Create EPA

Adds Expected Points calculations to Play-by-Play data.frame

Usage

create_epa(play_df, ep_model, fg_model)

epa_fg_probs(dat, current_probs, ep_model, fg_mod)

Arguments

play_df

(data.frame required): Clean PBP as input from cfbd_pbp_data()

ep_model

(model, default cfbfastR's ep_model): FG Model to be used for prediction on field goal (FG) attempts in Play-by-Play data.frame

fg_model

(model default cfbfastR's fg_model): Field Goal (FG) Model

dat

(data.frame required): Clean Play-By-Play data.frame as can be pulled from clean_pbp_dat()

current_probs

(data.frame required): Expected Points (EP) model raw probability outputs from initial prediction

fg_mod

(model, default cfbfastR's fg_model): FG Model to be used for prediction on field goal (FG) attempts in Play-by-Play data.frame

Value

play_df with EPA variables added

Updated expected points probabilities with FG make/miss weighted adjustment

Details

Code Description

1. pred_df:

Use select before play model variables -> Make predictions.

2. epa_fg_probs:

Update expected points predictions from before variables with FG make/miss probability weighted adjustment.

3. pred_df_after:

Use select after play model variables -> Make predictions.

4. join_ep:

Join ep_before calcs pred_df with ep_after calcs pred_df_after on c("game_id","drive_id","new_id").

5. kickoffs:

Calculate ep_before for kickoffs as if the pre-play assumption is a touchback.

6. wpa_prep:

Prep variables for WPA.