Averaging Ability Scores for Defenses

Sum of the mods has potential to work. The main problem I see is the weird situation stalker0 pointed out, where some statted characters will be completely immune against one particular attack type, and then incredibly weak versus the other two.

That could be a big hassle for classes/builds whose attacks primarily focus upon just one of the defenses. If their opponent is doubled up on that single defense then they are SOL. It also means that classes that have the option to attack all three defenses will be more powerful, because many opponents will have 2 weak defenses to strike at instead of just 1.

Another balancing issue would be for classes whose primary and secondary stat are shared under the same defense. With a point buy system, they are pretty much forced to be that "immune to one attack type, incredibly vulnerable to the two attack types" builds. This would be particularly crappy for CHA+WIS classes, as Will is clearly the least common attack type in 4E.

All that said, I really like the simplicity of the sum of mods as opposed to the average of 2 or just the best of 2. If you can think of some way to compensate for the aftereffects listed above, let us know...I know I'd certainly embrace it in a heartbeat =) I'm all for taming the minmax.
 
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After doing some really simple math (I'm not good at the more complex stuff), I figured out that before racial modifiers, using the standard array, summing together the modifiers, a PC gains 1 NAD 50% of the time, 2 NADs 33.33% of the time, and 3 NADs 16.67% of the time. The thing is, you always gain; there's no way to have it equal the normal system. Maybe an inherent NAD penalty would solve the problem, but if you go through that much bother it renders the house rule pointless.

I didn't figure anything out for averaging, but it seems to have the opposite problem. You alway lose points. And then you'll have to factor in AC, and heavy armor, and racial bonuses, and I lose all control. But I like the ideas being tossed around here, thanks for them.
 

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