Zoltar is my machine learning system that predicts the outcomes of NFL football games. The first game of the 2019 season is Thursday, September 5 (about three weeks from now) so I’m starting to get Zoltar ready.

I’ve had several different versions of Zoltar over the years. The problem of predicting NFL football scores lends itself to all kinds of interesting algorithms and technologies. Every year I try a different twist or two, usually some kind of new optimization algorithm. Currently I’m using the C# programming language with custom hybrid reinforcement plus neural optimization.

My preliminary work involves getting three data files ready: schedule data, Las Vegas point spread data, and results data. The schedule data has a complication that there are five games that are going to be played at a neutral site — four games in London and one game in Mexico City. In NFL football, the home field advantage is an important prediction factor.

I store all my data as plain text files for simplicity. The key programming challenge is defining data structures to hold the schedule, point-spread, and result data.

It took a couple of hours, but I successfully wrote code to read the games schedule data into memory. My next step will be to get the prediction engine up and running to make preliminary predictions for the first week’s games. Then I need to tune the “advice” engine which determines if Zoltar advises to bet on a particular game or not.

My prediction system is named after the Zoltar fortune telling machine you can find in arcades. That arcade machine is named after the “Zoltar Speaks ” machine from the 1988 movie “Big” starring Tom Hanks. And that movie machine was based on a 1950s era arcade machine called Zoltan.