Advanced IndyCar stats and analytics
Although I did not end up writing articles as much as anticipated in 2021, I did keep up as always with tracking IndyCar stats, including my Elo ratings. During the 2021 season I made some updates to how the ratings are calculated. This was partially an exercise to make sure my championship simulation was getting the best data possible, and also part of a regular process to make sure the model is tuned properly.
Continue reading “Elo Ratings Had a Good 2021”
If you followed this site last year you’ll remember the championship projections model that simulated the remaining races of the season 50,000 times and returned the probability of every driver finishing in every position in the championship. This model was rooted in each driver’s average finishing position, average track position, consistency, and influenced by how many races had already been completed. For this season I have completely overhauled the projection system and I am going to run through a few of the major changes in this article. Continue reading “Upgrading the Championship Projection Model”
For the past few years, the stats that I tracked on this website have been posted with the help of Google Sheets. This worked fairly well, but it didn’t support even simple sorting by columns or searching for drivers. For this upcoming season, I have completely changed the way my stats will be presented and available to people. I have been developing an R Shiny app that will be the new home for all of the stats that I track throughout the IndyCar season. It has a lot of nice features that I just want to briefly mention in this article so that you can get the most out of using it. It is still very much under active development, so there will likely be a few updates to it as I continue work and receive feedback. Continue reading “A New Way to View Stats on The Single Seater”
One interesting topic I’ve wanted to tackle for some time is forecasting the IndyCar championship. Who is most likely to win the championship at any point in the season? Further, what is the probability of a driver finishing in a specific position in the championship?
Continue reading “Simulating the IndyCar Season 50,000 Times”
In my opinion, there isn’t currently a good way to evaluate team strategy in IndyCar based off of the traditional statistics of starting and finishing position. If a car improves throughout a race, was it because of good strategy, great passes, or just being fast? It’s not particularly easy to tell and even if you watch the race, there’s too many cars and different things going on to get a good measure of what happened by the eye test.
Continue reading “A Statistic to Assess IndyCar Race Strategists”
The Single Seater 