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I have Time Series data for basketball players in the NBA for 2013. The columns are Date, Player, FG, FGA, 3P, 3PA, 2P, 2PA, FT, FTA, REB, ect.
I would like R to split the data frame by each player, apply a forecasting model to each players statistics and then return a new data frame that results predicted stats for each player.
I would also like to use the HoltWinters - exponential smoothing model of forecasting so that each player's forecast is dependent on its own smoothing constant (alpha). Beta and Gamma will be set to FALSE.
I have R and am just looking for the code. Attached is an example of the data. All variables after "player" need to be forecast. I pan on running this script every day. The data i will be using will consist of every NBA player including data from all games in 2013. Please feel free to rearrange my logic if you feel you can achieve the same result.