Hey everyone,
I’ve been spending some time analyzing my algo’s match history and Elo fluctuations, and I’m wondering how others here use that data to guide their improvements. I know tools like bcverdict’s Elo Tracker and Isaac’s replay scripts can help us see patterns, but I’d love to hear from folks who’ve had success turning those insights into actual performance gains.
Do you focus more on fixing weaknesses against specific opponent types, or do you aim for overall strategy shifts? Also, how do you decide when it’s time to scrap an algo and start fresh versus continuing to iterate on it?
Any tips or examples from your own process would be super helpful. I’m trying to take a more data-driven approach and learn from the awesome work others here have done.
Appreciate any advice or feedback you can share. Thanks for keeping this community so collaborative and insightful!
MICHAEL