Ok, here is what I've been talking about in terms of binomial graphs.
I've only put in the data for every 5 swings instead of every 1 swing.
axe vs sword time to be killed.png
This tells you what % chance at any time death occurs.
The Sword will most likely kill axe at 10 swings. You can see what chance this has to occur at different times.
The Axe will most likely kill sword at 25 swings.
The use of this information - to see how long until a unit can kill his enemy, and/or how close the enemy is to death. And compare them to each other.
At the bottom of have shaded areas - are these or another selection of areas what will tell us their overall strength?
axe vs sword chance to be killed.png
This tells you what % chance a unit has to have killed his opponent at given time. Or have survived!
This charts chance of death vs survival at any point in time.
The use of this information - to see how long a unit can survive (by not being dead).
I have shaded it again - could the area of these shapes be compared - the bigger the area covered - the more powerful the unit is in comparison?
Another practical use - when we know how long a unit can last, we know how long it could hold out to be flanked and killed if its stronger.
or know how long it can hold out to have a friend flank his opponent!
So we can tell how useful it is, and whether it needs to be buffed etc, to suit this purpose.
Here's an example,
If a sword fighter is being attacked by 2 axe fighters, it takes about 24 swings, or 8 swings in this case for him to have 50% chance to be dead.
IF you can get someone behind those axe fighters to kill them within 8 swings - about 10-15 seconds, then you have a good chance of saving him and killing the enemy.
If you can't get help within that amount of time, do something else (or at least don't try this manouver).
So here is where I draw the heavy use of maths into being useful for game tactics and game design

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