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Surprisingly, nothing breaks when switching D&D to 2d10 instead of d20
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<blockquote data-quote="NotAYakk" data-source="post: 8146743" data-attributes="member: 72555"><p>You are playing roll-over, not roll exactly. The distribution of 1d8+1d12 (SD 4.1) and 2d10 (SD 4.06) and 1d15+3 (SD 4.3) and 5d6-7 (SD 3.8) are very hard to distinguish in actual play results of "how many times did someone miss or hit a given target number in a game", assuming you have some kind of ~5% auto-hit/auto-miss "crit" mechanics attached.</p><p></p><p>Like, 100s or 1000s of samples to have any decent chance to tell which is which.</p><p></p><p>You should roll multiple dice as your core roll-over DC resolution mechanic when</p><p>a) You have a mechanic that is more interesting than "add up the total".</p><p>b) You intend to do standard-deviation based scaling differently on two parts of the game differently, and this provides a quick shortcut.</p><p>c) You consider this a quicker shortcut than somehow boosting the size of modifiers and target numbers would be.</p><p>d) You consider rolling more than one die to be intrinsically better for no reason related to its distribution shape.</p><p></p><p>Take craps, for example: here you are trying to roll a number exactly. Now the shape of the distribution matters more than roll-over systems.</p><p></p><p>When you play "roll over", you care about the cumulative distribution function, and that is a kind of integration. Integration flattens (or averages, or smooths) the bell curve into a very slightly wavey line (again, outside of the tails, which compass the area of a "crit miss" or "crit hit" mechanic). If you are visual, don't look at the bell curve, compare the roll over/under possibility. And scale the two charts based on mean (average) and standard deviation (a scale on modifiers/target numbers) to isolate the effects of that from the effects of the curve. The two curves end up being ridiculously close to each other.</p><p></p><p>And often the reason is (d), people might have more fun rolling more dice, or they might have more fun believing a story about how the bell curve makes it a better game, or whatever. If those stories make you feel your game is better, and thus your game is better, yay!</p><p></p><p>I think, as someone doing (even amateur) game design, you should know the cause of the effects, and not just hand wave "it felt better". That lets you intentionally cause gameplay effects instead of accidentally getting lucky.</p></blockquote><p></p>
[QUOTE="NotAYakk, post: 8146743, member: 72555"] You are playing roll-over, not roll exactly. The distribution of 1d8+1d12 (SD 4.1) and 2d10 (SD 4.06) and 1d15+3 (SD 4.3) and 5d6-7 (SD 3.8) are very hard to distinguish in actual play results of "how many times did someone miss or hit a given target number in a game", assuming you have some kind of ~5% auto-hit/auto-miss "crit" mechanics attached. Like, 100s or 1000s of samples to have any decent chance to tell which is which. You should roll multiple dice as your core roll-over DC resolution mechanic when a) You have a mechanic that is more interesting than "add up the total". b) You intend to do standard-deviation based scaling differently on two parts of the game differently, and this provides a quick shortcut. c) You consider this a quicker shortcut than somehow boosting the size of modifiers and target numbers would be. d) You consider rolling more than one die to be intrinsically better for no reason related to its distribution shape. Take craps, for example: here you are trying to roll a number exactly. Now the shape of the distribution matters more than roll-over systems. When you play "roll over", you care about the cumulative distribution function, and that is a kind of integration. Integration flattens (or averages, or smooths) the bell curve into a very slightly wavey line (again, outside of the tails, which compass the area of a "crit miss" or "crit hit" mechanic). If you are visual, don't look at the bell curve, compare the roll over/under possibility. And scale the two charts based on mean (average) and standard deviation (a scale on modifiers/target numbers) to isolate the effects of that from the effects of the curve. The two curves end up being ridiculously close to each other. And often the reason is (d), people might have more fun rolling more dice, or they might have more fun believing a story about how the bell curve makes it a better game, or whatever. If those stories make you feel your game is better, and thus your game is better, yay! I think, as someone doing (even amateur) game design, you should know the cause of the effects, and not just hand wave "it felt better". That lets you intentionally cause gameplay effects instead of accidentally getting lucky. [/QUOTE]
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Surprisingly, nothing breaks when switching D&D to 2d10 instead of d20
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