I created a metric known as AYOE (Air Yards Over Expected) For NFL Quarterbacks using an XGBoost model where I included inputs regarding…

Interesting to see how accolade models can differ. The NFL QB-MVP model was updated and I used my original methodology where I use pure statistical inputs into a logistic regression model to predict the QB-MVP and also used a methodology where I used principal component analysis for most of the statistical inputs (excludes win percentage, play percentage, interceptions, sacks which are directly inputted into the new logistic regression model). The first model outputs CJ Stroud as the predicted MVP due to his great statistical performance in his rookie season while the PCA model predicts Jalen Hurts as the MVP which largely is based on the Eagles 8–1 record.

I applied three different award prediction models to three different sports (NFL MVP, NBA MVP, MLB ALCY and NLCY). The NFL MVP model was…

Using hockeyR, I created my first hockey analytics project by analyzing the best attacking lines in the NHL 2022–23 season. These lines were determined by various methods, first with the collection of data which included a various amount of scoring, playmaking, playing time and faceoff metrics. These metrics were all…

I have recently gotten more into baseball than I ever have before and was aware of the fact that baseball was arguably the first iconic…

Similar to the NBA MVP prediction model I did previously, I did one for NFL by using train data from 2007 to 2021 (as all the statistics…

I created a project focusing around midfielder analysis in the Big 5 Leagues in the 2022–23 league season. The midfielders were analyzed in…

Using MVP Probabilities

I tweaked my previous project where I predicted the NBA MVP each season from 2000 to 2023 using machine learning and logistic regression by…