How to apply a trained Random Forest model to a new data set in R?
You need to setup another data frame that has the unlabeled 2019 observations. Assuming you have multiple predictors, your new data would have the exact same columns as your 2018 data but with no 2019_td column (since you presumably don't know anything about the 2019 season). That is, the players in 2019 that you wish to predict on, along with their predictors, but no target column.

Once you have the data frame, you can use predict(trained_model, newdata) to score your new predictions.

Edit: As an aside, you have data that is influenced by time. What happens if a player gets injured next season? What about trends in the players performance?