D&D 5E (2024) How useful/interesting is something like this?

[TigerDude]

yo need to explain what you're doing to make something interesting

 

[Deset Gled]

Personally, I would prefer to have access to the data/tables/formulas more than the graph. I like to see the actual numbers. Part of this is just the way I think/learn. Part of this is that I've become too used to seeing bad charts and infographics being used for bad arguments.

That being said, I also understand that the visual matters, and the chart can be a good summary. I still prefer it at the end rather than the beginning. But putting it up front and center will absolutely do more to get engagement. Such is the medium we are on.

 

[FrogReaver]

There were quite a few votes for 'what is this'. So maybe it's a good time to elaborate a bit on what it is.

Currently I pick some builds, compute the dpr and effective hp. I then plot those. What the graphical position of the points tells you is that points higher have better DPR's than those lower than them, and points further to the right have better eHp than those to the left of them. Practically what this means is that anything lower and to the left of a point is objectively worse for these 2 metrics. Obviously these 2 metrics alone aren't the full picture, but for most combat scenarios they likely have the biggest impact for numerically comparable features, which is why I focus on them.

Ideally the end state would allow filtering for high mobility or strong save tags applied to each build to compare builds with just those tags (these tags would be a bit more subjective due to all the different mobility and save style enhancements there are).

What is the Frontier line? That's the line going through the 2 outermost points. It's useful to show the optimal threshold. Essentially it shows what a linear tradeoff between damage and eHp would ideally look like based on the best damage and best eHp builds. Practically this means any point close to that line is a strong performer, any point far away is a weak performer, at least for those 2 important metrics.

Additionally this allow us to rank builds based on their closest distance to that optimal frontier line (that distance not displayed on the graph, but easily computable). That distance could then be used as a combined offensive and defensive score (or even better normalized into a value between 0 and 1 which is then used as the score). One of my major motivations for this was wanting to be able to better compare defensive builds to offensive builds to balanced builds and I think this will be a strong framework for that.

Also once builds are tagged, and all the numbers are computed, machine learning algorithms can be applied to 1) cluster builds together and 2) determine which features have the most impact on the final rating.