31298 entries retrieved in 4.0733235 seconds
… parsed in 16.9439467 seconds
… insert statements created in 0.2638696999999972 seconds
… inserted in 14.0668617 seconds
*Complete.
952 Users added.
25609 Unique Hero Team setups added.
2330 Unique Opponent Team setups added.
31222 Game data inserted.
in 35.348001599999996 total seconds
So the interesting thing i see here is the 25609 Unique Hero Team Setups
(this has something to do with the way I am storing a given hero team for a given game, and creating a unique hash for it - so i can run analysis on it more efficiently.
However, what I did do was preserve the order of the team → so Bunker, Tachyon, Legacy is considered a different team than Bunker Legacy Tachyon, which is different than Legacy Bunker Tachyon … and so on.
Im not sure if this is worth recording or not. Thoughts?
Yep. I still hate writing SQL queries. But… its the only way to make this kind of dynamic recall possible (my sql query is pretty brute force here, im sure there is a more elegant way to write these)
but this kind of query wouldnt be possible on the fly with a Dynamo (noSql) option so… here we are
Retrieval backend is just about finished. Still need a way to add games via api though.
If you’re someone who is a developer of front end sites and would like to help me out on building some, reach out! I’m starting the build in react, and my design skills are nil so yeah. Help is appreciated.
Or if you’d like to know how to access all this, well I’m not quite there yet, but I’ll be providing the retrieval link in the near future for anyone to use, and a private, API key enforced insert link (and a JSON schema for validating your input against) for those who want to hook into it directly.
The Haka, Legacy, Visionary, Tempest, and Wraith likely has to do with cheese potential out of the base box. Viz and Tempest helps Legacy keeps his more powerful Ongoings out. Wraith and Viz help manage the villain deck. Haka can swallow villain targets with Savage Mana.
While some of these make obvious sense (Legacy, GI Bunker, …) a bunch don’t! Why doesn’t Expatriette go last? What’s up with the Naturalist? Why so many games with Akash’Thriya in the lead?! I’m particularly curious why some characters’ distributions peak in the middle (i.e. usually neither first nor last), and why some aren’t uniform across the middle range but peak at, like, position #3. Is there any weighting applied depending on ?
I’m tempted to wonder if there’s a way you could capture whether a particular item is relevant for an unlock/achievement but I’m sure that would be a huge effort so don’t take it as more than idle wondering.
Its also important to remember that these have been collected since 2014 (there is actually 2 more years worth of data that is in a separate google sheet that i haven’t uploaded to the database yet) and so older heroes/villains/env have more time to get more representation. I will have to, when I start work on the Front End, plot out some of these things in interesting graphs - like : what density of entries over time - I would bet that there were far more games being added in the early days then there are now, meaning those early characters have a larger representation.
Edit: Oh and no weighting. Just straight raw counts.