in Code, Games, Streaming

backlogathon-confidence-screen 1.0

After a bunch of messing around with it over my vacation, I pushed the button to mark a 1.0 release of a very, very simple NodeCG bundle you can use for event streaming as a confidence screen generator.

A short demonstration of backlogathon-confidence-screen in action.

You can find the source and installation instructions here.

During my vacation from work over the holiday season, I thought it would be nice to finally sit down with some JavaScript and figure out a few things. My hobby target for this learning has been NodeCG, which is an open source platform used to generate graphics for livestream broadcasts.

It’s very modular, so it’s possible to produce a bundle that does something specific and attempts to do so very well, and then other broadcasters can pull that bundle into their setups and use it as they wish.

It makes use of a JavaScript library called textfit, which calculates a div size (in this case, a 1920×1080 display area), and then resizes the entered text to fit that area without overflow and with avoiding word wrapping when possible. It’s a neat library, and I’m happy to have found it.

For those not in the know, a “confidence screen” is a display that is usually placed within view of on-air talent, to send them information helpful to their broadcast roles. In the case of FGC events, we generally use it to send commentators information on who is playing the current game, as well as who is next up and when ad breaks and other broadcast beats are scheduled to occur, so they can lead into them smoothly.

For those of you who know what this is, I hope you find this useful. If you aren’t aware of what NodeCG is, I hope you take a look at it and consider using it down the road in your broadcast toolchains.

This is the first in what I’m hoping will be a handful NodeCG bundles I would love to help craft that can bring high-quality production concepts to more small-audience streamers. I also plan on expanding on this bundle in the future with a more holistic and information-dense approach to confidence screen displays. (More on that later.)