Earlier quoted context omitted.
This is great, thank you. Another approach is to do forecasting based on historical throughput (eg tasks/day). Generally using "story points" or other guesstimates turn out to be redundant if you have actual data (actual project by mostly the same team). It takes into account stuff like n% of issues "blowing up" into subtasks, and some issues taking longer. I read a great article on the subject which I've unfortunate…
Thanks for mentioning Screenful. Just wanted to comment on your remark: "In general I'd like to be able to just point a tool at N "completed" GitHub projects, and a fresh one - and get a forecast that adjusts as issues are completed and added (possibly filtering on issue tags in completed and new project)" That's exactly how our Forecasting chart works. You can import any number of repositories and projects (classic…
> Will this work if my tasks aren’t all the same size?
> The short answer is yes, your work items don’t have to be the same size for this approach to work. The chances are that If you take 100 tasks in the past and compare those to a sample of 100 tasks in your current backlog, they will be the same size on average. Also, they are likely to be the same size on average regardless of how you measure (e.g. in story points or by some other estimate) or simply by task count.