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Update on NBA Game Log

Now that the NBA season is underway, I am using the NBA game log tool I built. This allows me to track the games I watch and the notes I take. I’m primarily interested in tracking how much I have watched of each team so I can keep an eye on the entire league.

This idea was included in my previous projects post. Last season I tracked the games I watched in a spreadsheet. So far this app is easier to use, especially for looking at the data as a whole, and adds the capability of logging notes. 

I built this app using the Javascript MEAN stack: MongoDB, Express.js, Angular, and Node.js. This was my most ambitious Javascript project to date. I have learned a lot, especially regarding API design. I’m proud of what I have built so far but have more I would like to do such as:

  • Better design and interface
  • Password reset for users
  • Different analysis dashboards, such as for a particular team or player
  • Customizable sharing options for different users

Anyone can create an account and use the app but I mostly built it for my NBA viewing and for my Javascript experience. 

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Projects

Here are some projects I’m currently working on and/or thinking about kickstarting:
A computer version of the Parker Brothers World Flag Game About The United Nations. This is a classic game for the Needham family, especially at our cottage. I’m working on this game as a chance to practice the Angular framework and possibly the full MEAN stack. I wanted to use a board game that, as far as I know, has not been digitized before.

An NBA game log tool. I watch a lot of the NBA and I try to go beyond watching solely the best teams. Two seasons ago I used a Google Sheet to track what games I watched to ensure I was getting a decent spread of all 30 teams. I want to make a tool to easily log which games I watch, how much of a game I watch, and my notes on what I observe. Additional features would include tagging and looking up notes based on individual players as well as a login system for multiple users. My instinct is to make this with the Flask Python framework.

An NBA lineup quick view tool. The official NBA website has a great tool for analyzing different lineups. I want to make a handy reference where people can quickly see the best and worst lineups in the league and for each team on the basis of offensive success, defensive success, and net success. You could in theory do this with the NBA.com site, but it requires a number of steps. I want to create a website that has this data already prepared for you. This would likely be a Flask project as well.

Reach out to Scott Sumner and discuss building a cryptocurrency linked to NGDP as he proposed here. The step I need to take between here and now is building a just-for-fun cryptocurrency as proof of competency.

Calculate which NBA player had the highest game score against each NBA team last season. I did this for the 2016-2017 season.
Track how accurate Pythagorean win projections were throughout the previous NBA season. This was my original goal in starting a weekly NBA blog. I have the data ready to analyze, I just haven’t followed through on it yet!

If you read this post and are interested in collaborating on any of these projects, email me!