Setting up a BBAI would definitely be the best solution for me if I don't eventually add a second Kiwi, but I have the impression that would require a fair amount of effort software-wise that exceeds my current skill set - i.e. I had* just enough* to get wsprdaemon running on a Pi4. Perhaps I should do is make it my summer 2022 project, when I return to the KX4AZ/T site where the KiwiSDR is running.

Generally speaking, my goal has been to maximize the unique station counts in a 24 hour period, without tying up the KiwiSDR too much. When I occasionally run a supplementary hopper receiver, I adjust the bands based on the time of day, to focus on what makes the most sense, i.e. at night I don't bother with 15/12/10 meters, but 630/160m are worth including.

This thread actually belongs in the wsprbeacon forum, it occurs to me. My interest/curiosity is in devising a mathematical algorithm to predict how many *unique* stations might be missed on a specific band, if a receiver is only listening for x% of the time over the course of a 24 hour period. Essentially it becomes a cumulative probability of spotting, taking into account the the proportion of the day that the beacons are transmitting, combined with the probability that the receiver will "see" a signal of adequate S/N ratio. My sense is that a 20% duty cycle on a single band would yield much more than 20% of the total in comparison to a continuous (100%) receiving mode. The question is what that % value might be. And actually, this value could be extracted from the WSPR data base if one could interrogate it in the correct way, and see how many unique spots remain if 80% of them were randomly removed from entire set of raw spots in a day. So I should be able to answer my original question once I improve my WSPR database skills.