if the data set has a max/min of 1.100 or 0.987, we know to wait for the next magic hit (or two).

When using an average, every new hit can also reduce the accuracy of your test ... randomly.

When I was getting my 7th set from my impatient BLM buddy, I was actually watching the ACT parse as it happened and calculating the max/min until the ratio grew large enough to exceed 1.105. It was actually stuck on 1.100 or so for almost a whole minute until he got a new max damage 3 points higher so I could tell him to stop.


For the case of the data you posted, the result from the avg(min,max) method is 547.5 and the avg(population) is 549.97 -- I'd bet the former number is more accurate.

... and more importantly it only takes a few minutes to test per datapoint T.T