A week ago, I found myself once again browsing the limited selection of singles in my LGS. I have begun to haunt that place in search of Avatar cards—maybe there aren't many being traded in, but it seems like they sell instantly. I can never seem to find any.

As luck would have it, I found two on this occasion. To date, I have been tracking my collection using a printed checklist (external link) put together by Reddit user JonODonovan. This pen-and-paper solution worked pretty well for my long, floor-bound sessions spent sorting stacks of cards and organising three massive binders. It does not lend itself to digitised tracking very well. My solution has been to quickly take photos of these 28 A4 pages any time I'm going anywhere in-person to trade.

As it happens, my latest photos were not up-to-date. Both cards I purchased were duplicates. In a set of 1.7k cards, two dupes is a rounding error at most–but it felt like a gut punch. My system needed to be properly digitised.

My initial solution was, naturally, an Excel spreadsheet. I don't actually have a Microsoft Office subscription, and I didn't necessarily want to use Google Sheets for hosting, so somehow I ended up creating an .ODS file in LibreOffice Calc. This exercise helped me define the list. Following my recent shock discovery of 54 additional art cards I hadn't previously been tracking, the grand total finally came into view: 1,726 cards. That is my goal.

Turns out spreadsheets are not exactly a web-friendly format (outside of Google Sheets), so I ultimately decided to create a static webpage instead. Behold, the Grandmaster Set Checklist. This tool allows you to filter by set code, card number, card name, treatment, and ownership. It lists every Avatar UB card, playable and non-playable, in every extant treatment.

There is no account system; the tool is entirely client-side. Your checklist can be saved locally as a .JSON file to keep track of what cards you own. In fact, this tool can be run completely offline if you want to download the contents of the website from the GitHub repo (external link).

After painstakingly ticking each box in my new tool, I finally landed on a number my A4 sheets had never revealed to me: 982 / 1726 (56.9%). I'm officially past the halfway point. Before today, my collection was vibes-based; the physical collection was quantified in memory and paper notes. Digitalisation has collapsed that ambiguity into a list of 982 discrete, indexed, versioned print objects. It will take me a little while to recalibrate.

Anyway, I won't be picking up duplicates next time I spontaneously decide to flip through a trade binder.