Multilevel Expected points added Linear Least Squares
The goal of this package is to ease the testing of my college football prediction points prediction model. The package will be built off the CFB Stats data.
I expect the structure of the package to be small functions that can be piped together:
library(MELLS) library(magrittr) years <- 2005:2014 plays <- readin("play", years) teams <- readin("team", years) runs <- readin("rush", years) pass <- readin("pass", years) drives <- readin("drive", years) games <- readin("game", years) game_info <- readin("team-game-statistics", years) conf <- readin("conference", years) epa_model <- expected_points_build(plays[plays$Year != 2014, ], drives[drives$Year != 2014, ]) fixed_games <- fix_games(games) drives <- fix_drives(fixed_games, drives) model_plays <- combine_run_pass(runs, pass, fixed_games) %>% remove_garbage %>% fix_fcs(teams, conf) %>% add_epa(epa_model) model_values <- generate_preseason_mlm(run_plays = model_plays[["run_info"]], pass_plays = model_plays[["pass_info"]]) %>% add_preseason(run_plays = model_plays[["run_info"]], pass_plays = model_plays[["pass_info"]], drives = drives, preseason_vals = .) weekly_values <- weekly_values_mlm(model_runs = model_values[["run_data"]], model_pass = model_values[["pass_data"]], model_drives = model_values[["drives_data"]])
This package will also contain some model testing functions and validation results.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.