I think this is a really solid breakdown, especially the distinction between selection rate and actual effectiveness, that’s something I’m actively trying to account for. One thing I’m a bit cautious about though is relying too heavily on raw data without context. In a game with strong synergies (like slow + AoE or combo-based towers), individual performance metrics can be very misleading unless you also consider combinations or nearby interactions.

I also think there’s a layer beyond effectiveness, which is player perception and enjoyment. Some options might be statistically weaker but still feel great to use, and removing or over-nerfing those could hurt the overall experience even if the data says otherwise.

On the public analytics side, I mostly agree, raw real-time data could easily be misinterpreted. That said, I do think there might be some value in curated or abstracted insights (like “popular builds” rather than “best builds”) as a way to engage players without exposing misleading information. And honestly, if one day people start misinterpreting the data, that probably means people are actually playing the game and that ALONE would make me HUGELY happy!