We are so excited to share our meet predictor for the 2024 season! Coding is hard, so our data team broke down how our meet predictor was made below to share more insight into how the model works.
The predictor starts with tagging gymnasts with relevant values, such as their injury and year. We then load in Road to Nationals data to provide our scoring figures, including meet info such as home/away sites and opponents, for use in the prediction model.
After the necessary traits and scores are loaded in for both teams and individual gymnasts, we use different functions to carry out the prediction process. Our team scores function takes both past scores and a multiplier to introduce variability into the predictor model (so we don’t get the same result every time). It then creates a lineup of six gymnasts based off their past scores and generates new “predicted” scores for them. Again, a multiplier is added so we get variation in scores and don’t end up with the same scoring lineup over and over. This is done for each event for each team competing, making sure that each lineup has six gymnasts and that their scores max out at a perfect 10.
Then, this data is loaded in to a get meet prediction function that sums up the scores and determines the placement of the…
