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Hall of Dead Projects

Looking at my 2021 year in review post today, the fact that I never finish big side projects stuck out to me. I’ve never been a big fan of spending a lot of time outside of work programming, mostly because I don’t subscribe to the idea that a developer needs to eat, sleep, and breathe code to have a successful career. However, I have on occasion started a project that sounded interesting to me. To date, I have never finished one of those projects, so here I present the Hall of Dead Projects: ideas I was once excited about, but not actually excited enough to stick with building them.

Kalshi API

Before starting my new job at CHOP, I wanted to practice Go since it had been several years since I’d used it. I had recently found the event contract exchange Kalshi and decided to make a Go wrapper for their market data API because the concept seemed interesting and I was used to working with trade data from my previous job (although I would never dream of trying to trade these things with real money). I intended to build the API wrapper and then some application for viewing and annotating historical data. I made a little progress on the API portion before starting the new job and losing interest. This project was abandoned in November 2021.

NASCAR Cautions

I wanted to attempt to build a Bayesian model to predict the number of caution flags in a NASCAR race. I wrote a Python script to scrape season data (which contained number of cautions) from Racing-Reference and apply some transformation to get a simple set of features. I wanted to eventually add weather information and some other data sources that I thought would be useful for prediction. I eventually abandoned the project (probably because I was having issues getting PyMC3 to work) in July 2021, although the scripts to prepare the dataset are on Github and would be usable if I or someone else wanted to pick this up.


VirtualPitScreen was going to be a web app for decision making in team endurance races on iRacing, inspired by difficulties my team faced keeping track of the strategies the cars around us were using in the virtual 12 Hours of Sebring. During the real-life 12 Hours of Sebring the following week, I started working on a console app that pulled data from the iRacing client and generated events that would let us keep track of lap times, driver schedule, and pit strategy of our team and our competitors. The end goal of the project was to be able to see at any time in the race whether the cars around us were following the same pit strategy and if we could expect to catch the car in front of us based on previous lap times. This would be extremely useful for endurances races and I’d lke to get back to this at some point, but for now it lives in the Hall, abandoned in March 2021.

Minute C#

Inspired by a Reddit post by someone who created daily, one minute videos to explain Python concepts, I decided to do the same for C#. I created Twitter and Youtube pages for the project (with a logo and everything!). The project survived through three videos and planning a few more that I never got around to recording. I abandoned this one around the end of February 2021.


I wanted to build an NLP project to practice some machine learning skills I had let fade away after grad school. I had an idea to download comments from the /r/NASCAR race threads and build a binary classification model to predict whether or not the comment described something happening in the race. The end goal here was to use this to select comments that would provide a live overview of what had happened so far in the race. I intended to eventually pull in tweets as well and build other features to see what people were talking about during races. I got as far as using PRAW to download a ton of comments from old race threads before abandoning the project some time in 2020.