Im on my second Bantam tools next draw and love it. Having made a similar transition from generative art to printmaking with a risograph and drawing with a pen plotter; I love the slow physical process of using them.
I added an example to the readme but generally speaking this framework is pretty agnostic and you can use the x, y coordinates in each line with any library
I don't know. During the campaign I found out my wife is pregnant (with our first :D ). That's such a life changing event, I have no idea what I will do in two years time.
On the upside, the existence of that friction definitely points to a gap where value can be added. Another likely source of friction where you can add value is the work anyone working on multiple information sources (whether this is several databases/apis for one sport, or for different sports altogether) has to do to integrate multiple services and data models. If you can identify some people who are doing that work in the first place, you can probably make a business case for how you can simplify their application and give them a single interface/API for all of that data.
I'll also echo the suggestion from @scottrblock on the potential usefulness of various metadata. If all you have are game statistics, while people can obviously do lots of novel analysis on the data, it's fairly obvious what the "use" is. With a wide spectrum of metadata, you might end up simultaneously creating something of value to someone analyzing the effect of weather on different sports/teams/players and for hotel chains trying to set prices based on the historical attendance for all sporting events within 50 miles.
If you could create a revenue model that supports delivering the service both to continual high-volume business users and to users just using the API occasionally to support an analysis project, perhaps it's possible to pass revenue downstream to other data sources. Granted, this adds a number of administrative problems (people submitting data collected/generated/sold by other parties as their own to collect revenue on it; getting low-quality/falsified data; etc.)
* I wasn't aware of stattleship or sportsradar before this thread; no idea how well they cover these.
At this point, I had it in my mind as a broad and large undertaking, we would really need to dig into what information is available. For instance, if we look at baseball, we could make predictions based on historic outcomes and real-time scores but it would be much better the more granular we can get. Current score, current inning, current outs, current count, which players are in the outfield, who are the next 9 people to bat, who is pitching, which ballpark, the weather...
