Quote:
Originally Posted by Athletics
Thanks to NoOne and Rizon, I got inspired to sit down for a weekend and code a Python script to read in CSV files, use PyMongo to save the raw data to MongoDB, and then query the raw data from MongoDB to calculate stats.
I wanted an easier way to see wOBA, ISO, and xFIP splits for my entire fictional league. It's not user-friendly at all and runs from the command line.
Also, compare the game save file to the database size.
3.7G braves.lg/
ootp_braves 0.953GB
Source code and example output can be found here. https://github.com/namtsui/ootp |
i never saw rizon's reply. i don't put in that kind of effort. i am fine with the stats in game.
the only spreadsheet i have made for this game is to track stats related to LTMs. virtually everything is automated excepted adding or reducing # of years to be evaluated. i would have had to look that up. it's been 20 years since i learned this stuff and i don't do anything sophisticated with spreadsheets in my normal life since then. effort would not have matched the return. i just keep two template files - one for 100, the other 200 years.
if i make anything in the future, it will be to test things. e.g. at some point i'd like to do is flesh out which pitch combinations result in lower ERAs than what is projected in the player editor.
once you set up the data (anythign repeatable = can be automated), the spreadsheet does all the hard work, or you can use VB to create your own functions.
you can know every "best" decision within this video game, if someone puts in the time, lol. again, not really worth the effort and probably removes all the fun.